HomeMy WebLinkAbout12-12-2017 Item 01 - Community Choice Energy study Sessin
Meeting Date: 12/12/2017
FROM: Greg Hermann, Acting Assistant City Manager
Michael Codron, Community Development Director
Prepared By: Marcus Carloni, Sustainability Coordinator
SUBJECT: COMMUNITY CHOICE ENERGY STUDY SESSION
RECOMMENDATION
1. Receive and file the Technical Feasibility Study on Community Choice Energy (CCE) for the
Tri-County area including San Luis Obispo County, Santa Barbara County, and Ventura
County (Attachment E); and
2. Receive and file an initial feasibility study prepared by Pilot Power Group for the intra-
county region – City of San Luis Obispo and County of San Luis Obispo (Attachment F); and
3. Provide staff with direction regarding whether or not to continue to pursue community choice
energy options as follows:
1. Form a new CCE program; or
2. Solicit proposals to identify an existing CCE program to join; or
3. Discontinue or pause the pursuit of a CCE program at this time.
REPORT-IN-BRIEF
Climate Action was included as a Major City Goal in 2017-2019 Financial Plan. A key action in
this goal included the following objective:
Assess and report the requirements to achieve the “net-zero carbon City” target including
feasibility analysis and implementation of a Community Choice Energy program.
The purpose of this staff report is to provide information on the feasibility analyses completed to
date for CCE programs, pursuant to the Major City Goal objective, and for the City Council to
provide direction on next steps. In 2015 the City Council approved a resolution authorizing the
City’s participation in the exploration of Community Choice Energy. Since approval of that
resolution, the City has been involved in two feasibility study efforts: 1) the Intra-County Study -
a pro-bono “initial feasibility study” prepared by Pilot Power Group designed to provide a high-
level assessment of CCE feasibility within San Luis Obispo County, and 2) the Tri-County
Feasibility Study – a multi-jurisdictional feasibility study providing a detailed analysis of eight
geographical CCE participation scenarios across San Luis Obispo, Santa Barbara, and Ventura
Counties (including the City jurisdictions within those Counties).
The findings of the Intra-County Study generally align with the findings of a peer review of the
Tri-County study, finding with high probability that a new CCE program would be able to cover
its costs, generate net revenue, and maintain rate competitiveness across the studied scenarios.
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The results of the Tri-County study were released in September 2017 and conclude that a newly
created regional CCE program spanning San Luis Obispo, Santa Barbara, and Ventura Counties
is not likely to be a viable venture in terms of the CCE program’s ability to provide competitive
rates and remain a solvent organization. However, the results of the peer review indicate that it
may be possible for a local or regional CCE program operating within Pacific Gas and Electric
Company (PG&E) territory only (e.g. in San Luis Obispo and northern Santa Barbara County) to
offer competitive rates while covering its costs.
The Tri-County Feasibility Study and the Intra-County Study, however, did not consider the
viability of joining an existing CCE program, which is another potential option for the City. Of
the in-development CCE’s, Monterey Bay Community Power (MBCP) is the only one within
PG&E service territory and the City could pursue joining this effort, or other CCE programs
accepting new jurisdictions.
In addition to the option to join an existing CCE program such as MBCP, this report provides
several other options for the City Council’s consideration and direction to staff. Such options
include forming a new local CCE program that only includes the City of San Luis Obispo, and/or
forming a new CCE program wherein the City takes the lead to work with and include other
jurisdictions to establish a larger CCE. General pros and cons with these options are provided
herein together with a comparison table, and next steps associated with each of these options,
dependent upon City Council direction.
Note: for a glossary of terms used in this report please see Attachment A.
DISCUSSION
Background
1. About Community Choice Energy
Community Choice Energy (CCE), also known as Community Choice Aggregation (CCA),
enables local governments to leverage the purchasing power of their residents, businesses, and
governments to purchase or generate power for their communities. When a CCE program is
formed, the CCE provider purchases the electricity—which typically includes a higher
percentage of electricity from renewable resources like wind and solar—and sets the rates
charged to customers. The existing “investor-owned utility” (IOU), PG&E in our region,
continues to deliver the electricity purchased by the CCE provider over their power lines and
continues to provide metering, billing, and other customer service as they do now. The day-to-
day experience for the customer is the same, meaning services continue to be provided by PG&E
and the only difference is that energy is purchased through the CCE.
Currently, there are nine CCE programs in operation throughout California: five in the San
Francisco Bay Area, one in Humboldt County, and three in the Los Angeles area. The longest-
standing CCE program is MCE Clean Energy, which began operations in Marin County in 2010
and has since grown to also include parts of Napa, Solano, and Contra Costa Counties. More
than 20 jurisdictions are actively studying or developing CCE programs, with several programs
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expected to launch in 2018. Attachment D includes a matrix prepared by County of Santa
Barbara staff that compares the nine operational CCE programs and three in-development CCE
programs. All of the operational and in-development CCE programs conducted feasibility studies
that suggested CCE would be economically viable for their communities.
2. Steps to Forming a CCE Program
There are three basic steps to forming a CCE program as provided below.
• Step 1 (Feasibility): Assess the viability of CCE via a feasibility study. The study is
typically prepared by a third-party with energy industry expertise with input from local
government staff/elected officials and community members. A key milestone at this stage is
obtaining electricity consumption data from the existing investor-owned utility (e.g. PG&E)
and beginning to develop relationships with the investor-owned utility (IOU) as a working
partnership with them is required.
• Step 2 (Implementation): If feasible, the next step is to set up the CCE program
implementation organization, prepare an implementation plan and IOU service agreements.
If multiple jurisdictions are involved, a joint powers authority (JPA) is formed. The
implementation plan must be certified by the California Public Utilities Commission and
provides more detail about how the CCE program will be launched and operated. Power
procurement and other service contracts may also be initiated during this phase, and more
robust outreach and education efforts can occur.
• Phase 3 (Launch): Launch the CCE program. This includes setting up the systems and
processes, and securing vendors and staff needed to provide electricity service to customers.
Key activities include hiring staff/vendors, purchasing power, setting up power scheduling
systems and procedures with the California Independent System Operator, developing
customer support programs, establishing billing systems and processes with the IOU,
posting a California Public Utilities Commission bond and required deposits, developing
marketing materials, and notifying customers of program launch.
Previous Council Direction
In December 2013 City Staff presented the City Council with a detailed report to educate the
Council and community about CCE. No formal action was taken at that time other than
exploratory steps including appointing Councilmembers to a CCE exploration advisory
committee and allow the City Manager to release City power usage data to facilitate exploration
of potential feasibility. In March 2015 the City Council approved Resolution No. 10609
confirming the City of San Luis Obispo’s participation in the exploration of CCE. The resolution
authorized participation in an inter-jurisdictional investigation into CCE feasibility allowing
execution of appropriate documents to allow technical consultants to acquire energy usage load
data from the electric distribution utility for analysis as part of the feasibi lity study. (See
Attachment B for the December 2013 staff report, March 2015 staff report, and March 2015
resolution.)
Since adoption of the resolution, City staff have been involved in two CCE feasibility studies -
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the Central Coast Power feasibility study (also known as the “Tri-County” feasibility study) and
the Intra-County initial feasibility study. Details on these two efforts are provided below.
Update on efforts since Council direction
1. Tri-County Feasibility Study
In 2016, the Tri-County (San Luis Obispo, Santa Barbara, and Ventura Counties) CCE feasibility
study effort began; led by the County of Santa Barbara with funding from ten other jurisdictions 1
and the Community Environmental Council, and was conducted by Willdan Financial Services
(Willdan). A peer review was subsequently conducted by MRW & Associates. Staff from the
eleven jurisdictions participated in an Advisory Working Group (AWG) to help guide and
oversee the feasibility analysis, provide outreach support, and monitor policy and program
developments related to CCE. The City of San Luis Obispo was not directly apart of the AWG
but worked closely with County of San Luis Obispo and County of Santa Barbara staff to
monitor the process.
Scope of Tri-County Feasibility Study
This study evaluated the feasibility of forming a new CCE program run by one or multiple local
governments in the Tri-County Region. The study did not consider the viability of one or more
jurisdictions joining an existing CCE program.
The study assessed financial feasibility in terms of the ability of a local/regional CCE program to
provide competitive electricity rates while meeting policy goals and covering substantial CCE
program formation costs and ongoing operating expenses over a ten-year study period (2020-
2030).
The Advisory Working Group (AWG) selected eight participation scenarios to explore the
feasibility of different sizes and configurations for the CCE program and the potential effect of
customer demographics. In addition, due to the complexity of evaluating the feasibility of
forming a new CCE, the AWG took the additional prudent step to commission MRW &
Associates (MRW) to conduct a third-party peer review of the Willdan feasibility study – to
evaluate the assumptions and conclusions of Willdan’s work. For details on the participation
scenarios and discussion of the Tri-County Feasibility Study see Attachment C (County of Santa
Barbara Staff Report to Board of Supervisors October 3, 2017) and see Attachment E (Tri-
County Feasibility Study).
Findings of Tri-County Feasibility Study and MRW Peer Review
In summary, the feasibility study indicates that a newly created regional CCE program spanning
San Luis Obispo, Santa Barbara, and Ventura Counties is likely not a viable venture in terms of
the CCE program’s ability to provide competitive rates and remain a solvent organization. Key
factors that led to this conclusion are the very large size of the region leading to expensive and
1 County of San Luis Obispo, County of Santa Barbara, County of Ventura, Cities of Camarillo, Carpinteria,
Moorpark, Santa Barbara, Simi Valley, Thousand Oaks, and Ventura.
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risky debt issues, assumptions about significantly higher than expected future power cost
projections, and complications arising from potentially operating in two utility service territories
(Pacific Gas and Electric (PG&E) and Southern California Edison (SCE)). SCE’s relatively less
expensive rates also contributed to the infeasibility finding.
However, the results of the peer review (Attachment E, Tri-County Feasibility Study, Appendix
L) indicate that it may be possible for a local or regional CCE program to operate within Pacific
Gas and Electric Company (PG&E) territory, i.e., in San Luis Obispo and northern Santa Barbara
County, to offer competitive rates while covering its costs.
In its peer review, MRW did a rate comparison for unincorporated San Luis Obispo Count y
which is fully within PG&E territory. Figure 1 (below) shows the CCE program’s expected rates
(as shown by the stacked bar charts illustrating CCE costs) compared to the applicable IOU rates
(blue line) for unincorporated San Luis Obispo County. Figure 1 shows that, after the first year,
the unincorporated San Luis Obispo County CCE program’s rates are expected to also be
roughly the same/lower than PG&E’s rates, with the exception of a three-year period from 2025
through 2027 where the rates are projected to exceed PG&E’s rates, and then dip back down
below PG&E rates for the remaining years. This three-year anomaly is due to the anticipated
closure of the Diablo Canyon Power Plant, which is expected to temporarily lower PG&E’s rates
due to PG&E’s plans to replace Diablo Canyon’s output with low-cost energy efficiency rather
than new generation.
Figure 1. CCE versus PG&E Rate Comparison, Unincorporated San Luis Obispo County Middle of the
Road (50% Renewable)
Scenario
It is worth noting that the Tri-County feasibility study evaluates the feasibility of forming a new
CCE program run by one or multiple local governments in the Tri-County Region. The study did
not consider the viability of one or more jurisdictions joining an existing CCE program, which is
a potential option for the City of San Luis Obispo.
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Tri-County Study – Current Status
At this point, the County of San Luis Obispo, County of Ventura, and the other core jurisdictions
are no longer involved in the Tri-County study. The study is still moving forward (scope has
been adjusted, new consultants have been hired) and continues to be led by County of Santa
Barbara staff, but with the withdrawal of the jurisdictions noted above, the study’s scope is now
limited to assessing the feasibility of a CCE program within Unincorporated Santa Barbara
County and the City of Santa Barbara and is now being performed by Pacific Energy Advisors.
The County of Santa Barbara Board has also directed their staff to look into the possibility of
joining the two nearby in-development CCE programs (Monterey Bay Community Power for the
portion of the County in PG&E territory and Los Angeles Community Choice Energy for the
portion within SCE territory).
City Staff have been in communication with the County of Santa Barbara staff leading the Tri-
County effort. Dependent upon the results of the new feasibility study there may be an
opportunity for the City of San Luis Obispo and other local jurisdictions to join with Santa
Barbara to form a Joint Powers Authority for a CCE program. Upon direction from the City
Council, staff can continue to work with County of Santa Barbara staff to monitor the feasibility
study and discuss the City’s involvement.
2. Intra-County Feasibility Study
While the Tri-County Feasibility Study was underway, the City of San Luis Obispo worked in
parallel to analyze the feasibility of an intra-county CCE. On July 14, 2015 the City of San Luis
Obispo invited the County of San Luis Obispo to participate in an intra-county “initial feasibility
study” for a CCE program within the County of San Luis Obispo. Each of the other six
incorporated cities in the county were invited to participate, but none chose to do so. The initial
feasibility study was offered at no cost and has been completed by Pilot Power Group using an
analysis of regional energy use data from PG&E. The final report is provided as Attachment F.
The initial feasibility study provides a high-level assessment of the likelihood that a new CCE
program in San Luis Obispo would be able to maintain rate competitiveness and generate
revenue in excess of program costs. The study includes three geographic participation options
(County of San Luis Obispo only, City of San Luis Obispo only, and combined County and City
of San Luis Obispo) and two scenarios. Scenario 1 assumes the CCE program would operate
with the minimum amount of renewable energy needed to remain compliant with state
requirements – essentially the CCE would have the same renewable portfolio as PG&E in this
scenario. Scenario 2 assumes the CCE program would include 50% renewable energy in its
portfolio.
In all three geographic participation options and both scenarios, the study finds with high
probability that a new CCE program would be able to cover its costs, generate net revenue, and
maintain rate competitiveness. A summary of the results of the study is provided in the table
below. As an example, the table shows that a “City only” CCE (dark blue column) providing
50% renewable energy (Scenario 2) would have 65% probability of generating revenue in excess
of expenditures in the first year of operation (2018). Based on the assumptions of the study, the
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expected net revenue in year one would be $853,189. The simulations run as part of this study
showed that 46.63% of the time, the model produced a net revenue amount that was equal to or
exceeded the expected net revenue of $853,189.
In concluding that conditions are favorable to create a CCE program in San Luis Obispo, the
initial feasibility study findings generally confirm the findings of the MRW peer review of the
Tri-County Feasibility Study, noted above, which are that a City only option or combination of
jurisdictions with PG&E service area are likely financially viable.
It is important to note, however, that given the pro bono nature of the initial feasibility study, and
the associated limits on its scope, these findings should only be used to indicate initial feasibility.
A more in-depth, full feasibility analysis is the next step to determine whether a City of San Luis
Obispo led CCE is viable. As part of the Major City Goal, the 2017-2019 Financial Plan
allocated $25,000 to pay for this type of analysis.
Options for Council Consideration
With the results of the Tri-County and Intra County feasibility studies described above, staff
have included two basic options for the City to pursue Community Choice Energy, as provided
below.
1. Form a New CCE Program
Pros: Local control, may include multiple local jurisdictions in our efforts.
Cons: Slower (1 to 2 years), potential additional financial risk to the City, potentially more
expensive and resource intensive.
There are a number of options for forming a new CCE program which , if feasible, could include:
a) the City working to form a local CCE program that only includes the City of San Luis Obispo;
b) the City taking the lead and working with other jurisdictions to establish a larger CCE
program operating together as a joint powers authority; and/or, c) the City continuing to monitor
the Tri-County effort and possibly join Santa Barbara to establish a larger CCE program.
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Generally, the next step for options a and b, above, would include staff preparing a Request for
Proposals (RFP) to obtain, at a minimum, a consultant to assist in preparation of a full feasibility
study to provide a complete assessment of the viability of a CCE program. A full feasibility
study for the City of San Luis Obispo (and potentially including other jurisdictions) appears to be
a viable option based on the results of the Intra-County initial feasibility study which indicates
potential feasibility across all studied scenarios, as described above.
Cost Examples
Redwood Coast Energy Authority Example. Initial financial and startup costs can be significant.
Recently, new methods have emerged such as the approach used by Redwood Coast Energy
Authority (currently operational CCE) to finance a new CCE program. Their approach included
putting out an RFP in search of an entity, or group of entities, to provide comprehensive services
to support the development, financing, launch and operations of a CCE program with n o upfront
costs paid by Redwood Coast Energy Authority (RCEA). In this approach, the successful bidder
undertakes the development and launch of the program at their own risk and would receive on-
going operations fees after and contingent on the successful launch of the CCE program. If the
City undertook this approach it would essentially mean no costs would be borne by the City until
revenues from the operating CCE program are received.
California Choice Energy Authority Example. Another example of an initial financing approach
is the method proposed by the California Choice Energy Authority – a Joint Powers Authority
(JPA) of the City of Lancaster and the City of San Jacinto which is governed by the Lancaster
City Council with each City joining as an associate member of the JPA. CCEA offers initial
support (as well as continued support) for starting a new CCE. Note: their experience is in
Southern California Edison territory. CCEA offers their services (including use of their
contracted consultants) to help jurisdictions assess feasibility, prepare an implementation plan for
submittal to the California Public Utilities Commission and administrative support to manage
these efforts for a cost of $63,000. The City has currently budgeted $25,000 to support initial
efforts associated with establishing a CCE.
In addition to initial financing, CCEA has a hybrid approach to implementation where
jurisdictions join CCEA to group together and share operational expenses and leverage
economies of scale to help keep costs down, such as the cost of power purchasing, but individual
jurisdictions still operate their own local CCE (i.e. share operational expenses but still keep local
control of CCE revenues). If directed to “form a new CCE” staff will explore this approach
further, however, two initial concerns include 1) CCEA operates in SCE territory and doesn’t
have experience in PG&E territory, and 2) lack of control and the ability to decide key policy
decisions which under CCEA are currently solely governed by the City of Lancaster’s City
Council.
2. Join an Existing Program
Pros: fast (as soon as early 2019), cost effective, low risk to the City.
Cons: less control – City would be one of several votes on the JPA.
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Monterey Bay Community Power
The Tri-County Feasibility Study and the Intra-County Study did not consider the viability of
joining an existing CCE program, which is a potential option for the City. For a list and details of
operational and in-development CCE’s, see Attachment D. Of the in-development CCE’s,
Monterey Bay Community Power (MBCP) is the only one within PG&E service territory and the
City could pursue joining this effort, or other CCE programs accepting new jurisdictions.
MBCP begins serving customers in 2018 and currently consists of a Joint Powers Authority
between the Counties of Monterey, Santa Cruz, and San Benito. MBCP has already obtained all
the financing and funding needed to operate and is projecting approximately $39 million in net
revenue in its first year of operation (2018, partial year), and approximately $40-50 million in net
revenue in its first full year of operation (2019). The agency has discretion to set its rates to be
identical to PG&E rates with customer credits issued annually or quarterly depending upon
customer class, and their standard electricity portfolio is 100% carbon free by purchasing from
hydroelectricity sources.
Staff have been in preliminary discussion with the Chief Executive Officer of MBCP who has
expressed interest in the City of San Luis Obispo joining MBCP. The cost to join would be
approximately $25,000 to $50,000 to cover consultant costs associated with amending MBCP’s
Implementation Plan and resubmittal to the California Public Utilities Commission for re-
certification.
Other Existing Programs
While MBCP is the only option currently available for the City to join with an existing CCE in
PG&E service territory, several other CCE’s exist. As previously mentioned, the Santa Barbara
County Board of Supervisors recently directed its staff to look into Los Angeles Community
Choice Energy; however, that direction was only for its southern portion that is in SCE territory.
Staff can continue to monitor options available for joining a CCE located outside of PG&E
territory, but there are no clear options currentl y available to join.
3. Discontinue/Pause Pursuit of a CCE
Pros: Potential for new, better, CCE model to emerge.
Cons: Lose greenhouse gas emission reduction potential and economic benefit of CCE, rapidly
changing regulatory environment may preclude future options.
The electricity market and policy environment are rapidly transforming. While CCE programs
have enjoyed tremendous growth over the past couple of years, both in terms of the number of
programs and expansions of existing programs to serve more customers, the IOUs (e.g. PG&E)
have had time to adjust to a more competitive market in a way that poses a greater risk to new
CCE program formation. In addition, significant regulatory and potential legislative changes are
possible in the next couple of years for CCE programs. Two bills were being proposed during the
last legislative session that would have effectively stopped the formation of new CCE programs,
and similar bills may be proposed in the near future.
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The City Council could choose to discontinue or pause pursuit of a CCE program at this time to
wait and see what happens with the market. However, the City may lose the opportunity of
Community Choice Energy based on shifts at the regulatory level. If the City lost the opportunity
to participate in a CCE, it might be difficult to achieve established net carbon community goals.
This option is not recommended since options exist that may reduce the City’s upfront risk and
costs of launching a CCE program.
COMPARISON OF CCE OPTIONS
Speed Cost Risk Local Control
Regionalism
1
Form a New CCE Program
City of SLO Only Med Low-High
Med/Hig
h High Low
City of SLO + other Jurisdictions Med Low/Med Med Med Med
Monitor/Join Tri-County Effort2 Slow Med Med Med High
Join an Existing Program Fast Low Low Low Low
Discontinue or Pause Pursuit n/a n/a n/a n/a n/a
1 A regional approach (multiple jurisdictions) to reducing Greenhouse Gas Emissions in San Luis Obispo
2 At this time the results of the new study are unknown
QUESTIONS FOR COUNCIL CONSIDERATION AND DIRECTION
Staff has provided the following focused questions to facilitate City Council direction to help
guide the City Council in their deliberations.
Questions for City Council direction
Yes No
A. Pursuit of Community Choice Energy (CCE)
1. Continue pursuit of CCE
2. Pause pursuit of CCE
3. Discontinue pursuit of CCE
B. Form a new Community Choice Energy program?
1. City of San Luis Obispo Only?
2. City of San Luis Obispo and pursue other jurisdictions?
3. Continue to monitor the tri-county effort and possibly join Santa
Barbara?
C. Join an Existing Program?
1. Monterey Bay Community Power or research additional alternatives
outside of PG&E service territory?
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Questions for City Council direction
D. Evaluation Factors
1. What criterion or set of criteria should be prioritized in evaluating
CCE options?
a. Renewable portfolio
b. Pricing
c. Governance (i.e. local control vs. ease/cost of administration)
d. Risk tolerance
e. Other
Should the City Council direct staff to continue pursuit of Community Choice Energy staff has
provided a summary of next steps by option below:
1. Option B.1 (City of SLO Only): If chosen, staff will prepare a Request for Proposal
(RFP) and seek consultant(s) qualified to move us forward with Community Choice
Energy. Based on existing limited staff resources and funding, staff would seek
consultants who can provide comprehensive services to support development, financing,
launch and operation of a CCE program similar to the Redwood Coast Energy Authority
model described above. The RFP will be reviewed by the City Council for approval prior
to issuance.
2. Option B.2 (City of SLO + other Jurisdictions): If chosen, staff will reach out to other
jurisdictions within San Luis Obispo County as well as jurisdictions in Santa Barbara
County that are within PG&E service territory (e.g. Santa Maria) to assess and encourage
interest in joining the City. Then staff will prepare an RFP as discussed in option #1
above.
3. Option B.3 (Monitor and Possibly Join Santa Barbara): Note: this option could be
combined with options B.1 and 2 above. If chosen, staff would continue to monitor the
Tri-County effort and see what options exist for the City to join Santa Barbara should the
new review find feasibility.
4. Option C (Join an Existing Program): If chosen, staff will continue discussions with
Monterey Bay Community Power and search out opportunities to join other similar
programs by issuing a Request for Information to see if other CCE programs are
interested in allowing the City to join.
ENVIRONMENTAL REVIEW
Direction from the City Council regarding Community Choice Energy does not constitute a
project subject to environmental review under the California Environmental Quality Act (CEQA)
pursuant to CEQA Guidelines Section 15262, as the actions involve only feasibility or planning
studies for possible future actions which the Council has not approved, adopted, or funded and
does not have a legally binding effect on later activities.
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FISCAL IMPACT
The City Council has budgeted $25,000 for pursuit of Community Choice Energy through the
Climate Action Major City Goal work program. Fiscal impact will be researched in detail and
determined dependent upon Council direction.
ALTERNATIVES
The City Council could choose no options and elect to suspend all efforts to pursue a CCE. This
alternative is not recommended as CCE’s have shown promise in both reducing energy costs and
providing greater renewable energy options to help jurisdictions meet GHG reduction goals.
Attachments:
a - Glossary of Terms
b - December 2013 Council Agenda Report - March 2015 Council Agenda Report - March
2015 Council Resolution
c - County of Santa Barbara Staff Report to Board of Supervisors October 3, 2017
d - Matrix Comparing CCE Programs
e - Tri-County Feasibility Study (Executive Summary)
f - Intra-County Initial Feasibility Study
g - Council Reading File - Full Tri-County Feasibility Study
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Glossary of Terms
aMW: Average annual Megawatt. A unit of energy output over a year that is equal to the energy
produced by the continuous operation of one megawatt of capacity over a period of time (8,760
megawatt-hours).
Basis Difference (Natural Gas): The difference between the price of natural gas at the Henry Hub
natural gas distribution point in Erath, Louisiana, which serves as a centr al pricing point for
natural gas futures, and the natural gas price at another hub location (such as for Southern
California).
Buckets: Buckets 1-3 refer to different types of renewable energy contracts according to the
Renewable Portfolio Standards requirements. Bucket 1 are traditional contracts for delivery of
electricity directly from a generator within or immediately connected to California. These are the
most valuable and make up the majority of the RECS that are required for LSEs to be RPS
compliant. Buckets 2 and 3 have different levels of intermediation between the generation and
delivery of the energy from the generating resources.
Bundled Customers: Electricity customers who receive all their services (transmission,
distribution and supply) from the Investor-Owned Utility.
CAISO: The California Independent System Operator. The organization is responsible for
managing the electricity grid and system reliability within the former service territories of the
three California IOUs.
California Energy Commission (CEC): The state regulatory agency with primary responsibility for
enforcing the Renewable Portfolio Standards law as well as a number of other, electric -industry
related rules and policies.
California Public Utilities Commission (CPUC): The state agency with primary responsibility for
regulating IOUs, as well as Direct Access (ESP) and CCE entities.
Capacity Factor: the ratio of an electricity generating resource’s actual output over a period of
time to its potential output if it were possible to operate at full nameplate capacity continuously
over the same period. Intermittent renewable resources, like wind and solar, typically have lower
capacity factors than traditional fossil fuel plants because the wind and sun do not blow or shine
consistently.
Category 1: renewable energy and Renewable Energy Certificates (REC’s) from an RPS eligible
facility that is directly interconnected to the distribution or transmission grid within California
Category 2: renewable energy and REC’s from an RPS eligible facility but cannot be delivered to
a California balancing authority without substituting electricity from another source.
Category 3: procurement of unbundled RECs only or not meeting the conditions of Cat egory 1
and 2.
Category 2 Override: the pro forma model will exchange Category 2 renewables for Category 1
renewables.
Climate Zone: A geographic area with distinct climate patterns necessitating varied energy
demands for heating and cooling.
Coincident Peak: Demand for electricity among a group of customers that coincides with peak
total demand on the system.
Community Choice Aggregation: Method available through California law to allow Cities and
Counties to aggregate their citizens and become their electric generation provider.
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Community Choice Energy: A City, County or Joint Powers Agency procuring wholesale power to
supply to retail customers.
Congestion Revenue Rights (CRRs): Financial rights that are allocated to Load Serving Entities to
offset differences between the prices where their generation is located and the price that they
pay to serve their load. These rights may also be bought and sold through an auction process.
CRRs are part of the CAISO market design.
Consumption: The use of energy or the amount of energy consumed by an individual or
organization.
Demand Response (DR): Electric customers who have a contract to modify their electricity usage
in response to requests from a utility or other electric entity. Typically, will be used to lowe r
demand during peak energy periods, but may be used to raise demand during periods of excess
supply.
Direct Access: Large power consumers which have opted to procure their wholesale supply
independently of the IOUs through an Electricity Service Provider.
DWR Bond Charge: an imposed bond charge to recover Department of Water Resources (DWR)
bond costs from bundled customers.
EEI (Edison Electric Institute) Agreement: A commonly used enabling agreement for transacting
in wholesale power markets.
Electric Service Providers (ESP): An alternative to traditional utilities. They provide electric
services to retail customers in electricity markets that have opened their retail electricity markets
to competition. In California the Direct Access program allows large electricity customers to
optout of utility-supplied power in favor of ESP-provided power. However, there is a cap on the
amount of Direct Access load permitted in the state.
Electric Tariffs: The rates and terms applied to customers by electric utilities. Typically have
different tariffs for different classes of customers and possibly for different supply mixes.
Enterprise Model: When a City or County establish a CCE by themselves as an enterprise within
the municipal government.
Federal Tax Incentives: There are two Federal tax incentive programs. The Investment Tax Credit
(ITC) provides payments to solar generators. The Production Tax Credit (PTC) provides payments
to wind generators.
Feed-in Tariff: A tariff that specifies what generators, who are connected to the distribution
system, are paid.
Forward Prices: Prices for contracts that specify a future delivery date for a commodity or other
security. There are active, liquid forward markets for electricity to be delivered at a number of
Western electricity trading hubs, including NP15 which corresponds closely to the price location
which the City of Davis will pay to supply its load.
Implied Heat Rate: A calculation of the day-ahead electric price divided by the day-ahead natural
gas price. Implied heat rate is also known as the ‘break-even natural gas market heat rate,
because only a natural gas generator with an operating heat rate (measure of unit efficiency)
below the implied heat rate value can make money by burning natural gas to generate power.
Natural gas plants with a higher operating heat rate cannot make money at the prevailing
electricity and natural gas prices.
Integrated Resource Plan: A utility's plan for future generation supply needs.
Investor-Owned Utility: For profit regulated utilities. Within California there are three IOUs -
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26 October 20, 2017
Pacific Gas and Electric, Southern California Edison and San Diego Gas and Electric.
ISDA (International Swaps and Derivatives Association): Popular form of bilateral contract to
facilitate wholesale electricity trading.
Joint Powers Agency (JPA): A legal entity comprising two or more public entities. The JPA
provides a separation of financial and legal responsib ility from its member entities.
Load Data: Detailed information related to energy consumption by an individual, organization,
or community.
Load Forecast: A forecast of expected load over some future time horizon. Short-term load
forecasts are used to determine what supply sources are needed. Longer-term load forecasts are
used for budgeting and long-term resource planning.
Marginal Unit: An additional unit of power generation to what is currently being produced. At
and electric power plant, the cost to produce a marginal unit is used to determine the cost of
increasing power generation at that source.
MRTU: CAISO's Market Redesign and Technology Upgrade. The redesigned, nodal (as opposed to
zonal) market that went live in April of 2009.
Net Energy Metering: The program and rates that pertain to electricity customers who also
generate electricity, typically from rooftop solar panels.
Non-Coincident Peak: Energy demand by a customer during periods that do not coincide with
maximum total system load.
Non-Renewable Power: Electricity generated from non-renewable sources or that does not
come with a Renewable Energy Credit (REC).
NP15: Refers to a wholesale electricity pricing hub - North of Path 15 - which roughly corresponds
to PG&E's service territory. Forward and Day-Ahead power contracts for Northern California
typically provide for delivery at NP15. It is not a single location, but an aggregate based on the
locations of all the generators in the region.
Off Peak: time when demand for electricity is low between the hours of 11:00 pm to 6:59 am
during the week days and 24 hours during the weekends.
On-Bill Repayment (OBR): Allows electric customers to pay for financed improvements such as
energy efficiency measures through monthly payments on their electricity bills.
On-Peak: time when demand for electricity is high between the hours 7:00 am and 10:59 pm
during the weekdays.
Operate on the Margin: Operation of a business or resource at the limit of where it is profitable.
Opt-Out: Community Choice Aggregation is, by law, an opt-out program. Customers within the
borders of a CCE are automatically enrolled within the CCE unless they proactively opt-out of the
program.
Power Charge Indifference Adjustment (PCIA): A charge applied to customers who leave IOU
service to become Direct Access or CCE customers. The charge is meant to compensate the IOU
for costs that it has previously incurred to serve those customers.
PPA (Power Purchase Agreement): The standard term for bilateral supply contracts in the
electricity industry.
Rate Stabilization Fund: an amount allocated into a reserve fund to be utilized to offset higher
potential higher rates during rate setting.
Renewable Energy Credits (RECs): The renewable attributes from RPS-qualified resources which
must be registered and retired to comply with RPS standards.
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27 October 20, 2017
Resource Adequacy (RA): The requirement that a Load-Serving Entity own or procure sufficient
generating capacity to meet its peak load plus a contingency amount (15 percent in California)
for each month.
RPS (Renewable Portfolio Standards): The state-based requirement to procure a certain
percentage of load from RPS-certified renewable resources.
Scheduling Coordinator: An entity that is approved to interact directly with CAISO to schedule
load and generation. All CAISO participants must be or have an SC.
Scheduling Agent: A person or service that forecasts and monitors short term system load
requirements and meets these demands by scheduling power resource to meet that demand.
Spark Spread: The theoretical grow margin of a gas-fired power plant from selling a unit of
electricity, having bought the fuel required to produce this unit of electricity. All other costs
(capital, operation and maintenance, etc.) must be covered from the spark spread.
Supply Stack: Refers to the generators within a region, stacked up according to their marginal
cost to supply energy. Renewables are on the bottom of the stack and peaking gas generators on
the top. Used to provide insights into how the price of electricity is likely to change as the load
changes.
Total CAISO Load: the total electricity need to procure from the CAISO taking in consideration
for line losses. Line losses is wasted electric energy due to inherent inefficiencies or defects in
the distribution or transmission system.
Total Retail Load: the total electricity consumed by consumers (residential and commercial) in a
given period.
Uncollected Factor: a model parameter allocating a percentage of revenue as uncollectable,
otherwise considered bad debt.
Weather-Adjusted: Normalizing energy use data based on differences in the weather during the
time of use. For instance, energy use is expected to be higher on extremely hot days when air
conditioning is in higher demand than on days with comfortable temperature. Weather
adjustment normalizes for this variation.
Wholesale Power: Large amounts of electricity that are bought and sold by utilities and other
electric companies in bulk at specific trading hubs. Quantities are measured in MWs, and a
standard wholesale contract is for 25 MW for a month during heavy-load or peak hours (7am to
10 pm, Mon-Sat), or light-load or off-peak hours (all the other hours).
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RESOLUTION NO. 10609 (2015 Series)
A RESOLUTION OF THE CITY COUNCIL OF THE CITY OF SAN LUIS
OBISPO, CALIFORNIA, CONFIRMING CITY OF SAN LUIS OBISPO
PARTICIPATION IN THE EXPLORATION OF COMMUNITY CHOICE
AGGREGATION (CCA)
WHEREAS, the San Luis Obispo City Council is committed to supporting actions that
promote local economic benefit and job creation; and
WHEREAS, the San Luis Obispo City Council is committed to promoting choice and
competition for the benefit of its residents and businesses; and
WHEREAS, the San Luis Obispo City Council is committed to increasing energy
efficiency, and to supporting more broad availability and use of local renewable power sources;
and
WHEREAS, Community Choice Aggregation (CCA) is a program through which an
energy district, represented by participating local governments within its jurisdiction, purchases
electrical power on behalf of its residential and commercial customers; and
WHEREAS, the electric distribution utility is an important partner, responsible for
reliable delivery of power and enhancement and maintenance of grid infrastructure; and
WHEREAS, Community Choice Aggregation, if determined to be technically and
financially feasible, could provide substantial economic and environmental benefits to all
residents and businesses in the City of San Luis Obispo; and
WHEREAS, Community Choice Aggregation provides the opportunity to fund and
implement a wide variety of energy related programs of interest to the community; and
WHEREAS, it is intended for the CCA Exploration Advisory Committee (CEAC), to be
an advisory group comprised of local agency staff, local elected officials or their designees, and
members of the public with expertise in energy, finance, law and /or any other pertinent skills;
with the charge to develop CCA feasibility information and to advise the San Luis Obispo City
Council and participating local agencies; and
WHEREAS, the City of San Luis Obispo's adopted Climate Action Plan states that the
City shall evaluate the feasibility of a regional Community Choice Aggregation program to
procure electricity from renewable resources.
NOW, THEREFORE, BE IT RESOLVED by the San Luis Obispo City Council that:
1. The San Luis Obispo City Council agrees to participate in an inter -
jurisdictional investigation into the feasibility of Community Choice
Aggregation (CCA), through a CCA Exploration Advisory Committee
R 10609
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Resolution No. 10609 (2015 Series)
Page 2
CEAC), supported by SLO Clean Energy, California Clean Power, or
similar entity, to guide preparation of feasibility information without
obligation of the expenditure of General Funds unless separately
authorized in a future action by the San Luis Obispo City Council.
2. The San Luis Obispo City Council will appoint at least one designee and
an alternate to participate as a member of the CEAC.
City staff is authorized to execute the appropriate documents to allow the
city, CEAC, SLO Clean Energy, California Clean Power, or similar entity,
and its technical consultants to acquire energy usage load data from the
electric distribution utility so it may be analyzed as part of the exploration
process.
4. Adoption of this resolution in no way binds or otherwise obligates the San
Luis Obispo City Council to establish or participate in a Community
Choice Aggregation program.
Upon motion of Council Member Rivoire, seconded by Council Member Christianson, and on the
following roll call vote:
AYES: Council Members Carpenter, Christianson and Rivoire,
Vice Mayor Ashbaugh and Mayor Marx
NOES: None
ABSENT: None
The foregoing resolution was adopted this 31St day of March 2015.
I- 2*
a r Jan M rx
ATTEST:
cony ei, -
City Clerk
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Resolution No. 10609 (2015 Series)
Page 3
APPROVED AS TO FORM:
IN WITNESS WHEREOF, I have hereunto set my hand and affixed the official seal of the City
of San Luis Obispo, California, this s day of i
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CityofSanLuisObispo, CouncilAgendaReport, MeetingDate, ItemNumber
FROM: Michael Codron, Assistant City Manager
SUBJECT: RESOLUTION SUPPORTING CITY PARTICIPATION IN THE
EXPLORATION OF COMMUNITY CHOICE AGGREGATION ( CCA),
TOGETHER WITH OTHER JURISDICTIONS IN THE REGION.
RECOMMENDATION
Adopt a resolution in support of an inter-jurisdictional investigation into the feasibility of CCA
and to communicate this support to the County Board of Supervisors and the other cities in the
County. There is no obligation to expend City funds or commitment to establish or participate in
a potential future CCA program.
DISCUSSION
Background
In December 2013 City staff presented the City Council with a detailed report to educate the
Council and community about CCA, and identify options available to the City to participate in an
exploration of the feasibility of such a program in the region (Attachment 1, 12-3-13 Council
Agenda Report).1 At this meeting, the Council stopped short of officially endorsing CCA
exploration (because no resolution of support was adopted), but a majority of the Council
expressed sufficient interest that two exploratory steps were taken, as follows:
1. Council Member Christianson was appointed to be the City’s representative on a CCA
Exploration Advisory Committee supported by SLO Clean Energy. Council Member
Ashbaugh was selected to be the alternate; and
2. The City Manager was authorized to allow the release of City power usage data to
facilitate the exploration of feasibility.
Council Member Christianson was able to attend all of the meetings that occurred in 2014 and
has now been replaced on the Committee by Council Member Rivoire.
Current Request
Following the 2014 meetings it has become clear that the next official step is for a lead agency to
step forward and formally organize and fund a feasibility study. For this to happen, it would be
helpful for interested jurisdictions to step forward and declare their support. The Cityof San Luis
Obispo can express its support by passing a resolution similar to the one passed in 2014 by the
City of Morro Bay. The proposed resolution has no funding or other resources attached to it, but
is a clear indication of the City’s formal desire to participate in the exploration process if it
moves forward (Attachment 2).
1 Community Choice Aggregation (CCA) essentially leverages the aggregate buying power of individual customers
in a city or county to secure a different mix of energy sources than the standard investor-owned utility (PG&E).
CCA is often used to secure contracts with energy providers that use alternative power sources such as solar or
wind.
3/31/15
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Community Choice Aggregation Resolution Page 2
The proposed action is consistent with the Climate Action Plan (CAP) adopted in August 2012.
A specific implementation item in the CAP calls for the City to: “Evaluate the feasibility of a
regional Community Choice Aggregation program to procure electricity from renewable
resources.”2 The proposed action is one of many steps that the City can take to advance this
action item. Furthermore, the City is a member of the Air Pollution Control District’s
Greenhouse Gas Stakeholder Group, which supports a regional CCA feasibility study.
Should the Council adopt the resolution and direct a letter to be sent to the County and other
cities in the County, staff from Administration will craft that correspondence for the Mayor’s
signature.
Supporting Documentation and Resources
In addition to the information included in Attachment 1, SLO Clean Energy has provided the
following links for those that wish to research the issue more deeply:
1. Introduction to CCA by Geof Syphers, CEO of Sonoma Clean
Power https://www.youtube.com/watch?v=-pQLETdzcy4 (15 Minutes)
2. Recommendations on starting your own CCA from Geof
Syphers https://www.youtube.com/watch?v=queqJZUODB8 (22 Minutes)
3. Videos submitted by community choice leaders at a Business for Clean Energy
Conference in Silicon Valley http://biz4cleanenergy.com/new-energy-choices-silicon-
valley/
CONCURRENCES
The Utilities Department concurs with information included in this report.
FISCAL IMPACT
There is no fiscal impact associated with passing a resolution expressing interest in exploring a
CCA. It is likely that a funding request would be made to the City in the future, should another
jurisdiction take the lead role in the feasibility analysis, however the City makes no
commitments with respect to funding by passing the proposed resolution.
ALTERNATIVES
1. Do not pass a resolution in support of CCA. This alternative is not recommended because
the next steps in learning more about CCA require jurisdictions like the City of San Luis
Obispo to formally express their interest so that a lead agency might step forward to facilitate
the exploration process and feasibility study.
2. Continue consideration to a future meeting. The Council can continue consideration of the
draft resolution if more information is needed. In this case, direction should be provided to
staff to conduct additional research and return to the City Council at a future date.
2 City of San Luis Obispo. Climate Action Plan: Pg.: A-4. 2012
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ATTACHMENTS
1. 12-3-13 Council Agenda Report with background information about CCA
2. Draft resolution expressing the City’s support for participation in an exploration of the
feasibility of CCA
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ATTACHMENT 1
FROM: Carrie Mattingly, Utilities Director
Prepared By: Ron Munds, Conservation Manager
SUBJECT: COMMUNITY CHOICE AGGREGATION PROGRAMS (RELATED TO
ENERGY GENERATION CHOICES)
RECOMMENDATION
Receive information regarding Community Choice Aggregation Programs.
DISCUSSION
Background
In response to Council direction, the following report gives an overview of Community Choice
Aggregation (CCA). In 2002 the California Legislature passed Assembly Bill 117, which permitted
the creation of CCA programs. Under the legislation, a city, county, or Joint Powers Authority, may
implement a CCA program. A CCA entity is allowed to set rates for its customers and choose the
form of energy generation, enabling communities to choose renewable energy sources rather than
the local utility’s mix of energy sources. CCA essentially leverages the aggregate buying power of
individual customers in a city or county.
Once formed, individual customers within aCCA service area can opt out of the CCA and continue
to receive power from the local (usually investor -owned) utility. Although a CCA contracts for its
own energy supply mixes, the local utility continues to own the electricity distribution infrastructure
and provide electricity transmission, distribution, billing, and related customer services. This means
customers of a CCA continue to pay the same charges for the power transmission and distribution
charges as customers that remain with the utility. The CCA entity must pay the local utility for
services provided to the CCA (such asmeter reading and billing).
In order to form a CCA, the law requires jurisdictions to submit an implementation plan to the
California Public Utilities Commission (CPUC) that provides information on the proposed CCA’s
organizational structure, rate setting procedures, and a description of the financial and technical
capabilities of any third parties that will supply power to the CCA. AB 117 further stipulates that
the CPUC shall ensure that no costs are shifted to the remaining customers of the incumbent utility
as a result of the CCA customers’ departure from the electricity load served by the utility. The
CPUC has instituted a Cost Responsibility Surcharge that CCAs must pay to incumbent utilities
until shifted or “stranded” costs are paid off. The Cost Responsibility Surcharge potentially can
affect the cost-competitiveness of CCAs because a high Cost Responsibility Surcharge must be
recovered in the CCA’s rates. There is only one operating CCA in California, Marin Energy
Authority; the rates in their service area are currently competitive with PG&E’s rates with some
customers paying slightly less and others paying slightly more than PG&E customers.
Meeting Date
Item NumberDec. 3, 2013
SS1
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Community Choice Aggregation Page 2
Things to Consider – Potential Advantages of a CCA Program
There are a number of potential benefits to having a public CCA entity provide electrical power
rather than an investor owned utility:
1. Increased Renewable Energy Use: Because a CCA entity can select the type of power it
provides to its customers, it can focus on carbon-free renewable power sources, and reduce
its reliance on generation using fossil fuels such as gas or coal.
2. Local Economic Benefits: If the CCA entity were to focus on local renewable generation
sources, the revenues for electrical service paid by residents in a region would remain in the
area of benefit rather than be paid to the incumbent utility’s investors, thus potentially
creating local jobs and improving the local economy.
3. Local Control: The governing board of the CCA entity would be comprised of local elected
officials, so that residents could more easily influence decisions about the operation and
priorities of the CCA entity.
4. Lower Financing costs: Because public entities are able to finance electrical generation
facilities with tax-exempt bonds and do not have to pay dividends to shareholders, a public
CCA program may, in the long run, be able to provide electrical power at a lower cost than
an investor-owned utility.
5. Increased Customer Choice: A public CCA increases consumer choice, by giving
customers an option of receiving power from the CCA entity or remaining with the
incumbent utility.
6. Influence Conservation Programs: A public CCA could choose to undertake more
aggressive energy conservation programs than the incumbent utility which would provide a
community-wide benefit.
7. Implementation of City Policies: There are General Plan and Climate Action Plan policies
that support use of renewable energy.
8. Provide for Small-Scale Renewables: A CCA can provide a market for small-scale
renewable energy projects such as photovoltaics.
Things to Consider – Potential Issues and Risks of a CCA Program
The risks associated with CCA formation fall into two categories: Pre-formation risks and post-
formation (operational) risks.
Pre-formation Issues - Creating a CCA program will require a number of political, engineering,
legal, and financial steps, including the development of a detailed implementation plan that must be
submitted to and certified by the CPUC. The development work and the preparation of the
implementation plan will require the hiring of expert consultants to perform necessary analysis
including a feasibility study.
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The city received correspondence from the SLO Clean Energy coalition which indicated an
opportunity to share costs for a regional CCA feasibility study between San Luis Obispo, Santa
Cruz, Monterey, and San Benito Counties (Attachment, SLO Clean Energy Letter). The costs of the
study and cost allocation are not detailed in the submitted letter although it states a CCA feasibility
study can be over $200,000 for a single county.
Other California counties have completed CCA feasibility studies, including Sonoma County which
estimated the total start-up cost for a CCA in their county to be $1.7 million. Sonoma County’s
study also indicates that $500,000 to $750,000 of the total cost may not be recoverable from CCA
rates once in operation. The non-recoverable costs would include the feasibility study and the
drafting and execution of the necessary formation related agreements ( such as a Joint Powers
Agreement).
Once the decision has been made to initiate a CCA program, the entity will then need to begin
taking steps to commence operations. Depending on how the CCA elects to structure its program,
additional funds will be needed to finance start-up costs which would include but not be limited to
the following:
1. Recruit and hire staff
2. Develop information and outreach materials
3. Establish a customer call center for inquiries
4. Prepare short and long term load forecasts
5. Develop capability or negotiate contracts for operational services ( such as electronic data
interchange with utility, customer bill calculations, schedule coordinator services, etc.)
6. Execute contracts for electric supply; identify generation projects and negotiate participation
7. Obtain financing for program capital requirements
8. Send customer notices and explain opt-out option
9. Submit notification of certification to the CPUC
Post-formation Risks - The predominant cost of service variables and risks that might impact the
CCA’s operational costs are:
1. The Cost Responsibility Surcharge (CRS) will vary year-to-year: The CRS is inversely
related to the prevailing market price of electricity such that if market prices fall, the CRS
will increase. To the extent the CRS increases and CCA program has locked in electricity
prices through long-term contracts, the CCA customers’ total rates will increase.
2. Procurement Risks: This broad category of risks relates to the ability of a CCA to procure
power at reasonable costs, to avoid significant under- or over-procurement, avoid a
supplier’s ability to default on a supply contract at times when energy spot markets are high
forcing the CCA to purchase expensive power, and the future success of the CCA at
renewing power supply agreements.
3. Regulatory Risks: These risks consist of uncertainty in regulatory decisions by the
California Public Utilities Commission that could adversely affect the costs that customers
have to pay to take service from a CCA, such as exit fees paid by customers and bonding
requirements for the CCA.
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4. Policy Risks: While all CCA members have a voice on a governing Board, no single city
can control policy. Thus, due to the differing demographic, economic, and business
composition relative to a regional body, the City might find that the interests of its citizens
and businesses are not well served by decisions of the governing Board.
5. Customer Cost Risks: These risks consist of the uncertainty in exit fees, whether the CCA
can continue to “meet or beat” PG&E’s costs of service, how a CCA will handle adding
different types of customers in the future, and the uncertainty in costs that are passed
through directly from the CCA’s power supplier to customers. This also includes the risk
that the CCA may not be willing, or able, to provide low-income customers rates that will be
no higher than PG&E’s.
Community Choice Aggregation Programs in California
CCA Programs have been authorized in California since 2003. The only CCA program currently
operating in California was created in Marin County and began serving customers in May 2010.
However, there are multiple other cities or counties exploring the feasibility and program
requirements of establishing a CCA. The following is a summary and status of programs in
California:
Entity Status Milestones Additional Information
Marin Energy
Authority
Operating Only operational CCA
in California
marinenergyauthority.com
Sonoma Clean Power Initiating Projected to begin
service in January
2014
www.scwa.ca.gov/cca/
Clean Power SF Initiating Working to finalize
implementation plan
cleanpowersf.org
Monterey/Santa Cruz/
San Bonito Counties
Investigating Counties and
interested cities pass
resolution of
participation in May
2013
montereybaycca.org
Yolo County/City of
Davis
Investigating Early stages of
investigation
City-
council.cityofdavis.org
San Diego County Very Early Stages of
Investigation
Exploring funding
sources and other
organizational issues
sandiegoenergydistrict.org
This is not an all-inclusive list; there may be other cities and/or counties investigating the formation
of a CCA.
Next Steps
Should Council be interested in further exploring the formation of a CCA or expressing its support
for such a venture, more fully understanding the exact cost of participating in a feasibility study and
funding sources for such a study will be important. Some other items for consideration would be
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any electricity data access restrictions, collective community support for CCA formation, the
current energy mix of PG&E, and a broader study of the successes/challenges experienced by other
cities and/or counties who are doing this or attempted such an action. Exploration of the formation
of a CCA is not currently on the work program of any city department. Undertaking such
exploration would require a very significant commitment of interdepartmental staff resources and
financial resources, not currently contemplated or budgeted. Thus, if the Council is interested in
further studying the formation of a CCA, staff would recommend that Council consider options and
priorities in the context of the City’s existing budget processes, whereby current Major city goal and
work program impacts, workload re-prioritizations, and/or additional staff and financial resource
needs can be evaluated in a comprehensive way.
CONCURRENCES
The Community Development Department concurs with the information provided in this report.
FISCAL IMPACT
The material provided in this report has been presented for information purposes therefore there is
no fiscal impact associated with this report.
ATTACHMENT
1. SLO Clean Energy Letter
CCA (MattinglyMunds)
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BOARD OF SUPERVISORS
AGENDA LETTER
Clerk of the Board of Supervisors
105 E. Anapamu Street, Suite 407
Santa Barbara, CA 93101
(805) 568-2240
Agenda Number:
Department Name: Community Services
Department
Department No.: 057
For Agenda Of: October 3, 2017
Placement: Departmental
Estimated Time: 2 hours 30 minutes
Continued Item: No
If Yes, date from: N/A
Vote Required: Majority
TO: Board of Supervisors
FROM: Department
Director(s)
George Chapjian, Community Services Director
(805) 568-2467
Contact Info: Jen Cregar, Project Supervisor, Energy & Sustainability Initiatives
(805) 568-3506
SUBJECT: Community Choice Energy Feasibility Study Results
County Counsel Concurrence Auditor-Controller Concurrence
As to form: Yes As to form: Yes
Other Concurrence: Risk Management
As to form: Yes
Recommended Actions:
That the Board of Supervisors:
A. Receive and file a Technical Feasibility Study on Community Choice Aggregation for the
Central Coast Region (Attachment A; report and study appendices also may be downloaded at
http://www.centralcoastpower.org/resources.nrg);
B. Receive and file a Comparison Matrix of Community Choice Energy Programs (Attachment C);
C. Provide staff with direction regarding community choice energy options as follows:
1. Option 1. Join two existing CCE programs;
2. Option 2. Form a new CCE program;
3. Option 3. Not implement a CCE program at this time and continue to explore additional
CCE-related options for later consideration; or
4. Option 4. Not implement a CCE program at this time and discontinue the County’s
evaluation of CCE.; and
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Community Choice Energy Feasibility Study Results October 3, 2017
D. Determine that the above recommended actions do not constitute a project subject to
environmental review under the California Environmental Quality Act (CEQA) pursuant to
CEQA Guidelines Section 15262, as the actions involve only feasibility or planning studies for
possible future actions which the Board has not approved, adopted, or funded and does not have
a legally binding effect on later activities, and direct staff to file a Notice of Exemption (NOE)
(Attachment B); or
E. Provide other direction to staff.
Summary Text:
Staff, in collaboration with ten other jurisdictions across the Tri-County Region, has been evaluating the
feasibility of a regional community choice energy (CCE) program for Santa Barbara, San Luis Obispo,
and Ventura Counties. The County of Santa Barbara (“County”) commissioned a feasibility study
(Attachment A) in 2016 to determine whether CCE is a good fit for Santa Barbara County and the Tri-
County Region. The feasibility study and subsequent peer review suggest that a newly created regional
CCE program spanning Santa Barbara, San Luis Obispo, and Ventura Counties is likely not a viable
venture in terms of the CCE program’s ability to provide competitive rates and remain a solvent
organization. The feasibility study similarly found that a stand-alone CCE program for the
unincorporated area of Santa Barbara County also would not produce competitive rates or a long-term
financially viable organization.
The results of the peer review, however, indicate that it may be possible for a local or regional CCE
program operating within Pacific Gas and Electric Company (PG&E) territory, including northern Santa
Barbara County, to offer competitive rates while covering its costs. However, a jurisdiction that offers
CCE service to one residential customer must offer CCE service to all residential customers. This means
that the County cannot operate a CCE program solely within PG&E territory in the northern
unincorporated area of Santa Barbara County. The County must also offer CCE service in the southern
unincorporated area of Santa Barbara County, which is served by Southern California Edison (SCE),
which has lower electricity generation rates than PG&E. The feasibility study and peer review indicate
that a new regional CCE program, under the assumptions used in the feasibility study and peer review, is
not likely to be able to offer competitive rates in SCE territory.
Staff is requesting that the Board consider the following options and provide direction on how to
proceed with CCE:
Option 1. Join two existing CCE programs;
Option 2. Form a new CCE program;
Option 3. Not implement a CCE program at this time and continue to explore additional CCE-
related options for later consideration; or
Option 4. Not implement a CCE program at this time and discontinue the County’s evaluation of
CCE.
No additional funding or changes in staffing levels are requested at this time.
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Background:
About Community Choice Energy
CCE, also known as community choice aggregation (CCA), enables local governments to leverage the
purchasing power of their residents, businesses, and governments to purchase or generate power for their
communities. When a CCE program is formed, the CCE provider purchases the electricity—which
typically includes a higher percentage of electricity from renewable resources like wind and solar—and
sets the rates charged to customers. The existing investor-owned utility (IOU)—in our region, PG&E
and SCE—continues to deliver the electricity purchased by the CCE provider over the IOU’s power
lines and provide metering, billing, and other customer service.
Currently, there are nine CCE programs in operation throughout California: five in the San Francisco
Bay Area, one in Humboldt County, and three in the Los Angeles area. The longest-standing CCE
program is MCE Clean Energy, which began operations in Marin County in 2010 and has since grown
to also include parts of Napa, Solano, and Contra Costa Counties. More than 20 jurisdictions are actively
studying or developing CCE programs, with several programs expected to launch in 2018. Attachment C
includes a matrix that compares a potential Central Coast Power regional CCE program with the nine
operational CCE programs and three in-development CCE programs that would share some similarities
to a regional Central Coast Power CCE program. All of the operational and in-development CCE
programs conducted feasibility studies that suggested CCE could be economically viable for their
communities.
Board Action Related to CCE
On May 5, 2015, the Board provided direction to staff to solicit participation from area local
governments in a regional CCE feasibility study and to prepare information on the costs of CCE
exploration. On June 9, 2015, the Board appropriated funds to the Community Services Department to
conduct the initial phase of evaluating the formation of a CCE program (“Phase 1”). Per Board direction,
staff contacted all 27 eligible jurisdictions1 throughout the Tri-County Region in late 2015 to invite them
to participate in a regional CCE feasibility study. Ten jurisdictions, plus the Community Environmental
Council, joined the County to fund the study, the results of which are presented herein. Staff formed an
Advisory Working Group, composed of the contributing counties and cities,2 to help guide and oversee
the feasibility analysis, provide outreach support, and monitor policy and program developments related
to CCE.
The County, with input from the Advisory Working Group, commissioned Willdan Financial Services
(“Willdan”) to complete the CCE feasibility study. The contract with Willdan was approved by the
Board on May 10, 2016, and subsequently extended to allow for the completion of the study presented
herein. The Advisory Working Group selected Willdan to conduct the study, in part, due to its
commitment to providing an impartial assessment and willingness to forego future CCE work in the
region so as to not bias the outcome of the study. Willdan has also completed similar feasibility studies
for the Cities of Lancaster and San Diego. MRW and Associates (“MRW”), who was later hired to
conduct a peer review of Willdan’s feasibility study, also has agreed to the same commitment to
1 Lompoc operates its own municipally owned electric utility and therefore is not eligible to participate in a CCE program.
All other cities and counties in the Tri-County Region are included in the study.
2 For a list of Advisory Working Group members, visit http://centralcoastpower.org/about.nrg#leadership.
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impartiality and has performed similar CCE technical evaluations for other local governments, including
Alameda County and the City of San Diego.
Our regional CCE exploration effort is sometimes referred to as “Central Coast Power.” Staff, with input
from the Advisory Working Group, created a website (www.CentralCoastPower.org) to share
information about our local CCE progress.
Feasibility Study Scope
The feasibility study evaluates the feasibility of forming a new CCE program run by one or multiple
local governments in the Tri-County Region. The study did not consider the viability of one or more
jurisdictions joining an existing CCE program.
The study assessed financial feasibility in terms of the ability of a local/regional CCE program to
provide competitive electricity rates while meeting policy goals and covering substantial CCE program
formation costs and ongoing operating expenses over an eleven-year study period (2020-2030).
The Advisory Working Group selected eight participation scenarios to explore the feasibility of different
sizes and configurations for the CCE program and the potential effects of customer demographics. The
eight participation scenarios included in the study are:
1. All Tri-County Region, including all 27 eligible jurisdictions throughout San Luis Obispo, Santa
Barbara, and Ventura Counties
2. Advisory Working Group Jurisdictions, including the 11 jurisdictions that funded the feasibility
study
3. All San Luis Obispo County, including the unincorporated area of the county and its cities
4. Unincorporated San Luis Obispo County
5. All Santa Barbara County, including the unincorporated area of the county and its cities
6. Unincorporated Santa Barbara County
7. All Ventura County, including the unincorporated area of the county and its cities
8. City of Santa Barbara
In addition to the eight participation scenarios, three renewable energy content scenarios were
considered for each participation scenario:
1. Renewable Portfolio Standard (RPS) Equivalent: This scenario assumes that the CCE program
would offer its base electricity product to all customers starting at 33% renewable energy content
in 2020 and ramping up to 50% renewable energy content by 2030 in alignment with the
California RPS.3
2. Middle of the Road: This scenario assumes that the CCE program would offer its base electricity
product to all customers using 50% renewable energy content for the entire study period.
3. Aggressive: This scenario assumes that the CCE program would offer its base electricity product
to all customers using 75% renewable energy content for the entire study period.
3 http://www.cpuc.ca.gov/RPS_Homepage/
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For each of the renewable energy content scenarios, 2% of customers were assumed to voluntarily opt
up to a premium 100% renewable energy product. In total, 24 different scenarios were considered (8
participation x 3 renewable energy content scenarios). Twelve of the 24 scenarios include the
unincorporated area of Santa Barbara County. The results for the Advisory Working Group participation
scenario under all three renewable energy content scenarios are presented in the body of the feasibility
study report and in greater detail in Appendix D of the feasibility study report. Results for the remaining
scenarios are included in Appendices C and E-J. Appendix E includes the results for the Unincorporated
Santa Barbara County Scenario. The report and appendices are available at:
http://www.centralcoastpower.org/resources.nrg.
Feasibility Study Peer Review
Evaluating the feasibility of CCE is a difficult, complex, and time-consuming exercise involving
numerous variables and assumptions that are predicated on long-term forecasts of conditions and costs
within a dynamic energy procurement and regulatory landscape. While the existence of nine CCE
programs throughout California provides some verification of proof of concept, the procurement and
management of energy by local governments remains a complicated and multi-faceted venture.
Two IOUs currently serve Santa Barbara County: PG&E in North County and SCE in South County.
While this split IOU situation does not apply to other local governments in the region, each of the eight
participation scenarios that include the unincorporated area of Santa Barbara County is affected by the
presence of both IOUs. There are no other operational CCE programs that span multiple utility service
areas, and there is no way to offer a CCE program for the unincorporated area of Santa Barbara County
without operating in both IOU territories. PG&E and SCE have differing rate structures and actual
customer rates, which present some unique challenges to the CCE program that would need to be
considered when setting electricity rates.
In addition, a potential regional CCE program would be substantially larger in terms of customers
served, the amount of electricity provided, and geographic reach than any of the existing CCE programs
when they launched. While some of the existing CCE programs have grown over time, the absence of a
similar sized start-up CCE model proved to be challenging when conducting a feasibility assessment for
our region.
Willdan completed its preliminary draft feasibility study in May 2017. Given the complexities described
above, staff, with input from the Advisory Working Group, took the additional prudent steps of (1)
contacting existing CCE program staff to gather additional data related to the costs of operating a CCE
program and (2) commissioning MRW to conduct a third-party review of the Willdan draft study.
The purpose of the peer review was to evaluate the assumptions and conclusions of the Willdan draft
study. MRW suggested several revisions to the Willdan draft study and the pro forma upon which the
financial assessment was built to, in the opinion of MRW, improve the reasonableness and efficacy of
the assumptions that underpinned the Willdan draft feasibility study. MRW’s findings and
recommendations along with Willdan’s response to the MRW analysis are included in Appendix L of
the feasibility study report.
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Three variables had the largest influence on the Willdan feasibility study and MRW peer review:
1. Cost of Renewable Energy: To forecast renewable energy costs, Willdan relied on the average
prices that PG&E & SCE have paid for renewable energy to comply with the State RPS. Some of
this pricing is based on long-term contracts that the IOUs executed more than a decade ago. By
contrast, MRW relied on renewable energy prices from contracts executed in 2016, which it
believes is more reflective of the marketplace in which the CCE program would procure
renewable energy. MRW’s assumed renewable energy costs were approximately 30 perc ent
lower than those assumed by Willdan and in line with pricing reported by operational CCE
programs. Willdan also did some sensitivity testing of lower renewable energy prices.
2. Escalation of PG&E and SCE Rates: Electricity rates include two primary components: the
charges assessed for the cost of (1) the electricity provided to the customer (“generation charge”)
and (2) the delivery of the electricity over the IOUs’ power lines and related infrastructure
(“delivery charge”). The delivery charge is the same for CCE and non-CCE customers; whereas,
the generation charge can vary between IOUs and CCE providers. Therefore, the rate
competitiveness of a CCE program is dependent, in part, on the behavior of future PG&E and
SCE generation rates against which the CCE generation rates must compete.
Willdan and MRW take different approaches in forecasting future IOU generation rates. Willdan
adjusts PG&E’s and SCE’s rates by 0% – 0.5% annually based on current IOU rates that have
already been approved by the California Public Utilities Commission (CPUC) and market prices
for renewable energy. By contrast, MRW, citing pending rate cases before the CPUC and
accounting for factors other than renewable energy prices, forecasts more robust growth rates for
the IOUs’ generation rates over the study period.
3. Financing: Willdan assumed that the CCE program’s start-up costs (e.g., staff, office, and
consultant costs prior to program launch); working capital equal to five months of operating
expenses; and contributions to a rate stabilization and contingency fund would be financed
through a 30-year bond issuance. According to Willdan, the sheer size of a potential CCE
program serving the Tri-County Region precludes the cost-effective use of other, more
traditional financing models (e.g., General Fund or bank loans) commonly used by smaller
existing CCE programs. MRW noted the use of long-term bond financing was unusual and the
amount financed was high relative to other CCE programs. MRW suggested that it is atypical to
include a fully funded rate stabilization/contingency fund in initial financing. MRW also
highlighted the more common practice by other CCE programs to finance three—rather than
five—months of working capital.
Although not as large of a driver of the feasibility outcome as the items cited above, the Power Cost
Indifference Adjustment (PCIA) exit fee charged to CCE customers by the IOUs affects the
competitiveness of the CCE program’s rates relative to the IOUs’ rates.4 The PCIA fluctuates based on
4 The PCIA is designed to keep remaining IOU customers who do not join a CCE program from having to bear the sunk cost
of contracts the IOUs already signed for customers who no longer will receive electricity bought for them by the IOUs. The
PCIA is intended to not penalize (or reward) remaining IOU customers when CCE customers depart. However, it puts CCE
rates at a disadvantage due to the added charge. Both IOUs and the CCE providers are unhappy with the current PCIA model,
which is under review by the CPUC as part of R.17-06-026 to Review, Revise and Consider Alternatives to the Power
Charge Indifference Adjustment.
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current renewable energy market prices and is in part based on confidential pricing paid by the IOUs for
historical power purchases. The market fluctuations and confidential nature of the data make it hard for
CCE programs to predict the impact of the PCIA on CCE rate competitiveness year to year.
Feasibility Study Findings
CCE program feasibility is typically assessed based on (1) the competitiveness of CCE rates against the
existing IOU rates and (2) the long-term financial viability of the enterprise. According to Willdan’s
analysis, none of the 24 scenarios studied—including the County operating its own CCE program in the
unincorporated area of Santa Barbara County—shows a feasible outcome, meaning the CCE rates were
higher than PG&E and/or SCE rates, and the CCE program is predicted to have negative net margins in
most study years (2020-2030). Given the underperformance of the CCE program in terms of being rate
competitive, consistently having negative net margins, and failing to meet the target for working capital,
the CCE program under the assumptions used in Willdan’s analysis is neither reliably solvent nor
financially feasible.
A summary of Willdan’s assessment of how electricity rates, the overall electricity bill, and greenhouse
gas emissions would change for a typical residential customer under the CCE program or existing IOU
for each of the 12 scenarios that include the unincorporated area of Santa Barbara County is shown in
Table 1 below. The rate comparison is for the generation component of the overall electricity rates only;
the delivery rates would stay the same regardless of whether the customer is a CCE or non-CCE
customer. For the Advisory Working Group Middle of the Road (50% Renewable) Scenario, a
typical CCE residential customer in PG&E territory (northern Santa Barbara and San Luis
Obispo Counties) would, on average, experience nearly 30% higher generation rates, resulting in
an extra $16 charge on the customer’s monthly electricity bill. A CCE residential customer in SCE
territory (southern Santa Barbara and Ventura Counties) would, on average, experience 50%
higher generation rates, resulting in an extra $20 on its monthly bill. The rate and bill impact is even
higher (more costly) under the Advisory Working Group Aggressive (75% Renewable) Scenario.
Similarly, the rate and bill delta would be larger for the unincorporated area of Santa Barbara
County for all three renewable energy content scenarios than for the equivalent Advisory
Working Group scenarios. A CCE program serving solely the unincorporated area of Santa Barbara
County would see higher rates because it would have fewer customers over which to spread fixed costs
for common CCE functions such as power procurement and scheduling, legal/regulatory support, and
billing coordination with the IOUs, despite having somewhat lower expenses due to smaller staff size
and lower power costs.
While the CCE Middle of the Road (50% Renewable) and Aggressive (75% Renewable) Scenarios
would lower greenhouse gas emissions relative to PG&E’s and SCE’s electricity portfolios, the RPS
Equivalent Scenario would increase greenhouse gas emissions for all CCE participation scenarios. The
emissions increase is because PG&E and SCE currently have more greenhouse gas-free renewable
energy in their electricity supply portfolios than required by the State RPS, and based on renewable
energy contracts already signed, the IOUs are expected to continue to exceed the RPS requirement until
at least 2020. If the CCE program were to merely meet—rather than exceed—the RPS, the CCE
program would create more greenhouse gas emissions than either IOU in 2020.
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Table 1. Willdan Summary of Forecasted Outcomes for a Typical Residential Customer in 2020
Participation
Scenario
Included
Jurisdictions
Renewable
Energy
Content
Pacific Gas & Electric Southern California Edison
Proportional
GHG
Comparison
Generation
Rate
Comparison
(% Increase/
Decrease for
CCA
Customers)
Bill
Comparison
($ Increase/
Decrease for
CCA
Customers)
Generation
Rate
Comparison
(% Increase/
Decrease for
CCA
Customers)
Bill
Comparison
($ Increase/
Decrease for
CCA
Customers)
All Tri-County
Region
All San Luis
Obispo County
All Santa
Barbara County
All Ventura
County
RPS
Equivalent 22% $11.25 41% $14.55 6%
50% 29% $14.62 51% $17.93 -9%
75% 43% $21.72 71% $25.05 -55%
Advisory
Working Group
Jurisdictions
San Luis Obispo
County
Santa Barbara
County
Carpinteria
Santa Barbara
Ventura County
Camarillo
Moorpark
Ojai
Simi Valley
Thousand Oaks
Ventura
RPS
Equivalent 22% $12.21 41% $16.08 6%
50% 29% $15.92 50% $19.79 -9%
75% 43% $23.68 70% $27.64 -55%
All Santa
Barbara County
Buellton
Carpinteria
Goleta
Guadalupe
Santa Barbara
Santa Maria
Solvang
Unincorporated
Santa Barbara
County
RPS
Equivalent 24% $11.15 45% $14.53 7%
50% 31% $14.27 55% $17.69 -9%
75% 45% $20.78 75% $24.22 -55%
Unincorporated
Santa Barbara
County
Unincorporated
Santa Barbara
County
RPS
Equivalent 26% $15.08 47% $19.29 7%
50% 33% $18.97 56% $23.23 -9%
75% 47% $27.11 76% $31.44 -54%
In its peer review, MRW analyzed the feasibility of a CCE program under the Advisory Working Group
Middle of the Road (50% Renewable) Scenario. MRW’s analysis generally assumed lower CCE
program costs and higher IOU rates against which the CCE program would compete, resulting in MRW
showing a smaller delta between the CCE and IOU rates (as compared to Willdan). For the Advisory
Working Group Middle of the Road (50% Renewable) Scenario, MRW’s analysis shows the CCE
program’s rates being higher than the weighted average of the IOUs’ rates for at least the first five or six
years of the CCE program’s operation, as shown in Figure 2.
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Figure 2. CCE versus Weighted Average IOU Rate Comparison, Advisory Working Group
Middle of the Road (50% Renewable) Scenario
Because of the complications of trying to set CCE rates that can compete in PG&E and SCE territory,
MRW concludes—consistent with Willdan’s findings—that a regional CCE program is not likely to be
able to offer rates that are competitive with SCE for CCE customers located in SCE territory. MRW
suggests, however, that a CCE program may be able to offer competitive rates for CCE customers
located in PG&E territory. To illustrate the potential rate competitiveness in PG&E territory, MRW did
a rate comparison for the unincorporated area of Santa Barbara County.
Figure 3 shows the CCE program’s expected rates (as shown by the stacked bar charts illustrating CCE
costs) compared to the applicable IOU rates (blue line) for the unincorporated area of Santa Barbara
County. After the first year, the CCE rates for the unincorporated area of Santa Barbara County are
projected to be generally comparable to the weighted average of the SCE and PG&E rates. This is
because the unincorporated area of Santa Barbara County has more PG&E than SCE customers; the
PG&E customers consume more electricity than the SCE customers; and PG&E’s generation rates are
higher than SCE’s rates, meaning the CCE rates do not have to be as low to compete with PG&E versus
SCE rates.
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Figure 3. CCE versus Weighted Average IOU Rate Comparison, Unincorporated Santa Barbara
County Middle of the Road (50% Renewable) Scenario
Options for Board Consideration
At best, the feasibility study and peer review results suggest a regional CCE program could offer
customers electricity with a higher renewable energy content (at either 50% or 75%) than either PG&E
(43%) or SCE (41%) are expected to offer in 2020, but at higher rates (29% to 70% higher according to
Willdan). At worst, the CCE program could charge higher rates and dissolve within a matter of a few
years due to an inability to cover costs and maintain adequate working capital. In short, the results of the
feasibility study and peer review do not support the creation of a regional CCE program at this time due
to the:
difficulty of maintaining rates that can be competitive, in particular with SCE’s low generation
rates;
uncertainty of a shifting market and policy landscape, especially in light of the California Public
Utilities Commission (CPUC) open proceeding to consider modifications to the PCIA;5 and
IOUs’ historical trends of shifting generation-related costs to the fixed delivery charge paid by
CCE and non-CCE customers, which makes it harder for CCE programs to compete with
decreasing IOU generation rates.6
Thus, staff recommends the County not pursue a regional CCE program at this time.
MRW’s peer review, however, preliminarily suggests that a CCE program may be able to offer
competitive rates for CCE customers located in PG&E territory, including northern Santa Barbara
5 R.17-06-026, Rulemaking to Review, Revise and Consider Alternatives to the Power Charge Indifference Adjustment
6 Analysis conducted by Willdan shows that SCE’s delivery charge (which is the same for CCE and non -CCE customers) for
residential customers from 2014 to 2017 has increased 89%, while the residential generation charge (against which CCE
programs compete) has decreased 13%. Similar trends hold for non-residential customers. Although comparable data is not
available to do as thorough of an analysis for PG&E, according to Willdan, statewide IOU rate trends suggest PG&E has also
shifted costs from the generation charge, against which CCE programs compete, to the delivery charge paid by all customers.
Lancaster Choice Energy also recently filed a protest with the CPUC because of its concerns about SCE’s generation and
delivery charges and the impact on Lancaster Choice Energy’s customers.
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County. However, the statute that enables local governments to pursue CCE programs requires that a
jurisdiction that offers CCE service to one residential customer must offer CCE service to all residential
customers.7 This means that the County cannot operate a CCE program solely within PG&E territory in
northern Santa Barbara County. The County must also offer CCE service in southern Santa Barbara
County, which is served by SCE.
Staff presents the following options for your Board’s consideration:
Option 1. Join two existing CCE programs. The feasibility study and peer review did not consider the
viability of the County joining an existing CCE program. County staff has spoken with staff at other
operational and in-development CCE programs to gauge their interest in having Santa Barbara County
join their programs. As mentioned previously, all existing CCE programs have experience with either
PG&E or SCE, but not both. PG&E and SCE have different billing systems, rate structures, and
approaches to coordinating with CCE programs. Therefore, it would be difficult for an existing CCE
program operating (or soon to be operating) in a single IOU territory to absorb Santa Barbara County,
spanning two IOUs. Furthermore, the existing CCAs that staff spoke with prefer to add local
governments that are contiguous (or near contiguous) with their boundaries to maintain a cohesive
community feel.
With these constraints in mind, it may be possible for the County to join two CCE programs: potentially
Monterey Bay Community Power (MBCP)8 for the northern unincorporated part of Santa Barbara
County and, for the southern part, one of the in-development LA area CCE programs, such as Los
Angeles Community Choice Energy (LACCE),9 South Bay Clean Power (SBCP),10 or California Choice
Energy Authority (CCEA).11 Three of the programs (MBCP, LACCE, and CCEA) use a joint powers
authority (JPA) structure; SBCP has not yet been created, and it is not clear if the program will launch.
Both MBCP and LACCE plan to launch in early 2018.
California Choice Energy Authority is operating and offers a new service model created by the City of
Lancaster in which CCEA provides back-office functions, such as power procurement, billing
coordination with SCE, and legal/regulatory support, for a fee to smaller stand-alone CCE programs.
Each of the CCEA member CCE programs are responsible for their own rate-setting, marketing and
outreach, program offerings, and financial and risk management. This fee-for-service model is similar to
the “JPA of JPAs” model supported by SBCP. However, staff does not feel CCEA or related “JPA of
JPA” models are a good fit for the County because the County would continue to be exposed to SCE’s
low generation rates and the ongoing uncertainty of the PCIA and other market/regulatory factors.
A significant complication with joining two existing CCE programs is that Public Utilities Code Section
366.2 (b) requires that a local government that offers CCE to its community must serve 100% of
residential customers. While joining two CCE programs could serve all of the County’s residents, there
may be questions about program timing, such as whether both CCE programs would be required to start
serving all Santa Barbara County residents on the same day and how all residential customers would
7 Public Utilities Code Section 366.2 (b). http://codes.findlaw.com/ca/public-utilities-code/puc-sect-366-2.html. This equal
service provision does not apply to non-residential customers.
8 http://montereybaycca.org/
9 http://green.lacounty.gov/wps/portal/green/lacce
10 https://southbaycleanpower.org/
11 https://californiachoiceenergyauthority.com/
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continue to be offered a CCE choice if one or both programs are discontinued. Staff has spoken with
CPUC staff, who have indicated a split-CCE approach like this would require further review with no
guarantees that the CPUC would accept this approach. There is some precedent for how the CPUC may
handle a split-IOU approach under a single CCE program, as Placer County is pursuing a phased launch
across two IOU service areas: PG&E and Liberty Utilities.12 Further study would be needed to
determine whether existing CCE programs would be willing and able to add the County and the
logistical considerations and costs of joining an existing program(s).
Joining other CCE programs would also likely mean joining existing JPAs, the structure and operating
rules of which have already been established. Participating in such a JPA would limit the County’s
control and decision-making authority related to, for example, rates and program design, but could
reduce the County’s costs and risk exposure.
Option 2. Form a new CCE program. Although staff does not recommend it based on the feasibility
study and peer review results, the County could establish a new CCE program. There are two sub-
options for consideration further described below.
Option 2a. Create a CCE program for the unincorporated parts of Santa Barbara County.
If the County were to form a new CCE program serving only the unincorporated areas, the
County would fund the CCE program using an enterprise fund and could house the program
within an existing or new department or division. This would allow the County to retain more
control over program design, costs, and rate-setting than forming a JPA, but it also would mean
the County must fully fund the start-up program and carry all the risk. The County would still
face the hurdle of rate-competitiveness in SCE territory and potentially PG&E territory. If
market and policy dynamics change in the future in support of a regional CCE program, the
County could later pursue a JPA structure to add other interested jurisdictions.
Option 2b. Create a CCE program with one or more jurisdictions. If your Board is interested
in continuing to pursue a regional CCE program and other jurisdictions are also interested, a new
JPA could be formed to administer the regional CCE program.
Option 3. Not implement a CCE program at this time and continue to explore additional CCE-
related options for later consideration. The electricity market and policy environment are rapidly
transforming. While CCE programs have enjoyed tremendous growth over the past couple of years, both
in terms of the number of programs and expansions of existing programs to serve more customers, the
IOUs have had time to adjust to a more competitive market in a way that poses a greater risk to new
CCE program formation. Similarly, the CPUC is grappling with how to manage the growth of CCE and
level the playing field for all types of electricity providers. Significant regulatory and potential
legislative changes are expected in the next couple of years for CCE programs. It may benefit the
County to take a “wait and see” approach to let the market stabilize before further considering CCE.
If your Board chooses not to proceed with CCE at this time, staff is prepared—with ongoing funding to
be determined based on your direction for which option to pursue—to continue to work with the
Advisory Working Group and others to pursue other local renewable energy generation (e.g.,
12 The San Joaquin Valley Power Authority pursued CCE across two IOU territories in the mid-2000s, but ultimately the
CCE program did not launch.
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aggregation of government accounts); green job creation; and greenhouse gas reduction strategies in
support of the County’s economic and sustainability goals, including its commitment to reduce
countywide greenhouse gas emissions to 15% below 2007 levels by 2020, as called for by the County’s
Energy and Climate Action Plan. Staff can also further study different CCE options, such as limiting
CCE service to residential and government customers or the CCE program providing electricity
produced by its own renewable energy generation projects from the start. Staff could also pursue
legislative options for allowing the County to offer a CCE program for a portion of the unincorporated
county, for example, PG&E’s service area where CCE may be more financially feasible.
Option 4. Not implement a CCE program at this time and discontinue the County’s evaluation of
CCE. Your board may direct staff to discontinue implementation or further exploration of CCE.
Table 2 summarizes the potential benefits and risks of each option.
Table 2. Potential Benefits and Risks of CCE Options
Options Benefits Risks
1. Join 2 Existing CCE
Programs
May ameliorate the
negative impact of SCE’s
lower generation rates on
CCE rates for North
County
May be less time-
consuming than creating a
new program
May lower rates due to
lower start-up and
operational costs
May not require as large
of a financial investment
May allow programs and
electricity products to be
better tailored to North
and South County
Carries greater risk of
CPUC rejecting program
May not find willing host
for both parts of the
county
Dilutes local control
May require more
complex logistical
coordination
May create
customer/brand confusion
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Community Choice Energy Feasibility Study Results October 3, 2017
Performance Measure:
N/A
Contract Renewals and Performance Outcomes:
N/A
Fiscal and Facilities Impacts:
Budgeted: Yes
Fiscal Analysis:
The Board has authorized ongoing annual funding of $165,000 towards salaries and benefits expenses
for CCE and related programs in the Energy and Sustainability Initiatives Division of the Community
Services Department. In addition, in FY2015-16, the Board authorized $235,000 towards the costs of the
Phase I CCE exploration, including the feasibility study presented today. Approximately $160,000 of the
$235,000 remains.
2. Form a New CCE Program Increases local control
(especially Option 2a) and
may increase accessibility
of customers to decision-
makers
Simplifies and streamlines
decision-making process
(Option 2a) May be less
time-consuming than
forming a JPA
Increases County’s
financial risk exposure
May increase rates and
provide less financial
stability due to smaller,
less diverse customer base,
reduced purchasing power,
and possibly less
advantageous credit terms
Presents fewer resources
due to smaller size
3. Not implement a CCE
program at this time and
continue to explore additional
CCE-related options for later
consideration
May identify other more
cost-effective options for
achieving similar policy
goals
May avoid significant
market and policy risk and
cost
May miss opportunity to
offer CCE to community
4. Not implement a CCE
program at this time and
discontinue the County’s
evaluation of CCE.
May avoid significant
market and policy risk and
cost
Can reallocate funding to
other policy priorities
May miss opportunity to
offer CCE to community
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Community Choice Energy Feasibility Study Results October 3, 2017
The County also received $327,500 from outside entities to help fund the Phase I costs. Additionally,
over the past two fiscal years, the Board has conditionally appropriated $275,000 and $300,000 for
anticipated Phase 2 and Phase 3 costs, respectively, should your Board direct staff to continue CCE
implementation.
Key_Contract_Risks:
N/A
Staffing Impacts:
No additional staffing requests are being made at this time. However, depending on Board direction,
staff may request additional resources to pursue next steps.
Special Instructions:
Please send one copy of the minute order to Jennifer Cregar.
Attachments:
Attachment A: Technical Feasibility Study on Community Choice Aggregation for the Central Coast
Region (report and study appendices also may be downloaded at
http://www.centralcoastpower.org/resources.nrg)
Attachment B: CEQA NOE
Attachment C: Comparison Matrix of Community Choice Energy Programs
Authored by:
Jennifer Cregar, Project Supervisor, Energy and Sustainability Initiatives
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Community Choice Energy Program Comparison Matrix
September 2017
Central Coast Power Apple Valley Choice Energy CleanPowerSF Lancaster Choice Energy Marin Clean Energy Peninsula Clean Energy Pico Rivera Innovative
Municipal Energy
Redwood Coast Energy
Authority Silicon Valley Clean Energy Sonoma Clean Power Inland Choice Power Los Angeles Community
Choice Energy
Monterey Bay Community
Power
Milestones
June 2015 - SB County BOS
provided direction and funding for
feasibility study
December 2015 - Advisory Working
Group formed
Summer 2017 - feasibility study and
peer review expected to be
completed
Fall 2017 - CCE votes expected
Spring 2020 - possible launch
2010 - Initial feasibility study
2014-2015 - Updated feasibility
study
September 2016 - Submitted
implementation plan (IP)
November 2016 - IP certified by
CPUC
April 2017 - Launch
May 2004 - SF BOS authorized CCE
program
June 2007 - Draft implementation
plan (IP) approved by SF BOS
March 2010 - Revised IP approved
by SF BOS and submitted to CPUC
May 2010 - CPUC certified IP;
SFPUC & PG&E execute CCA
Service Agreement (later extended
through Dec 2018)
June 2013 - CPUC certified revised
IP
August 2015 - CPUC certified
another revised IP
May 2016 - Phase 1 launch
Nov 2017 - Phase 2 launch
Summer 2019 - Full launch
July 2013 - Initial Phase I feasibility
study completed
Q2 2014 - Phase II feasibility study
completed
May 2014 - Lancaster City Council
authorized CCE program and
approved implementation plan (IP)
October 2014 - CPUC certified IP
March 2015 - CPUC certified
revised IP
May 2015 - Phase 1 launch
Oct 2015 - Remaining residential +
commercial accounts launched
2017 - Launched California Choice
Energy Authority to provide
backend services to other SoCal
CCAs
December 2008 - JPA formed
May 2010 - Phase 1 launch
2011 - Included other accounts in
original member jurisdictions;
added new Marin County cities
2012 - Remaining Marin accounts
started service; Richmond joined;
EE programs launched
2013 - Program launched in
Richmond
2015 - Unincorporated Napa
County and cities of Benicia, El
Cerrito, and San Pablo joined
September 2016 - Additional Napa
and Contra Costa County cities
joined
2018 - Planned addition of
unincorporated Contra Costa
County + 8 cities
December 2014 - Initial CCE
research
September 2015 - Feasiblity study
completed
October 2015 - JPA formed
February 2016 - Deadline for cities
to join JPA
April 2016 - Implementation plan
submitted
October 2016 - Phase 1 launch
April 2017 - Phase 2 launch
October 2017 - Estimated final
phase launch
Mid-2016 - Joined California Choice
Energy Authority to develop
implementation plan and provide
support services
December 2016 - Implementation
plan submitted
September 2017 - Phase 1 (full)
launch
June 2015 - RCEA board approved
CCE implementation
September 2015 - JPA amended for
CCE
October 2016 - Implementation
plan (IP) submitted
January 2017 - IP certified
May 2017 - Full launch
Late 2017 - Ferndale to join (last
city in Humboldt County)
2014 - Initial CCE research
May 2015 - Initial CCE assessment
report
November 2015 - Feasibility study
March 2016 - Formed JPA
April 2016 - Feasibility study
completed
July 2016 - Submitted
implementation plan
April 2017 - Phase 1 launch
July 2017 - Phase 2 (final) launch
2011 - Steering committee formed
to explore CCE; feasibility study
completed
2012 - Original implementation
plan; JPA formed
2013 - Revised implementation
plan submitted and certified; cities
sign on
May 2014 - Phase 1 launch
December 2014 - Phase 2 launch
June 2015 - Cloverdale, Petaluma,
and Rohnert Park joined
June 2017 - Mendocino County,
Fort Bragg, Point Arena, and Willits
joined
November 2016 - Feasibility study
covering tri-COG region completed
Spring 2017 - San Bernardino
County withdrew its interest due
to pressure from anti-CCE group
July 2016 - Feasibility study
completed
September 2016 - LA County BOS
directed staff to proceed and form
a JPA with interested cities
April 2017 - LA County approved
CCE for unincorporated county
January 2018 - Estimated Phase 1
launch
July 2018 - Estimated Phase 2
launch
January 2019 - Estimated Phase 3
launch
2013 - Advisory group formed
Mid-2014 - Study funds raised
May 2016 - Feasibility study
completed
February-April 2017 - JPA formed
August 2017 - Submitted
implementation plan (IP)
March 2018 - Estimated Phase 1
launch
July 2018 - Estimated Phase 2
launch
Current No. Customers Served
Tri-County: ~600,000 accounts
AWG: ~393,000
Unincorporated SB County:
~53,000
~28,000 accounts (July 2017)~76,000 accounts (July 2017);
~360,000 accounts at full launch ~51,000 accounts (July 2017)~256,000 accounts (July 2017)~290,000 accounts (July 2017 ~16,000 accounts (implementation
plan estimate at full launch)~61,000 accounts (July 2017)~210,000 accounts (July 2017)~600,000 accounts (July 2017)~1.3M accounts (feasibility study
estimate at full launch)
Unincorporated county: ~300,000
accounts (feasibility study
estimate)
Uninc. + cities: ~1.5M accounts
(feasibility study estimate at full
launch)
~270,000 accounts (IP estimate at
full launch)
Opt-out Rate
Feasibility study assumed 15% (+ all
Direct Access customers, which
comprise 23.5% of AWG
customers)
Unknown 3.3% (July 2017)6% (October 2016)
16% (Jun 2010, based on initial
participants); decreased to 9% at
most recent program expansion in
Sep 2016
1.8% (July 2017)Unknown 3% (May 2017)< 2% (July 2017)12% (2017)Unknown Unknown IP estimates ~5% (August 2017)
Current Annual Load
Tri-County: ~8,500 GWh
AWG: ~5,900 GWh
Unincorporated SB County: ~1,300
GWh
* Includes non-DA customers only
~220 GWh (2017);
~280 GWh (2018 - 1st full year of
operations)
535 GWh (July 2017); ~3,600 GWh
(full launch)
Peak: 93 MW (July 2017)
~600 GWh (July 2017)
Peak: 123 MW (July 2017)
~2,800 GWh (July 2017)
Peak: 520 MW (July 2017)
~3,600 GWh (July 2017)
Peak: 660 MW (July 2017)
~230 GWh (implementation plan
estimate at full launch)
~730K GWh (implementation plan
estimate at full launch)~3,500 GWh (July 2017)
~2,300 GWh (2016); ~2600 GWh
(June 2017)
Peak: 512 MW (July 2017)
~21,000 GWh (feasibility study
estimate at full launch)
~3,000 GWh (feasibility study
estimate for unincorporated
county)
~2,300 GWh (Phase 1 - March
2018;
Phase 2: ~3,600 GWh (Phase 2 -
July 2018)
Current Financials
For AWG Middle of the Road (50%
Renewable) Scenario, 2020
Net: -$44,000 (feasibility study
estimate)
Revenues: $13.2M (2017 projection
from IP)
Costs: $12.2M (2017 projection
from IP)
Net: $1.0M (2017 projection from
IP)
In process of developing monthly
financial statements; will also be
included in annual CAFRs for SFPUC
(July 2017)
Revenues: $23.4M (2016)
Revenues: $44.1M ( March 2016)
Costs: $14.6M (March 2016)
Net: $29.5M (March 2016)
Net position: $18M (FY16-17);
projected $33M (FY1718)
Revenues: $12.5M (2018
projection from IP)
Costs: $$12.1M (2018 projection
from IP)
Net: $$460,000 (2018 projection
rom IP)
Unknown Net position: $6.7M (June 2017);
$31.1M (2018 projection from IP)
Revenues: $69.6M (June 2017)
Costs: $15.9M (June 2017)
Net: $53.7M (June 2017)
Unknown Unknown
Revenues: $173M (2018 projection
from IP)
Costs: $134M (2018 projection
from IP)
Net: $39M (2018 projection from
IP)
Rollout Strategy
Phase 1: Large commercial
accounts
Phase 2: Small and medium
commercial accounts
Phase 3: Residential, outdoor
lighting, and traffic control
accounts
No phasing - all customers served
on Day 1
Phase 1: Sample of residential and
commercial accounts
Phase 1: Municipal + sample of
residential and commercial
accounts
Phase 2: Remaining
Phase 1: Municipal + sample of
residential and C&I accounts
comprising 20% of load
Phase 2: Another 20% of
residential and C&I accounts
Phase 3: Remaining accounts in
Marin Couny
Phase 4: Richmond accounts
Phase 5: Unincorporated Napa
County accounts
Phase 6: San Pablo, Benicia, and El
Cerrito accounts
Phase 7: American Canyon,
Calistoga, Lafayette, Napa, St.
Helena, Walnut Creek, and
Yountville accounts
Phase 1: Municipal +
small/medium commercial + 20%
of residential + early adopters
Phase 2: Large C&I + 35% of
residential
Phase 3: Agricultural + street
lighting + remaining residential
Phase 4: Remaining (if needed)
No phasing - all customers served
on Day 1
No phasing - all customers served
on Day 1
Phase 1: Municipal +
small/medium commercial + 20%
of residential accounts
Phase 2: All remaining accounts
Note: IP originally called for 3
phases with option for 4th phase;
Board voted to collapse into 2
phases
Phase 1: Sample of residential and
most commercial accounts
Phase 2: Remaining accounts in
initial service territory
Phase 3: Cloverdale, Petaluma, and
Rohner Park accounts
Phase 4: Mendocino County, Fort
Bragg, Point Arena, and Willits
accounts
Phase 1: Municipal accounts + 5%
of commercial accounts
Phase 2: Remaining
Phase 1: LA County municipal
accounts in unincorporated county
Phase 2: Non-residential accounts
Phase 3: Residential accounts
Phase 1: All C&I and agricultural
accounts
Phase 2: All residential accounts
Phase 3: Remaining (if needed)
Post-Launch Governing Body Apple Valley Town Council SFPUC with rate approval by SF
BOS
Lancaster City Council, California
Choice Energy Authority (CCEA) JPA JPA JPA Pico Rivera City Council, California
Choice Energy Authority (CCEA) JPA JPA (existing)JPA JPA JPA JPA JPA
Pre-Launch Coordinating Body
Advisory Working Group comprised
of San Luis Obispo, Santa Barbara,
and Ventura Counties and the cities
of Camarillo, Carpinteria,
Moorpark, Ojai, Santa Barbara, Simi
Valley, Thousand Oaks, and
Ventura
Town of Apple Valley SFPUC City of Lancaster
County of Marin, Marin Municipal
Water District, North Marin Water
District, Berkeley, Emeryville,
Oakland, and Pleasant contributed
to "CCA Demonstration Project"
Later formed Local Government
Task Force
County advisory committee of all
cities and select stakeholders met
for 8 months until JPA was formed
and Board was seated
City of Pico Rivera RCEA Board
CCE Partnership comprised of
Santa Clara County, Cupertino,
Mountain View, and Sunnyvale
later morphed into JPA with all 12
participating jurisdictions
Steering committee of the Sonoma
County Water Agency, city council
members, city managers and staff,
business representatives, activists,
and others
Informal coordination among
Coachella Valley Association of
Governments, San Bernardino
Associated Governments, and
Western Riverside Council of
Governments
Stakeholder advisory group led by
LA County
Santa Cruz County hosts the
Planning and Development
Advisory Committee which is made
up of interested cities and some
local experts
OPERATIONAL IN DEVELOPMENT
Page 1 of 5 Packet Pg 53
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Community Choice Energy Program Comparison Matrix
September 2017
Central Coast Power Apple Valley Choice Energy CleanPowerSF Lancaster Choice Energy Marin Clean Energy Peninsula Clean Energy Pico Rivera Innovative
Municipal Energy
Redwood Coast Energy
Authority Silicon Valley Clean Energy Sonoma Clean Power Inland Choice Power Los Angeles Community
Choice Energy
Monterey Bay Community
Power
OPERATIONAL IN DEVELOPMENT
Community Advisory Committee No
Not explicity for CPSF, but SFPUC
has an existing Citizens' Advisory
Committee that includes a Power
Subcommittee
No No Yes Unknown
Yes - existing Community Advisory
Committee to also provide
feedback on CCE matters
Unknown
Yes - JPA Agreement includes
requirement for:
- Ratepayer Advisory Committee
to be appointed by board and
comprised of 3 C&I customers and
4 residential customers (1 of whom
must be a tenant)
- Business Operations Committee
to be appointed by board and
comprised of 5 members with
expertise in managmeent,
administration, finance, public
contracts, infrastructure
development, renewable power
generation, power sale and
marketing, and energy
conservation
Unknown Unknown Yes
Original Jurisdictions 1) Apple Valley 1) City and County of San Francisco 1) Lancaster
1) Marin County
2) Belvedere
3) Fairfax
4) Mill Valley
5) San Anselmo
6) San Rafael
7) Sausalito
8) Tiburon
1) San Mateo County
2) Atherton
3) Belmont
4) Brisbane
5) Burlingame
6) Colma
7) Daly City
8) East Palo Alto
9) Foster City
10) Half Moon Bay
11) Hillsborough
12) Menlo Park
13) Millbrae
14) Pacifica
15) Portola Valley
16) Redwood City
17) San Bruno
18) San Carlos
19) San Mateo
20) South San Francisco
21) Woodside
1) Pico Rivera
1) Humboldt County
2) Arcata
3) Blue Lake
4) Eureka
5) Fortuna
6) Rio Dell
7) Trinidad
1) Santa Clara County
2) Campbell
3) Cupertino
4) Gilroy
5) Los Altos
6) Los Altos Hills
7) Los Gatos
8) Monte Sereno
9) Morgan Hill
10) Mountain View
11) Saratoga
12) Sunnyvale
1) Sonoma County
2) Cotati
3) Santa Rosa
4) Sebastopol
5) Sonoma
6) Windsor
1) Riverside County
2) Banning
3) Blythe
4) Calimesa
5) Canyon Lake
6) Catherdral City
7) Coachella
8) Corona
9) Desert Hot Springs
10) Eastvale
11) Hemet
12) Indian Wells
13) Indio
14) Jurupa Valley
15) La Quinta
16) Lake Elsinore
17) Menifee
18) Moreno Valley
19) Murrieta
20) Norco
21) Palm Desert
22) Palm Springs
23) Perris
24) Rancho Mirage
25) Riverside
26) San Jacinto
1) Los Angeles County
1) Monterey County
2) Carmel-By-The-Sea
3) Del Rey Oaks
4) Gonzales
5) Greenfield
6) King City
7) Marina
8) Monterey
9) Pacific Grove
10) Salinas
11) Sand City
12) Seaside
13) Soledad
14) San Benito County
15) Hollister
16) San Juan Bautista
17) Santa Cruz County (lead
agency)
18) Capitola
19) Santa Cruz
20) Scotts Valley
21) Watsonville
Current Jurisdictions 1) Apple Valley 1) City and County of San Francisco
1) Lancaster
Note: CCEA jurisdictions listed
separately
1) Marin County
2) Belvedere
3) Corte Madera
4) Fairfax
5) Larkspur
6) Mill Valley
7) Novato
8) Ross
9) San Anselmo
10) San Rafael
11) Sausalito
12) Tiburon
13) Napa County
14) American Canyon
15) Calistoga
16) Napa
17) St. Helena
18) Yountville
19) Benicia (Solano County)
20) El Cerrito (Contra Costa
County)
21) Richmond (Contra Costa
County)
22) San Pablo (Contra Costa
County)
23) Walnut Creek (Contra Costa
1) San Mateo County
2) Atherton
3) Belmont
4) Brisbane
5) Burlingame
6) Colma
7) Daly City
8) East Palo Alto
9) Foster City
10) Half Moon Bay
11) Hillsborough
12) Menlo Park
13) Millbrae
14) Pacifica
15) Portola Valley
16) Redwood City
17) San Bruno
18) San Carlos
19) San Mateo
20) South San Francisco
21) Woodside
1) Pico Rivera
1) Humboldt County
2) Arcata
3) Blue Lake
4) Eureka
5) Fortuna
6) Rio Dell
7) Trinidad
1) Santa Clara County
2) Campbell
3) Cupertino
4) Gilroy
5) Los Altos
6) Los Altos Hills
7) Los Gatos
8) Monte Sereno
9) Morgan Hill
10) Mountain View
11) Saratoga
12) Sunnyvale
1) Sonoma County
2) Cloverdale
3) Cotati
4) Petaluma
5) Rohnert Park
6) Santa Rosa
7) Sebastopol
8) Sonoma
9) Windsor
10) Mendocino County
11) Fort Bragg
12) Point Arena
13) Willits
It appears Riverside County,
Rancho Mirage, and San Jacinto
will pursue their own CCAs
independent of what the Tri-COG
region chooses. San Bernardino
County is not moving forward.
1) Los Angeles County
2) Calabasas
3) Rolling Hills Estates
4) South Pasadena
5) West Hollywood
1) Monterey County
2) Carmel-By-The-Sea
3) Gonzales
4) Greenfield
5) Marina
6) Monterey
7) Pacific Grove
8) Salinas
9) Sand City
10) Seaside
11) Soledad
12) San Benito County
13) Hollister
14) San Juan Bautista
15) Santa Cruz County (lead
agency)
16) Capitola
17) Santa Cruz
18) Scotts Valley
19) Watsonville
Page 2 of 5 Packet Pg 54
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Community Choice Energy Program Comparison Matrix
September 2017
Central Coast Power Apple Valley Choice Energy CleanPowerSF Lancaster Choice Energy Marin Clean Energy Peninsula Clean Energy Pico Rivera Innovative
Municipal Energy
Redwood Coast Energy
Authority Silicon Valley Clean Energy Sonoma Clean Power Inland Choice Power Los Angeles Community
Choice Energy
Monterey Bay Community
Power
OPERATIONAL IN DEVELOPMENT
JPA Composition N/A N/A
Spun off California Choice Energy
Authority to provide back-office
services to other cities pursuing
CCE
24 members - 1 per jurisdiction
Nominee and alternate required to
be elected official
22 members - 1 per city + 2 for San
Mateo County
Nominee required to be elected
official; alternate can also be staff
Member of California Choice
Energy Authority
9 members - 1 per jurisdiction +
water district
12 members - 1 member per
jurisdiction
Nominee required to be elected
official; alternate can also be staff
or member of public
2 official JPA members (County +
Water Agency), but all 9 cities sit
on board and have voting
privileges, so 11 participants
overall - currently 1 per
jurisdiction, but allowed to appoint
more than 1 with board approval;
Santa Rosa permitted to have
same number of voting
participants as Sonoma County
Not required to be elected official
Feasibility study evaluates two JPA
options:
1) New tri-COG JPA
2) Separate existing JPAs (1 per
COG)
5 members (as of September 2017)
- 1 member per jurisdiction
Nominee required to be elected
official; alternates (up to 2) can
also be a member of an advisory
body, staff person, or member of
public
11 members - weighted based on
population as follows:
- 1 seat per jurisdiction for
populations of 50K+:
1) Monterey County
2) Santa Cruz County
3) Salinas
4) Santa Cruz
5) Watsonville
- 1 seat per jurisdiction b/c of
large geographic area:
6) San Benito County
- 1 seat shared b/t Santa Cruz
County's small cities:
7a) Scotts Valley
7b) Capitola
- 1 seat shared among Monterey
County's small Peninsula Cities:
8a) Carmel
8b) Monterey
8c) Pacific Grove
JPA Voting Structure N/A N/A N/A
1st Tier: Voting share is split 50/50
as follows:
- Simple Majority (1 vote per
member)
- Load Share (proportional based
on load)
2nd Tier: Special Voting
- 2/3 majority (based on 50/50
split above) required to amend JPA
agreement
1st Tier: Simple Majority (1 vote
per member)
2nd Tier: Load Share (proportional
based on load) + Simple Majority
- 1 vote per member except for
County which must share 1 vote
among its 2 positions
- Can be called by any member on
any vote
3rd Tier: Special Voting
- 2/3 majority required for
involuntary termination of a
member or amendment of the JPA
agreement
- 3/4 majority required for
eminent domain and member $
contributions
N/A
1st Tier: Voting share is weighted
as follows:
- 1/3 Pro Rata Share calculated as
follows: [1/Total # CCE
Participants] x 1/3
- 2/3 Customer Base Share
calculated as follows [# CCE
customers in member's
jurisdiction/Total # of CCE
customers] x 2/3
Only CCE participants may vote on
CCE matters (not all existing RCEA
JPA members are CCE participants).
2nd Tier (applies to all RCEA
members, not just CCE
participants): Special Voting
- 2/3 majority required for
amending the JPA agreement and
allowing members to withdraw
1st Tier: Simple Majority (1 vote
per member)
2nd Tier: Load Share (proportional
based on load)
- Requires 2+ members to call for
this voting process
- Also requires Simply Majority
3rd Tier: Special Voting
- 2/3 majority required to add
members, incur debt, allow
members to withdraw, shorten
notification period for members to
withdraw, involuntarily terminate a
member, or amend the JPA
agreement
1st Tier: Load Share (proportional
based on load)
- If jurisdiction has more than 1
member, jurisdiction gets only 1
weighted vote
2nd Tier: Load Share + Simple
Majority (1 vote per member)
- Can be called by any member on
any vote
3rd Tier: Special Voting
- 2/3 majority required for
removal of Ratepayer Advisory
Committee member, involuntary
termination of a party, or
amending the JPA agreement; can
also require load share vote
- 3/4 majority required for
eminient domain and member $
contributions; can also require load
share vote
Unknown
1st Tier: Simple Majority (1 vote
per member)
2nd Tier: Load Share
- Can be called by 3+ members on
any affirmative 1st Tier vote
3rd Tier: Special Voting
- 2/3 majority required for change
of Treasurer or Auditor, issuing
bonds or other debt, eminent
domain, amending the JPA
agreement, or involuntary
termination of a party
1st Tier: Simple Majority (1 vote
per member, per seat assignments
above)
2nd Tier: Special Voting
- 2/3 majority required for
involuntary termination of a party
or amending the JPA agreement
- 3/4 majority required for
eminent domain and member $
contributions
JPA Entry Requirements N/A N/A N/A
"Initial Participants" must execute
JPA agreement within 6 months of
the 1st two local governments
signing and have lower
requirements:
- Executed JPA agreement
- Ordinance
To join after 1st 6 months, member
agency must submit:
- Executed JPA agreement
- Resolution
- Ordinance
- Membership fee (proportional)
- MCE currently does not
require fee to join
- Agreement to any supplemental
conditions (established by JPA
board)
- Receive affirmative vote of JPA
board
Takes effect when the County of
San Mateo and 2+ municipalities
execute agreement.
To join, member agency must
submit:
- Executed JPA agreement
- Ordinance
N/A
To join, existing RCEA members
must submit:
- Ordinance
Takes effect when 3+ initial
participants execute agreement
To join, member agency must
submit:
- Executed JPA agreement
- Resolution
- Ordinance
- Membership fee (proportional)
- Initial participants share Phase
2 & 3 costs, which must be
provided within 30 days of
agreement execution date
- Agreement to any supplemental
conditions (established by JPA
board)
To join, member agency must
submit:
- Executed JPA agreement
- Resolution
- Ordinance
- Membership fee (proportional)
- Agreement to any supplemental
conditions (established by JPA
board)
- Receive affirmative vote of JPA
board
Unknown
Takes effect when LA County + 1
other entity execute agreement
Other "Initial Participants" must
execute JPA agreement within 6
months of the 1st two local
governments signing and have
lower requirements:
- Executed JPA agreement
- Ordinance
To join after 1st 6 months, member
agency must submit:
- Executed JPA agreement
- Ordinance
- Membership fee (proportional)
- Agreement to any supplemental
conditions (established by JPA
board)
- Receive affirmative vote of JPA
board
Takes effect when 3+ jurisdictions
execute agreement.
To join, member agency must
submit:
- Executed JPA agreement
- Ordinance
- Membership fee (start-up costs
allocated proportionally based on
population for credit guarantee)
JPA Exit Requirements N/A N/A N/A
Minimum 30-day notice prior to
initial program agreement
Subsequent to initial program
agreement, minimum 6-month
notice required with withdrawal to
take effect at beginning of next FY
Liable for applicable costs through
termination date
Minimum 15-day notice prior to
program launch if, after receiving
bids from power suppliers, bids do
not result in:
1) rates equal to or less than
PG&E,
2) GHG emission rates lower than
PG&E, OR
3) renewable energy content
higher than PG&E
Subsequent to program launch,
minimum 6-month notice required
with withdrawal to take effect at
beginning of next FY
30-day notice required if member
seeks to withdraw after an
amendment to the JPA agreement
that the member voted against
Except for the pre-program launch
withdrawal option, liable for
applicable costs through
termination date
N/A
No specific exit requirements for
CCE participants; any member may
withdraw upon receiving 2/3 vote
Minimum 15-day notice prior to
program launch if, after receiving
bids from power suppliers, bids do
not result in:
1) rates equal to or less than
PG&E,
2) GHG emission rates lower than
PG&E, OR
3) renewable energy content
higher than PG&E
Subsequent to program launch,
minimum 6-month notice required
with withdrawal to take effect at
beginning of next FY
Pre-vote notice required if
member seeks to withdraw after
an amendment to the JPA
agreement that the member plans
to vote against
Liable for applicable costs through
termination date, even if withdraw
prior to program launch
Minimum 6-month notice required
with withdrawal to take effect at
beginning of next FY
30-day notice required if member
seeks to withdraw after an
amendment to the JPA agreement
that the member voted against
Liable for applicable costs through
termination date
Unknown
Minimum 6-month notice and
affirmative vote of local
government's governing body
required
Liable for applicable costs through
termination date
Minimum 15-day notice prior to
program launch if, after receiving
bids from power suppliers, bids do
not result in:
1) rates equal to or less than
PG&E,
2) GHG emission rates lower than
PG&E, OR
3) renewable energy content
higher than PG&E
Minimum 6-month notice required
with withdrawal to take effect at
beginning of next FY
30-day notice required if member
seeks to withdraw after an
amendment to the JPA agreement
that the member voted against
Liable for applicable costs through
termination date (for pre-program
launch withdrawal option, only
liable for proportionate credit
guarantee contribution)
Page 3 of 5 Packet Pg 55
1
Community Choice Energy Program Comparison Matrix
September 2017
Central Coast Power Apple Valley Choice Energy CleanPowerSF Lancaster Choice Energy Marin Clean Energy Peninsula Clean Energy Pico Rivera Innovative
Municipal Energy
Redwood Coast Energy
Authority Silicon Valley Clean Energy Sonoma Clean Power Inland Choice Power Los Angeles Community
Choice Energy
Monterey Bay Community
Power
OPERATIONAL IN DEVELOPMENT
JPA Compensation N/A N/A N/A No - but reimbursement policy
may be adopted
No - but reimbursement policy
may be adopted N/A
No - but will reimburse for
documented expenses related to
Board duties
No - but reimbursement policy
may be adopted
No - but reimbursement policy
may be adopted Unknown Unknown No - but reimbursement policy
may be adopted
Implementation model (at launch)
In-house
1) Finance
2) Outreach/marketing
3) Key account management
4) Resource planning
5) Legal/regulatory (with outside
counsel as needed)
Outsourced
1) Customer service/call center
2) Data management/billing
coordination/enrollment
3) Power scheduling
4) Power procurement
5) Legal/regulatory
In-house
1) Resource planning
2) Power procurement
3) Finance
4) Key account management
5) Legal/regulatory
6) Outreach/marketing
Outsourced
1) Power scheduling
2) Customer service/call center
(with expectation to bring in-
house)
3) Data management/billing
coordination/enrollment (with
expectation to bring in-house)
4) DSM program development and
implementation (via SFE and
possibly others)
In-house
1) Finance
2) Outreach/marketing
Outsourced
1) Resource planning
2) Power procurement
3) Power sheduling
4) Customer service/call center
5) Data management/billing
coordination/enrollment
6) Legal/regulatory
7) DSM program development and
implementation
In-house
1) Finance
2) Outreach/marketing
3) Key account management
4) Legal/regulatory
Outsourced
1) Resource planning
2) Power procurement
3) Power scheduling
4) Customer service/call center
5) Data management/billing
coordination/enrollment
In-house
1) Finance
2) Outreach/marketing
3) Key account management
4) Legal/regulatory
5) Resource planning
Outsourced
1) Power procurement
2) Power scheduling
3) Customer service/call center
4) Data management/billing
coordination/enrollment
In-house
1) Finance
2) Outreach/marketing
3) Key account management
4) Legal/regulatory (with outside
counsel as needed)
Outsourced
1) Resource planning
2) Power procurement
3) Power scheduling
4) Customer service/call center
5) Data management/billling
coordination/enrollment
In-house
1) Finance
2) Key account management
3) Resource planning (in
coordination with TEA)
4) Outreach/marketing (in
coordination with LEAN)
Outsourced
1) Power procurement
2) Power scheduling
3) Customer service/call center
4) Data management/billing
coordination/enrollment
5) Outreach/marketing
6) Legal/regulatory
In-house
1) Finance
2) Outreach/marketing
3) Key account management
4) Resource planning
5) Legal/regulatory (with outside
counsel as needed)
Outsourced
1) Customer service/call center
2) Data management/billing
coordination/enrollment
3) Power scheduling
4) Power procurement
5) Legal/regulatory
In-house
1) Finance
2) Outreach/marketing
3) Key account management
4) Legal/regulatory
Outsourced
1) Resource planning (later
brought in house
2) Power procurement (later
brought in house)
3) Power scheduling
4) Customer service/call center
(some brought in house)
5) Data management/billing
coordination/enrollment
Unknown Unknown
In-house
1) Finance
2) Outreach/marketing
3) Key account management
4) Legal/regulatory (with outside
counsel as needed)
5) Resource planning
Outsourced
1) Power procurement
2) Power scheduling
3) Customer service/call center
4) Data management/billing
coordination/enrollment
5) Legal/regulatory
Vendors
Technical: Willdan/EnerNex
Other: LEAN Energy US, MRW &
Associates (peer review)
Power Supply: Shell Energy North
America
Technical: Davis & Associates
Communications, MRW &
Associates, and Pacific Energy
Advisors
Power Scheduling: APX
Power Supply: Calpine,
Constellation, and Iberdrola
Data Management/Call Center:
Calpine Energy Solutions (formerly
Noble Americas)
Other: Willdan/EnerNex (job
creation impact); SF Department of
Environment (DSM)
Technical: Willdan/EnerNex,
Pacific Energy Advisors
Power Supply & Scheduling: Direct
Energy
Data Management/Call Center:
Calpine Energy Solutions (formerly
Noble Americas)
Technical: Navigant Consulting
Power Supply: Shell Energy North
America, G2Energy, Dominoin,
Genpower, Calpine, EDP,
Recurrent, Waste Management,
East Bay MUD, Avangrid, Portland
General Electric, 3 Phases,
SunPower, Powerex, City of Santa
Clara, First Solar, Nextera, SPower,
EDF, Terra Gen, LA County
Sanitation District, WAPA, Exelon,
Energy America, Morgan Stanley
Forecasting: Pacific Energy
Advisors
Data Management/Call Center:
Calpine Energy Solutions (formerly
Noble Americas)
Technical: Pacific Energy Advisers
Marketing: Circlepoint; Green
Ideals
Power Scheduling: Energy America,
ZGlobal
Power Supply: Energy America,
Shell Energy North America,
Exelon, NRG, Mega Renewables,
Wright Solar Park, Silicon Valley
Power, Direct Energy, Buena Vista
Energy, Energy Development &
Construction Corp., Cuyama Solar,
LLC, Morgan Stanley Group
Data Management/Call Center:
Calpine Energy Solutions (formerly
Noble Americas)
Other: MRW & Associates (peer
review); Winston & Strawn (legal);
Troutman Sanders (legal); PIN
Presort (mailing)
California Choice Energy Authority
Strategy: LEAN
Technical: The Energy Authority
Marketing: LEAN
Power Supply & Scheduling: The
Energy Authority
Data Management/Call Center:
Calpine Energy Solutions (formerly
Noble Americas)
Other: Braun Blaising McLaughlin
& Smith (legal/regulatory),
Richards Watson & Gershon
(legal/regulatory)
Technical: Pacific Energy Advisers
Technical: Dalessi Management
Consulting (now Pacific Energy
Advisors)
Power Scheduling: Constellation,
Shell Energy North America
Power Supply: Constellation, NRG,
Direct Energy, ConEdison (finalists
but not clear if contracts were
executed with all)
Data Management/Call Center:
Calpine Energy Solutions (formerly
Noble Americas)
Other: MRW & Associates (peer
review); Troutman Sanders (legal)
Technical: EES Consulting with Bki
Technical: EES Consulting with BKi
Other: Arc Alternatives (peer
review)
Strategy: LEAN
Technical: Pacific Energy Advisors
Marketing: Miller Maxfield
Other: MRW & Associates (peer
review)
Staffing
Tri-County: 57 FTEs (feasibility
study estimate)
AWG: 45 FTEs (feasibility study
estimate)
Unincorporated SB County: 28 FTEs
(feasibility study estimate)
3-5 FTEs (May 2017)10 FTEs (May 2017)3-5 FTEs (May 2017)40-45 FTEs (May 2017)10-15 FTEs (May 2017)3 FTEs expected to start
(September 2017)
3 dedicated FTEs + 4 mostly
dedicated FTEs + interns + 2 FTE
CCE/EE shared Key Account
Managers (May 2017)
12 FTEs (May 2017)15-20 FTEs (May 2017)Unknown Unknown 8 FTEs to launch (Aug 2017)
Funding Sources
Feasibility Study: $220,756
provided by members of AWG
Start Up: Feasibility study suggests
a bond issuance
Feasibility Study: GF
Start Up: ~$2.6M from GF (includes
interest, 5-year repayment term
starting in 2nd year of operations);
Feasibility Study: General Fund
Start Up: ~$12.9M from SF GF
($8.9M for feasibility study, IP, etc.
+ $4M for 2 months working
capital that was subject to internal
0.73% IR)
Feasibility Study: ~$600K (not
confirmed)
Start Up: Combination of financing
($3M line of credit) and negotiated
cash flow agreements with power
service providers (begin payback in
3rd year of operations with 3 years
to pay in full)
Start UP: ~$3.4M
- $110K CEC grant
- $75K BAAQMD grant
- $140K Marin Municipal Water
District contribution
- $10K North Marin Water District
contribution
- $847K Marin County
contribution (including interest-
free loans)
- $750K loan from 3 individuals
($250K each investor @ 5.75% IR,
unsecured)
- $1.45M in bank loans (secured
by Marin County and City of
Fairfax, both of whom earned
interest)
MCE has a $25M line of credit with
River City Bank but has not used it
as of June 2017
Feasibility Study: San Mateo
County provided funding from GF
(from residual revenues of a
previous project)
Start Up: Combination of County
and bank financing, including $12
million loan from Barclay and
nearly $9M from County including
$6M credit guarantee for bank
loan; County loans include interest
Feasibility Study: General Fund
Start Up: General Fund
Feasibility Study: Included in start
up costs fronted by TEA
Start Up: ~$8.2M
- $120K RCEA GF
- $700K Revolving line of credit
wtih 5% interest from county
economic development fund
- Balance vendor financed with
5% interest for power procurement
and operational costs
Feasibility Study: ~$680K split
evenly between the County,
Cupertino, Mountain View, and
Sunnyvale
Start Up: ~$222.7M, of which
$2.0M shared proportionally
among initial participants to JPA
agreement, with repayment within
3 years (codified in agreement); all
debt expected to be repaid by
December 2017
Feasibility Study: $60K funded by
Water Agency
Start Up: $10M funded through 2
separate lines of credit (one for
power procurement-related
expenses and the other for
everything else)
Feasibility Study: Each COG
contributed proportionately
Start Up: ~$20M (feasibility study
estimate)
Feasibility Study: GF, up to $15M
of which the JPA agreement
specifies will be repaid to LA
County
Start Up: ~$43M (feasibility study
estimate)
Feasibility Study: ~$400K from a
combination of grants and private
individual and organization
contributions
Start Up: ~$13M (feasibility study
and IP estimate) secured through 2
loans from River City Bank; IP
states MBCP expects to recover
borrowed costs within 1st year of
operations; JPA agreement
includes provision for Santa Cruz
County to be reimbursed for its
early contributions
Page 4 of 5 Packet Pg 56
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Community Choice Energy Program Comparison Matrix
September 2017
Central Coast Power Apple Valley Choice Energy CleanPowerSF Lancaster Choice Energy Marin Clean Energy Peninsula Clean Energy Pico Rivera Innovative
Municipal Energy
Redwood Coast Energy
Authority Silicon Valley Clean Energy Sonoma Clean Power Inland Choice Power Los Angeles Community
Choice Energy
Monterey Bay Community
Power
OPERATIONAL IN DEVELOPMENT
Products & Rates
Base - 35% renewable at 3%
discount relative to SCE generation
rate (CARE rate 13% lower)
Premium - 50% renewable at
$2/month premium (residential) or
$0.002/kWh premium (non-
residential)
Base - 40% renewable (Cat 1),
example generation charge slightly
lower than PG&E but total bill
roughly equivalent
Premium - 100% renewable (Cat 1),
base rate + $0.02/kWh; rates and
total bill lower than PG&E 100%
green product
Note: overall 2017 portfolio is 53%
renewable
Base - 35% renewable, example
residential generation charge and
overall monthly bill very slightly
lower (-$1 for resi and -$2.60 for
C&I); designed to be 3% lower than
SCE
Premium - 100% renewable, flat
$10 premium resulting in about
$10 higher monthly bill for
example residential customer
Base - 50% renewable, example
residential generation charge $12
lower than PG&E but total bill
slightly higher (+$2)
Premium 1 - 100% renewable,
example residential generation
charge $7 lower than PG&E but
total bill higher (+$6); 2.6% of sales
in 2016
Premium 2 - 100% local solar,
example residential generation
charge $20 higher than PG&E and
total bill much higher (+$34)
Note: IP noted 25% renewable at
launch; have 626.5 MW of new
generation under contract
Base - 50% renewable and 80%
carbon free at 5% discount below
PG&E generation rate
Premium - 100% renewable and
100% carbon free at $0.01/kWh
premium
Note: One of PCE's new-build
projects is Cuyama (40MW)
Base - 50% renewable at unknown
rate delta (estimated 1-5% savings
in IP)
Premium - 100% renewable at $11
more for residential customers and
$0.01/kWh premium for non-
residential customers
Base - 40% renewable - designed
portfolio to achieve 2.7% rate
savings compared to PG&E's
standard rate
Premium - 100% renewable at
$0.01/kWh premium
Base - 50% RPS-eligible renewable
& 100% carbon free (other 50%
from hydro, as of April 2017) at 1%
below PG&E; example residential
generation charge ~$15 lower than
PG&E and total bill roughly the
same
Premium - 100% renewable and
100% carbon free at <$0.01/kWh
premium; example residential
generation charge ~$11 lower than
PG&E and total bill ~$3 more
Base - 42% RPS-eligible renewable
and 91% carbon free
Premium - 100% renewable & local
to Sonoma County (geothermal)
Note: IP noted 33% RE at launch
and has incrementally increased
since then
Feasibility study evaluates three
renewble content scenarios
(savings shown for year 1):
1) RPS-equivalent - estimated
4.9% rate savings compared to SCE
standard rate
2) 50% renewable - estimated
3.8% rate savings compared to SCE
standard rate; 11.2% rate savings
compared to SCE 50% green power
product
3) 100% renewable - estimated
5.7% rate increase compared to
SCE standard rate; 9.4% rate
savings compared to SCE 100%
green power product
Feasibility study evaluates three
renewable content scenarios
(savings shown for year 1):
1) RPS-equivalent - estimated
5.4% rate savings compared to SCE
standard rate
2) 50% renewable - estimated
4.1% rate savings compared to SCE
standard rate
3) 100% renewable - estimated
6.3% rate increase compared to
SCE standard rate
Board is considering 30-35% RPS-
eligible renewable energy in base
product at launch with the
remaining power coming from
carbon free resources
Board is considering setting rates
exactly equal to PG&E by customer
class and returning any
accumulated revenues above costs
to customers in the form of a
quarterly or year-end bill credit
Rate Setting and Structure
Rates approved by Town Council
Customer classes generally match
SCE's with option to establish
customized tariffs for large C&I
customers (e.g., indexed pricing,
fixed term pricing)
Rates set through public process
overseen by existing Rate Fairness
Board and approved by SFPUC
Board with veto authority by SF
BOS
Customer classes match PG&E's at
launch with flexibility to modify
later
Rates approved by City Council
Adopted simplified (not 1:1) rate
structure/customer class from
beginning
Rates approved by JPA Board
Customer classes generally match
PG&E's
Rates approved by JPA Board
Customer classes generally match
PG&E's with flexibility to modify
Rates approved by City Council
Customer classes generally match
SCE's with option to establish
customized tariffs for large C&I
customers
Rates approved by JPA Board
Customer classes generally match
PG&E's
Rates approved by JPA Board
Customer classes generally match
PG&E's with option to establish
customized tariffs for large C&I
customers (e.g., indexed pricing,
fixed term pricing)
Rates approved by JPA Board
Customer classes generally match
PG&E's with flexibility to modify
(e.g., customerize for C&I
customers)
Unknown Rates to be approved by JPA board
Rates to be approved by JPA board
Customer classes generally match
PG&E's with flexibility to modify
(e.g., customerize for C&I
customers)
Reserve Fund
Reserve Fund: 5 months working
capital
Contingency/Rate Stabilization
Fund: 12% of power costs + 10% of
non-power costs
Reserve Fund: 3% of annual
revenues
Contingency/Rate Stabilization
Fund: Unknown
Reserve Fund: 90 days operating
costs
Contingency/Rate Stabilization
Fund: 15% of annual revenues to
be achieved within 3 years of
completing enrollment
Reserve Fund: Unknown
Contingency/Rate Stabilization
Fund: Unknown
Reserve Fund: 90 days operating
costs
Contingency/Rate Stabilization
Fund: 15 % of annual revenues to
be achieved by March 2019
(subject to ability to maintain
competitive rates)
Reserve Fund: Unknown
Contingency/Rate Stabilization
Fund: 5% of annual gross revenues
Unknown
Reserve Fund: $6M within first
year of operations
Contingency/Rate Stabilization
Fund: Unknown
Reserve Fund: 90 days operating
costs, excluding power costs
Contingency/Rate Stabilization
Fund: Unknown
Reserve Fund: Unknown
Contingency/Rate Stabilization
Fund: Unknown
Unknown Unknown Reserve Fund: ~50% of operating
expenses
Use of Unbundled RECs No Yes - 8% (July 2017)No - exclusively use Cat 1 (CA
bundled) RECs Yes - 8% (July 2017)
Yes - 2017-2026 IRP commits to ≤
3% unbundled RECs in line with
RPS
No Unknown Initially no, but does not appear to
be explicit restriction on Cat 3 RECs
Initially no, but amended
procurement strategy to include
up to 12.5% Cat 3 RECs for 2017-18
due to difficulty securing Category
2 RPS-eligible renewables
Initially yes; sold Cat 3 RECs in 2016
and will only use going forward if
required to suport local RE
programs or protect the value of
CA renewables
Unknown Unknown No
Renewable Energy/Environmental
Goals
Lower GHG emissions and supports
participating local governments'
climate action plans
Prioritizes local and in-state
renewable resources
Unknown Unknown City aims to be zero net energy
community
Base product to be 80% renewable
by 2025; long-term* goal of 100%
renewable energy
75% GHG-free portfolio by 2017;
100% GHG-free portfolio by 2025
("subject to operational
practicalities and product
availability")
25 MW of local solar by 2021
Long-term* goal of offsetting 2% of
annual energy requirements with
DER
Offset 5% of annual capacity
(Resource Adequacy) requirements
through DR by 2026
* Long-term not defined
100% GHG-free portfolio by 2021
100% CA RPS eligible renewable
energy by 2025
20MW of new local power by 2025
Unknown
5% more renewables than PG&E
5% lower GHG intensity than PG&E
100% carbon free
Reduce electricity sales by 0.5% by
2024 through energy efficiency
(incremental to existing PG&E EE
efforts)
Website states SCP is "on track" to
be 50% renewable by 2020 Unknown Unknown Maximize carbon-free resources
DSM Programs Desires to administer/support DSM
programs
Plans to apply for independent
administration
Plans to apply for independent
administration
Withdrew business plan to apply
for independent administration Self administer
Plans to apply for independent
administration; may bring existing
local DSM programs in house
Plans to apply for independent
administration
Does not plan to apply to
administer; RCEA to continue to
administer PG&E-funded programs
with intent to add new programs
Plans to apply for independent
administration; may bring existing
local DSM programs in house
Plans to apply for independent
administration; may bring existing
local DSM programs in house
Unknown Unknown
Do not plan to apply for
independent administration within
the first few years; TBD after that
Opt-out Notice Mechanism Mailer Mailer independent from PG&E
bills Mailer Mailer Mailer - possible bill insert with
PG&E Mailer Mailer Mailer Mailer Unknown Unknown Mailer
Opt-out Fee (after 1st 60 days)Resi- $5; C&I - $25 (proposed)Resi - $5; C&I - $25
Not clear - no mention of fee on
website but IP included an
estimated $75 fee for resi and$100
for C&I
Resi - $5; C&I - $5-25 Resi - $5; C&I - $25 (after 1st year
of service)Unknown No fee
Base product: Resi - $5; C&I - $25
Premium product: Resi - $105;
Small C&I - $125; Large C&I - $25 +
$0.03/kWh (if no notice) or $25 (6-
month notice)
Resi - $5; C&I - $25 Unknown Unknown Resi - $5; C&I - $25 (estimate
included in IP)
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FINAL REPORT
3H9HFG 2017
ON COMMUNITY CHOICE AGGREGATION
FOR THE CENTRAL COAST REGION
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EXECUTIVE SUMMARY
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Executive Summary
A. Community Choice Aggregation Overview
Community Choice Aggregation (CCA) is a program for local jurisdictions in California to procure
electricity supply for, and develop energy resources to serve, jurisdictional customers. According to the
Local Government Commission,1 the most common reasons for forming a CCA program are to:
Increase use of renewable generation,
Exert control over rate setting,
Stimulate economic growth, and
Lower rates.
When a CCA is formed, the local incumbent electric investor-owned utility (IOU) continues to deliver
power through its transmission and distribution facilities to customers within its service territory. The
IOU also provides monthly customer metering and billing services. The local CCA program procures the
electric commodity and sells it to its customers, with the intent that the electricity is less expensive, more
local, and/or uses more renewable generation than the current utility alternative. The two components,
delivery and generation, already appear separately on customer bills. The incumbent utility continues to
provide billing services, but the CCA’s generation rate replaces the IOU’s generation rate on customer
bills.
Jurisdictions in California have formed CCA programs in efforts to provide constituents the option to be
served with a greater mix of renewable and carbon-free energy generation than is provided by the
incumbent utility. Eight CCA programs are
currently operational in California, with ten more
launching in 2018. At least 17 additional
jurisdictions are exploring and/or are in the
planning stages for CCA.
B. Study Scope and Purpose
This technical feasibility Study for CCA for the
Central Coast Region (Study) was directed by the
Advisory Working Group (AWG), which was
formed by eleven governments in the Santa
Barbara, San Luis Obispo, and Ventura County
(Tri-County) Region. The Advisory Working
Group collectively has named the potential CCA
“Central Coast Power.” The Study’s purpose is to
advise and guide the Tri-County Region in
understanding the feasibility of forming a new CCA
program. This Study considers required startup
and operational processes and evaluates multiple
Ten local governments joined with the County of
Santa Barbara to fund this Study, and the
following jurisdictions formed an Advisory
Working Group in December 2015:
• Unincorporated San Luis Obispo County
• Unincorporated Santa Barbara County, plus:
o City of Carpinteria
o City of Santa Barbara
• Unincorporated Ventura County, plus:
o City of Camarillo
o City of Moorpark
o City of Ojai
o City of Simi Valley
o City of Thousand Oaks
o City of Ventura
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Executive Summary
Technical Feasibility Study Central Coast Region
on Community Choice Aggregation August 2017
ES-2
procurement scenarios to determine whether a CCA program in the Tri-County Region is: a) financially
feasible; and b) will meet its stated policy objectives. The Study results do not necessarily apply to one or
more of the Tri-County local governments joining an existing CCA program.
This Study evaluates the financial and economic viability of a CCA by:
xForecasting the CCA electricity demand requirements (load) and potential customers by class;
xEstimating the costs of procuring the necessary electricity supply; and
xProjecting the costs of starting up and administering a CCA program.
The Study also enumerates the potential benefits and associated risks of a CCA program and discusses
implementation requirements.
C. Energy Procurement and Study Scenarios
Energy procurement is complex and the total cost
of procurement is subject to changes in both market
conditions (price) and consumption (volume). Load
Serving Entities (LSEs)—IOUs, CCAs, and Electricity
Service Providers (ESPs)—must manage both load
forecasting and energy procurement with a robust
risk management approach to account for the
dynamic and volatile nature of power markets and
load.
Given the uniqueness of multiple municipalities
partnering to commission this feasibility Study, the Advisory Working Group established eight geographic
participation scenarios. These eight scenarios were selected to explore the feasibility of different sizes and
configurations for the CCA program and the potential effect of customer demographics. Although the
entire Tri-County Region may not ultimately pursue CCA, certain jurisdictions may decide to move
forward with CCA. The eight participation scenarios defined for this Study are:
1.All Tri-County Region
2.AWG Jurisdictions
3.All San Luis Obispo County
4.Unincorporated San Luis Obispo County
5.All Santa Barbara County
6.Unincorporated Santa Barbara County
7.All Ventura County
8.City of Santa Barbara
In addition to the eight participation scenarios, three renewable energy content scenarios were
considered. All scenarios include a customer option to opt-up to a 100% renewable energy product. For
the purposes of this Study, 2% of customers were assumed to opt-up to the 100% renewable option. The
three renewable energy content scenarios are as follows:
Throughout the report, the term LSE is used to
provide illustrative trends that are affecting the
Tri-County Region as a whole, regardless of
whether the electricity is provided by an IOU,
ESP or CCA program. For our purposes, a CCA
program is a subset of the more broad LSE
term.
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Executive Summary
Technical Feasibility Study Central Coast Region
on Community Choice Aggregation August 2017
ES-3
xRPS Equivalent: This scenario assumes that Central Coast Power would offer its base electricity
product to all customers starting at 33% renewable content in 2020 and ramping up to 50%
renewable content by 2030 in alignment with the California minimum Renewable Portfolio
Standard (RPS).2
xMiddle of the Road: This scenario assumes that Central Coast Power would offer its base
electricity product to all customers using 50% renewable content for the entire Study period.
xAggressive: This scenario assumes that Central Coast Power would offer its base electricity
product to all customers using 75% renewable content for the entire Study period.
This Study evaluates an eleven-year period from 2020 to 2030, although a potential CCA program could
begin earlier than 2020. Figure ES-1 illustrates how the renewable energy content in the RPS Equivalent
scenario grows over time, and in the other two scenarios remains constant across the Study period. These
three scenarios were chosen to illustrate the relative differences in cost given different levels of renewable
supply content. Actual CCA implementation may choose to follow a progression of increasing renewable
generation over that period based on cost competitiveness. For example, Central Coast Power CCA may
launch in 2020 with 50% renewable content and progress to 75% renewable content by 2030, assuming it
can do so at a cost advantage to the IOUs.
To enhance report readability, the main body of this report presents results for the AWG Jurisdictions
participation scenario, for the RPS Equivalent, Middle of the Road, and Aggressive renewable energy
content scenarios. Detailed results for the other seven participation scenarios are provided in Appendices
C, and E through J.
Figure ES-1 Renewable Energy Content Modeled in this Study
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The fundamental operational role of a CCA is to forecast
customer electricity needs and procure energy and
associated energy related services. Power procurement
consists of forecasting and risk management tasks. Power
procurement planning and day-to-day decision making rely
heavily on short-term and long-term forecasts of consumer
demand for power. The procurement function must also
evaluate and assess the inherent risks associated with demand forecasting and develop appropriate risk
mitigation strategies. Though no one can predict future energy demand with 100% certainty, logical, data-
driven, industry-standard methodologies to forecasting are available to provide a realistic outlook of
energy demand under a variety of future scenarios. Brief discussions covering the forecasts for customer
power demand and power procurement costs are provided in the following segments.
D. Customer Demand
As shown in Figure ES-2, Ventura County is the largest
electricity consumer of the three counties considered in
this Study, followed by Santa Barbara and San Luis Obispo
Counties. Collectively, customers in the incorporated
cities in San Luis Obispo and Ventura Counties consume
more electricity than customers in the unincorporated
county. The reverse is true in Santa Barbara County.
The fundamental operational role of a
CCA is to forecast customer electricity
needs and procure energy and
associated energy related services.
Energy is measured in several units
throughout this study: kilowatt-hours
(kWh), which is the unit used on customer
bills; megawatt-hours (MWh), where 1
MWh equals 1,000 kWh; and gigawatt-
hours (GWh), where 1 GWh equals
1,000 MWh or 1,000,000 kWh.
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Figure ES-2 Annual Demand in Gigawatt-hours (GWh) by County
Figure ES-3 shows the annual electricity consumption for each of the Study’s eight geographic participation
scenarios. The consumption and number of accounts generally mirror each other, with the exception of
unincorporated San Luis Obispo and Santa Barbara Counties.
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Figure ES-3 Annual Demand in GWh for Each Geographic Participation Scenario
Electricity consumption is forecasted to grow moderately over the Study period, however continued
customer adoption of distributed generation (DG) solar photovoltaic (PV) is expected to offset this
growth. DG PV reduces the amount of energy that needs to be provided by the potential CCA. Figure ES
4 illustrates the growth of customer-owned DG PV since the year 2000 and illustrates a forecast for
additional DG PV capacity if this trend continues. Table ES 1 lists the forecasted annual energy
consumption, annual DG PV generation, and the annual net load (consumption-generation) served by the
potential CCA for the AWG Jurisdictions participation scenario. In summary, a Central Coast Power CCA
would likely sell less electricity each year given customer DG PV adoption.
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Figure ES-4 California Solar Initiative Incentivized Customer-Owned Solar Photovoltaic in the Region with
2030 Forecast
Table ES-1 Load, Distributed Generation, and Net Load Forecast, AWG Jurisdictions Participation
Scenarios
Year Annual Energy
Consumption
(MWh)
Annual DG Generation
(MWh)
Annual Net Load
Served by LSE (MWh)
2020 6,698,164 164,987 6,533,177
2021 6,735,965 202,979 6,532,985
2022 6,777,276 244,414 6,532,862
2023 6,811,982 287,988 6,523,995
2024 6,868,761 335,074 6,533,686
2025 6,888,329 381,954 6,506,375
2026 6,930,669 431,948 6,498,721
2027 6,971,608 483,660 6,487,948
2028 7,026,296 538,288 6,488,008
2029 7,047,280 592,489 6,454,791
2030 7,085,173 650,280 6,434,893
Forecast
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As explained in Section II Technical and Financial Analysis, the increasing amount of DG PV also creates
more volatile customer load due to the variable nature of its energy output. Solar generation depends on
solar irradiance, which can fluctuate significantly over very short periods of time (within seconds) due to
weather patterns and resulting cloud cover.
E. Power Procurement Cost Forecasts
CCAs, like all LSEs, satisfy customer demand for electricity by managing a power supply portfolio, a
collection of supply-side resources. For the purposes of this Study, a power supply portfolio is designed
to acquire two distinct commodities: energy, typically measured in MWh, and resource adequacy capacity,
typically measured in megawatts (MW). Energy resources include natural gas generation, RPS compliant
renewable energy generation, energy storage, and California Independent System Operator (CAISO) day-
ahead and real-time market purchases. Resource adequacy is used to make sure there is sufficient capacity
to produce electricity during peak demand periods.
This Study projects decreasing costs for all energy resources considered, except for energy procured in
the CAISO markets, where average pricing remains constant and large fluctuations are due to variability
in renewable generation for both utility scale resources and customer-owned DG PV. Actual CAISO real-
time market prices from January 2014 through October 2016 for the Tri-County Region average around
$36 per megawatt-hour (MWh). However, the range of prices around that mean varied greatly, reaching
a high of $4,377 per MWh during shortages of supply relative to demand, and a low of -$1,277 per MWh—
meaning that CAISO will pay participants to take power—when supply exceeds demand. The high level
of DG PV penetration in California, combined with solar and wind energy’s variable nature, accounts for
much of this market volatility. This Study has modeled renewable resource variability and the CCA’s
associated exposure to CAISO market prices.
Table ES-2 presents the Study forecast for the average annual power procurement cost for the AWG
Jurisdictions participation scenario for the three renewable supply scenarios. As can be seen in these data,
the average cost of power procurement for the CCA rises as more renewable energy content is added
because renewable generation is forecast to be more expensive than alternative non-renewable resources,
despite a slight downward trend in renewable energy prices.
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Table ES-2 Average Annual Power Procurement Costs ($ per MWh), AWG Jurisdictions Scenarios
Year RPS Equivalent Middle of the Road
(50% Renewable)
Aggressive (75%
Renewable)
2020 $67 $74 $87
2021 $66 $74 $85
2022 $66 $74 $85
2023 $66 $72 $85
2024 $66 $72 $84
2025 $66 $71 $84
2026 $67 $70 $84
2027 $68 $70 $84
2028 $68 $69 $83
2029 $68 $69 $82
2030 $68 $69 $81
The total energy requirements served by various power supply options, including PPAs, the CAISO day-
ahead and real-time markets, among others, change depending on scenario, however, the price of each
option does not. This is what would be expected in actuality, as the amount of energy procured by the
CCA would have little to no bearing on the prevailing PPA and market prices on a long-term basis.
In support of the power procurement cost forecast, data from the U.S. Department of Energy’s Energy
Information Administration’s Annual Energy Outlook 2017,3 which provides estimates of renewable
generation costs on a regional basis, were examined. This data is used by utilities, energy consultancies,
and others to help understand current and future energy-related pricing trends and is based on real-world
project construction, financing, ownership, and ongoing operations and maintenance costs. Table ES-3
shows the various costing components for a new solar photovoltaic project and a new wind project,
assuming they are installed on sites where there is no need to work within the constraints imposed by
existing buildings or infrastructure (greenfield projects). This cost data supports all-in pricing at around
$67 per MWh for wind resources and $101 per MWh for solar PV resources.
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Table ES-3 Energy Information Administration Cost Estimates for New Wind and Solar Energy Resources
in California
Description
Wind Farm –
Onshore
Utility-Scale
Photovoltaic
Configuration
100 MW; 56 turbines
at 1.79 MW each
20 MW, Alternating
Current, Fixed Tilt
Installation Type Greenfield Installation
Greenfield
Installation
Total Capacity (MW) 100 20
Capacity Factor (National Average,
Jan. 2016-Apr. 2017) 36.59% 26.76%
Total Project Cost, California-Mexico Region ($ per kW-installed) $2,010 $2,578
Total Project Cost, California-Mexico Region ($) $201,000,000 $51,560,000
Variable O&M ($ per MWh) $ - $ -
Fixed O&M ($ per kW-year) $46.71 $21.66
Weighted Average Cost of Capital (%) 5.50% 5.50%
Debt Finance Term (years) 20 20
Financing Costs per Year ($) $16,819,545 $4,314,506
Fixed O&M Costs per Year ($) $4,671,000 $433,200
Total Project Costs per Year ($) $21,490,545 $4,747,706
Energy Production per Year (MWh) 320,528 46,884
Per Unit Cost ($ per MWh) $67.05 $101.27
Like all energy price forecasts, the one used within the Study—just as those used within other CCA
feasibility studies—may or may not accurately reflect actual future conditions, which are unknown and
not predictable. Various market drivers may change resulting in different outcomes from those assumed
here. The forecast used herein is a reasonable estimate for the purposes of analyzing the feasibility of
CCA within the Tri-County Region, but no warranties as to the accuracy of forecast prices for power
purchase agreements or CAISO market commodities are implied or should be inferred. For example,
large hydroelectric generation resources owned and managed by the IOUs were not significantly utilized
during the recent drought years through 2016. Rainfall in the winter of 2016-2017 filled the hydroelectric
reservoirs, enabling a low cost, carbon-neutral generation resource for the IOUs. Generally speaking, all
other things being equal, increased hydro production will lower IOU generation revenue requirements
and could have a dampening effect on IOU rates, potentially lowering the rates required for the CCA to
be competitive.
F. Greenhouse Gas Emissions Impact
This Study also evaluated the greenhouse gas (GHG) emissions impact of the renewable energy content
of the CCA’s portfolio—including the 100% renewable energy product assumed to be chosen by 2% of
customers—relative to that of the incumbent IOUs, Southern California Edison (SCE) and Pacific Gas and
Electric (PG&E). For the purposes of this comparison, the IOU Base Case assumes the IOUs will progress
from currently published 2020 RPS levels of renewable generation linearly to the 50% RPS goal in 2030.
Although each IOU may elect to exceed RPS requirements as they have in recent history and relative to
2020 requirements, for example PG&E submitted a joint proposal to decommission the El Diablo nuclear
power station and voluntarily reach 55% RPS by 2031,4 neither IOU has publicly stated firm plans to
exceed RPS targets. California is currently considering Senate Bill 100, which would increase the renewable
energy mandate to: 50% by December 31, 2026 and 60% by December 31, 2030.5 Figure ES-5 summarizes
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the GHG impact analysis results for the IOU renewable scenario and three CCA renewable scenarios.
Figure ES-5 GHG Emissions Impact Analysis, AWG Jurisdictions Participation Scenarios
Large hydroelectric generation resources owned and managed by the IOUs do not count towards RPS
goals and were also not significantly utilized during the recent drought years through 2016. Rainfall in the
winter of 2016-2017 filled the hydroelectric reservoirs enabling a low cost, carbon-neutral generation
component for the IOUs. In addition, the pumped hydro energy storage that can balance the variability of
other sources of renewable generation also relies on rain to fill reservoirs. Future rainfall and drought
conditions are unknown, and therefore the future utilization of large hydroelectric generation by the IOUs
cannot be predicted. Additional use of hydro resources or increases to the IOU RPS content would result
in lower GHG emissions for the IOUs, potentially decreasing the additional GHG reduction benefit of the
CCA program.
G. Cost of Service and Financial Pro Forma Analysis
The cost of service analysis relied on traditional utility ratemaking principles and followed an industry
standard methodology for creation of a financial pro forma to forecast the future economic and financial
performance of the CCA program. The Study assessed financial feasibility in terms of the ability of the
CCA program to realistically deliver competitive costs for customers while paying its substantial start-up
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and agency formation costs and ongoing operating expenses.
The first step in the cost of service analysis was developing
the projected CCA program revenue requirement: the
amount of revenue required to cover the costs of the CCA
program, including all operating and non-operating expenses,
debt-service payments, a contingency allotment, a working
capital reserve, and a rate stabilization fund. The revenue
requirement was based on a comprehensive accounting of all
pertinent costs and projections of customer participation;
assumptions and input development are described later in this
report. Cost assumptions relied on historical publicly-available
information, power cost forecasts conducted for this Study,
data provided by PG&E and SCE, and subject matter expertise
gained working with a host of public utilities and similar
organizations. Table ES-4 summarizes the CCA program Test
Year revenue requirements for the AWG Jurisdictions
participation scenarios
Table ES-4 Test Year CCA Revenue Requirements, AWG Jurisdictions Participation Scenarios
CCA program customer participation was assumed to be constant for each participation scenario across
the three renewable energy content scenarios examined. For all scenarios, an opt-out rate of 15% was
used for all rate classes for all years, meaning that 15% of bundled customers by load in each rate class
were assumed to opt out of the CCA program.6 This 15% opt-out rate is in addition to an estimated
23.5% of AWG Jurisdictions scenario load that represents typically large commercial customers who are
RPS Equivalent
Middle of the
Road Aggressive
REVENUE REQUIREMENT
Baseload
Total Operating Expenses Excluding Power Costs 10,146,683$ 10,256,373$ 10,482,215$
Total Non-Operating Expenses 16,959,517 18,158,147 20,239,969
Power Costs 461,419,035 489,933,855 549,930,521
Contingency/Rate Stabilization Fund 54,171,111$ 57,535,423$ 64,613,615$
BASELOAD REVENUE REQUIREMENT 542,696,345$ 575,883,798$ 645,266,320$
Opt-up to 100% RPS
Total Operating Expenses Excluding Power Costs 207,075$ 209,314$ 213,923$
Total Non-Operating Expenses 346,113 370,574 413,061
Power Costs 12,617,576 12,617,576 12,617,576
Contingency/Rate Stabilization Fund 1,105,533$ 1,174,192$ 1,318,645$
OPT-UP TO 100% RPS REVENUE REQUIREMENT 14,276,297$ 14,371,657$ 14,563,205$
TOTAL REVENUE REQUIREMENT 556,972,642$ 590,255,454$ 659,829,525$
AWG Jurisdictions Participation Scenarios
Description
The Test Year is the future
annualized period for which operating
costs are analyzed and rate proxies
established. The Study Test Year is
based on forecasts of CCA operating
conditions for years 2022, 2023, and
2024 and represents a twelve-month
period of normalized operations
selected to evaluate the cost of
service for each customer class and
the adequacy of rate proxies to
provide sufficient revenue.
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likely to remain with their existing Direct Access (DA) ESP. Other CCA feasibility studies have supported
the assertion that opt-out rates, within a reasonable range, have little bearing on CCA feasibility. Figure
ES-6 and Figure ES-7 summarize Test Year customer accounts by rate class and Test Year customer usage
by rate class for the AWG Jurisdictions participation scenarios, respectively. Average CCA Test Year
customer profiles for the three AWG Jurisdictions participation scenarios are provided in Table ES-5.
Figure ES-6 Test Year CCA Customer Accounts, AWG Jurisdictions Participation Scenarios
0
50
100
150
200
250
300
350
400
PG&E Customers, AWG
Jurisdictions Scenarios
SCE Customers, AWG Jurisdictions
Scenarios
Total CCA Customers, AWG
Jurisdictions Scenarios
Thousands Test Year Customer Accounts by Rate Class Traffic Control
Residential CARE
Residential
Lighting
Small Comm
<200kW
Med Comm
200<500kW
Large Comm
500<1,000kW
Very Large Comm
>1,000kW
Agriculture
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Figure ES-7 Test Year CCA Customer Usage, AWG Jurisdictions Participation Scenarios
0
1,000
2,000
3,000
4,000
5,000
6,000
PG&E Customers, AWG
Jurisdictions Scenarios
SCE Customers, AWG
Jurisdictions Scenarios
Total CCA Customers, AWG
Jurisdictions Scenarios
GWH Test Year Customer Energy Usage by Rate Class
Traffic Control
Residential CARE
Residential
Lighting
Small Comm
<200kW
Med Comm
200<500kW
Large Comm
500<1,000kW
Very Large Comm
>1,000kW
Agriculture
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Table ES-5 Test Year CCA Customer Accounts and Usage, AWG Jurisdictions Participation Scenarios
While rate design was not part of the Study scope, based on the detailed pro forma analysis, CCA rate
proxies by customer class by IOU jurisdiction were developed. Rate proxies represent the amount of
revenue by customer class required to make the CCA financially solvent, based on the Test Year. Based
on this analysis, CCA baseline customers would have all-in rate proxies that are higher than both PG&E
and SCE for most rate classes for all participation and renewable energy content scenarios examined.
Table ES-6 through Table ES-8 present the generation rate differences between the CCA and PG&E and
SCE for the AWG Jurisdictions participation scenarios for the RPS Equivalent, Middle of the Road, and
Aggressive renewable energy content scenarios. The generation portion of customers’ bills is the only
cost component for which the CCA competes with the incumbent utilities. Customer billing and delivery
charges (transmission and distribution) are the same for both CCA and IOU bundled customers.
Generation rate comparisons are provided for the first five years of the Study period by rate class.7 The
Accounts Annual Load
Average Monthly
Load
Line Description (MWh) (kWh/Account)
1 BASELOAD
2 Agriculture 6,454 490,772 6,337
3 Very Large Comm >1,000kW 13 718,495 4,673,350
4 Large Comm 500<1,000kW 405 441,022 90,742
5 Med Comm 200<500kW 576 297,829 43,094
6 Small Comm <200kW 40,034 1,124,051 2,340
7 Lighting 1,757 26,357 1,250
8 Residential 256,812 1,709,325 555
9 Residential CARE 22,929 124,036 451
10 Traffic Control 841 2,811 278
11 TOTAL BASELOAD 329,821 4,934,699 1,247
12 OPT-UP TO 100% RPS (MWH)
13 Agriculture - - -
14 Very Large Comm >1,000kW - - -
15 Large Comm 500<1,000kW 9 10,071 90,742
16 Med Comm 200<500kW 29 15,106 43,094
17 Small Comm <200kW 538 15,106 2,340
18 Lighting - - -
19 Residential 9,078 60,425 555
20 Residential CARE - - -
21 Traffic Control - - -
22 TOTAL OPT-UP TO 100% RPS 9,655 100,708 869
23 TOTAL CCA 339,476 5,035,407 1,236
CUSTOMERS OPTING UP TO 100% RENEWABLES Portion of Opt Up Portion of Total CCA
24 Agriculture 0%0.00%
25 Very Large Comm >1,000kW 0%0.00%
26 Large Comm 500<1,000kW 10%0.20%
27 Med Comm 200<500kW 15%0.30%
28 Small Comm <200kW 15%0.30%
29 Lighting 0%0.00%
30 Residential 60%1.20%
31 Residential CARE 0%0.00%
32 Traffic Control 0%0.00%
33 TOTAL 100%2.00%
Test Year
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total anticipated bill impact to residential customers in 2020 is included in Table ES 9.
Table ES-6 Generation Rate Comparisons for PG&E, SCE, and CCA, AWG Jurisdictions RPS Equivalent
Renewable Energy Content Scenario
CCA
Rates
PG&E
Rates
CCA
Rates
PG&E
Rates
CCA
Rates
PG&E
Rates
CCA
Rates
PG&E
Rates
CCA
Rates
PG&E
Rates
Agriculture 0.1175 0.0742 0.1175 0.0753 0.1175 0.0749 0.1175 0.0747 0.1175 0.0754
Commercial/Industrial Small <200kW 0.1183 0.1049 0.1183 0.1065 0.1183 0.1059 0.1183 0.1055 0.1183 0.1065
Commercial/Industrial Medium 200<500 kW 0.1190 0.1097 0.1190 0.1113 0.1190 0.1107 0.1190 0.1103 0.1190 0.1114
Commercial/Industrial Large 500<1000 kW 0.1145 0.1107 0.1145 0.1124 0.1145 0.1118 0.1145 0.1114 0.1145 0.1124
Residential 0.1220 0.1003 0.1220 0.1018 0.1220 0.1013 0.1220 0.1009 0.1220 0.1018
Residential CARE 0.1152 0.0936 0.1152 0.0950 0.1152 0.0945 0.1152 0.0941 0.1152 0.0950
Residential Solar Choice 0.1920 0.1265 0.1920 0.1284 0.1920 0.1277 0.1920 0.1272 0.1920 0.1284
Weighted Average 0.1193 0.0961 0.1193 0.0975 0.1193 0.0970 0.1193 0.0967 0.1193 0.0976
CCA Rate Premium/ (CCA Savings)24.10%22.27%22.92%23.37%22.22%
Rate Class
CCA
Rates SCE Rates
CCA
Rates SCE Rates
CCA
Rates SCE Rates
CCA
Rates SCE Rates
CCA
Rates SCE Rates
Agriculture 0.1050 0.0543 0.1050 0.0551 0.1050 0.0548 0.1050 0.0547 0.1050 0.0552
Commercial/Industrial Small <200kW 0.1072 0.0922 0.1072 0.0936 0.1072 0.0931 0.1072 0.0927 0.1072 0.0936
Commercial/Industrial Medium 200<500 kW 0.1064 0.0837 0.1064 0.0850 0.1064 0.0845 0.1064 0.0842 0.1064 0.0850
Commercial/Industrial Large 500<1000 kW 0.1057 0.0777 0.1057 0.0789 0.1057 0.0785 0.1057 0.0782 0.1057 0.0789
Residential 0.0999 0.0712 0.0999 0.0723 0.0999 0.0719 0.0999 0.0716 0.0999 0.0723
Residential CARE 0.0924 0.0635 0.0924 0.0645 0.0924 0.0641 0.0924 0.0639 0.0924 0.0645
Residential Green Tariff 0.1199 0.1127 0.1199 0.1144 0.1199 0.1138 0.1199 0.1134 0.1199 0.1144
Weighted Average 0.1034 0.0776 0.1034 0.0788 0.1034 0.0784 0.1034 0.0781 0.1034 0.0788
CCA Rate Premium/ (CCA Savings)33.23%31.26%31.97%32.44%31.21%
2026
Rate Class
2022 2023 2024 2025
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Table ES-7 Generation Rate Comparisons for PG&E, SCE, and CCA, AWG Jurisdictions Middle of the Road
Renewable Energy Content Scenario
Table ES-8 Generation Rate Comparisons for PG&E, SCE, and CCA, AWG Jurisdictions Aggressive
Renewable Energy Content Scenario
CCA
Rates
PG&E
Rates
CCA
Rates
PG&E
Rates
CCA
Rates
PG&E
Rates
CCA
Rates
PG&E
Rates
CCA
Rates
PG&E
Rates
Agriculture 0.1242 0.0742 0.1242 0.0753 0.1242 0.0749 0.1242 0.0747 0.1242 0.0754
Commercial/Industrial Small <200kW 0.1250 0.1049 0.1250 0.1065 0.1250 0.1059 0.1250 0.1055 0.1250 0.1065
Commercial/Industrial Medium 200<500 kW 0.1257 0.1097 0.1257 0.1113 0.1257 0.1107 0.1257 0.1103 0.1257 0.1114
Commercial/Industrial Large 500<1000 kW 0.1212 0.1107 0.1212 0.1124 0.1212 0.1118 0.1212 0.1114 0.1212 0.1124
Residential 0.1287 0.1003 0.1287 0.1018 0.1287 0.1013 0.1287 0.1009 0.1287 0.1018
Residential CARE 0.1219 0.0936 0.1219 0.0950 0.1219 0.0945 0.1219 0.0941 0.1219 0.0950
Residential Solar Choice 0.1987 0.1265 0.1987 0.1284 0.1987 0.1277 0.1987 0.1272 0.1987 0.1284
Weighted Average 0.1260 0.0961 0.1260 0.0975 0.1260 0.0970 0.1260 0.0967 0.1260 0.0976
CCA Rate Premium/ (CCA Savings)31.06%29.13%29.82%30.29%29.08%
Rate Class
CCA
Rates SCE Rates
CCA
Rates SCE Rates
CCA
Rates SCE Rates
CCA
Rates SCE Rates
CCA
Rates SCE Rates
Agriculture 0.1117 0.0543 0.1117 0.0551 0.1117 0.0548 0.1117 0.0547 0.1117 0.0552
Commercial/Industrial Small <200kW 0.1139 0.0922 0.1139 0.0936 0.1139 0.0931 0.1139 0.0927 0.1139 0.0936
Commercial/Industrial Medium 200<500 kW 0.1132 0.0837 0.1132 0.0850 0.1132 0.0845 0.1132 0.0842 0.1132 0.0850
Commercial/Industrial Large 500<1000 kW 0.1124 0.0777 0.1124 0.0789 0.1124 0.0785 0.1124 0.0782 0.1124 0.0789
Residential 0.1066 0.0712 0.1066 0.0723 0.1066 0.0719 0.1066 0.0716 0.1066 0.0723
Residential CARE 0.0991 0.0635 0.0991 0.0645 0.0991 0.0641 0.0991 0.0639 0.0991 0.0645
Residential Green Tariff 0.1266 0.1127 0.1266 0.1144 0.1266 0.1138 0.1266 0.1134 0.1266 0.1144
Weighted Average 0.1102 0.0776 0.1102 0.0788 0.1102 0.0784 0.1102 0.0781 0.1102 0.0788
CCA Rate Premium/ (CCA Savings)41.87%39.78%40.53%41.04%39.72%
2026
Rate Class
2022 2023 2024 2025
CCA
Rates
PG&E
Rates
CCA
Rates
PG&E
Rates
CCA
Rates
PG&E
Rates
CCA
Rates
PG&E
Rates
CCA
Rates
PG&E
Rates
Agriculture 0.1382 0.0742 0.1382 0.0753 0.1382 0.0749 0.1382 0.0747 0.1382 0.0754
Commercial/Industrial Small <200kW 0.1390 0.1049 0.1390 0.1065 0.1390 0.1059 0.1390 0.1055 0.1390 0.1065
Commercial/Industrial Medium 200<500 kW 0.1397 0.1097 0.1397 0.1113 0.1397 0.1107 0.1397 0.1103 0.1397 0.1114
Commercial/Industrial Large 500<1000 kW 0.1352 0.1107 0.1352 0.1124 0.1352 0.1118 0.1352 0.1114 0.1352 0.1124
Residential 0.1426 0.1003 0.1426 0.1018 0.1426 0.1013 0.1426 0.1009 0.1426 0.1018
Residential CARE 0.1359 0.0936 0.1359 0.0950 0.1359 0.0945 0.1359 0.0941 0.1359 0.0950
Residential Solar Choice 0.2026 0.1265 0.2026 0.1284 0.2026 0.1277 0.2026 0.1272 0.2026 0.1284
Weighted Average 0.1399 0.0961 0.1399 0.0975 0.1399 0.0970 0.1399 0.0967 0.1399 0.0976
CCA Rate Premium/ (CCA Savings)45.56%43.41%44.18%44.70%43.35%
Rate Class
CCA
Rates SCE Rates
CCA
Rates SCE Rates
CCA
Rates SCE Rates
CCA
Rates SCE Rates
CCA
Rates SCE Rates
Agriculture 0.1258 0.0543 0.1258 0.0551 0.1258 0.0548 0.1258 0.0547 0.1258 0.0552
Commercial/Industrial Small <200kW 0.1280 0.0922 0.1280 0.0936 0.1280 0.0931 0.1280 0.0927 0.1280 0.0936
Commercial/Industrial Medium 200<500 kW 0.1272 0.0837 0.1272 0.0850 0.1272 0.0845 0.1272 0.0842 0.1272 0.0850
Commercial/Industrial Large 500<1000 kW 0.1265 0.0777 0.1265 0.0789 0.1265 0.0785 0.1265 0.0782 0.1265 0.0789
Residential 0.1208 0.0712 0.1208 0.0723 0.1208 0.0719 0.1208 0.0716 0.1208 0.0723
Residential CARE 0.1132 0.0635 0.1132 0.0645 0.1132 0.0641 0.1132 0.0639 0.1132 0.0645
Residential Green Tariff 0.1308 0.1127 0.1308 0.1144 0.1308 0.1138 0.1308 0.1134 0.1308 0.1144
Weighted Average 0.1242 0.0776 0.1242 0.0788 0.1242 0.0784 0.1242 0.0781 0.1242 0.0788
CCA Rate Premium/ (CCA Savings)59.94%57.58%58.43%59.00%57.52%
2026
Rate Class
2022 2023 2024 2025
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Figure ES-8 and Figure ES-9 graphically depict the difference in generation rates between the CCA and
PG&E and the CCA and SCE, respectively, for the AWG Jurisdictions scenario for the three renewable
content scenarios.
Figure ES-8 CCA and PG&E Generation Rate Comparison Summary for AWG Jurisdictions Participation
Scenarios
0.0000 0.0500 0.1000 0.1500 0.2000
CCA Rates
PG&E Rates
CCA Rates
PG&E Rates
CCA Rates
PG&E Rates
AWG RPS Equivalent AWG Middle of The Road AWG Aggressive
2022-2026 Average Base Generation Rates ($/kWh)
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Figure ES-9 CCA and SCE Generation Rate Comparison Summary for AWG Jurisdictions Participation
Scenarios
Table ES-9 shows the percentage change in average generation rates and the monetary change in monthly
Residential bills for CCA customers versus PG&E and SCE, and the percent change in GHG emissions for
all rate classes. This data is presented for year 2020. The previous Tables ES-6 through ES-8 present
weighted average rate impacts across all seven customer classes examined for years 2022-2026.
0.0000 0.0500 0.1000 0.1500 0.2000
CCA Rates
SCE Rates
CCA Rates
SCE Rates
CCA Rates
SCE Rates
AWG RPS Equivalent AWG Middle of The Road AWG Aggressive
2022-2026 Average Base Generation Rates ($/kWh)
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Table ES-9 Summary of Forecasted Residential Class Outcomes by Renewable Energy Content Scenario,
AWG Jurisdictions Participation Scenarios, Year 2020
Participation
Scenario
Included
Jurisdictions
Renewable
Energy
Content
Pacific Gas & Electric Southern California Edison
Proportional
GHG
Comparison
Generation
Rate
Comparison
(% Increase/
Decrease for
CCA
Customers)
Monthly Bill
Comparison
($ Increase/
Decrease for
CCA
Customers)
Generation
Rate
Comparison
(% Increase/
Decrease for
CCA
Customers)
Monthly Bill
Comparison
($ Increase/
Decrease for
CCA
Customers)
All Tri-County
Region
All San Luis
Obispo County
All Santa Barbara
County
All Ventura
County
RPS
Equivalent
22% $11.25 41% $14.55 6%
50% 29% $14.62 51% $17.93 -9%
75% 43% $21.72 71% $25.05 -55%
Advisory Working
Group
Jurisdictions
San Luis Obispo
County
Santa Barbara
County
Carpinteria
Santa Barbara
Ventura County
Camarillo
Moorpark
Ojai
Simi Valley
Thousand Oaks
Ventura
RPS
Equivalent
22% $12.21 41% $16.08 6%
50% 29% $15.92 50% $19.79 -9%
75% 43% $23.68 70% $27.64 -55%
All San Luis
Obispo County
Arroyo Grande
Atascadero
Grover Beach
Morro Bay
Paso Robles
Pismo Beach
San Luis Obispo
Unincorporated
SLO County
RPS
Equivalent
29% $12.07 7%
50% 36% $14.89 -9%
75% 51% $20.77 -54%
Unincorporated
San Luis Obispo
County
Unincorporated
SLO County
RPS
Equivalent
35% $15.70 7%
50% 42% $18.77 -9%
75% 56% $25.21 -54%
All Santa Barbara
County
Buellton
Carpinteria
Goleta
Guadalupe
Santa Barbara
Santa Maria
Solvang
Unincorporated
Santa Barbara
County
RPS
Equivalent
24% $11.15 45% $14.53 7%
50% 31% $14.27 55% $17.69 -9%
75% 45% $20.78 75% $24.22 -55%
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Participation
Scenario
Included
Jurisdictions
Renewable
Energy
Content
Pacific Gas & Electric Southern California Edison
Proportional
GHG
Comparison
Generation
Rate
Comparison
(% Increase/
Decrease for
CCA
Customers)
Monthly Bill
Comparison
($ Increase/
Decrease for
CCA
Customers)
Generation
Rate
Comparison
(% Increase/
Decrease for
CCA
Customers)
Monthly Bill
Comparison
($ Increase/
Decrease for
CCA
Customers)
Unincorporated
Santa Barbara
County
Unincorporated
Santa Barbara
County
RPS
Equivalent
26% $15.08 47% $19.29 7%
50% 33% $18.97 56% $23.23 -9%
75% 47% $27.11 76% $31.44 -54%
All Ventura
County
Camarillo
Fillmore
Moorpark
Ojai
Oxnard
Port Hueneme
Santa Paula
Simi Valley
Thousand Oaks
Ventura
Unincorporated
Ventura County
RPS
Equivalent
41% $15.87 6%
50% 50% $19.54 -10%
75% 70% $27.35 -55%
City of Santa
Barbara Santa Barbara
RPS
Equivalent
69% $17.91 6%
50% 78% $20.42 -10%
75% 100% $25.98 -55%
Table ES-10 shows annual operating results for the AWG Jurisdictions participation scenario for the RPS
Equivalent renewable energy content scenario. Net operating margins are negative for all years of the
Study period; meaning revenues are not sufficient to cover total operating and non-operating expenses
plus the contingency and rate stabilization fund. In the initial years of the study period, this is due to the
phasing in of customers and a lag in revenues versus expenditures. In later years, this revenue insufficiency
is caused by rates remaining unchanged even though the CCA experiences an increase in operating costs.
Rates were not increased because the CCA rate proxies were not competitive with IOU rates from the
onset of the Study through 2026. Raising rates would make them less competitive. Although working
capital initially is adequate, given the current debt assumptions that include a long-term bond financing in
year 2020 of $288 million, starting in year 2024, working capital declines below targeted amounts and
continues to decrease. The combination of increasingly negative net margins and a shortage of working
capital would indicate the need for a rate increase around year 2026, again which would further harm the
CCA program’s rate competitiveness relative to the IOUs. Table ES-11 presents this data for the AWG
Jurisdictions Middle of the Road renewable energy content scenario and Table ES-12 presents this data
for the AWG Jurisdictions Aggressive renewable energy content scenario. Generally speaking, results for
these alternate renewable energy content scenarios are similar to the RPS Equivalent scenario, although
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net margins and working capital deficiencies are better due to the higher rate proxies, which are set at
the beginning and remain constant throughout the study period. Rate increases would still be required,
but around the 2028 timeframe.
Table ES-10 CCA Annual Operating Results, AWG Jurisdictions RPS Equivalent Scenario
Table ES-11 CCA Annual Operating Results, AWG Jurisdictions Middle of the Road Scenario
Year
Operating
Revenues
($000s)
Total Operating
Expenses Plus
Contingency/ Rate
Stabilization Fund
($000s)
Non-Operating
Revenues/
(Expenses)
($000s)
Debt Service
($000s)
Net Margin1
($000s)
Working Capital
Fund ($000s)
Working Capital
Target ($000s)
Working Capital
Surplus/
(Deficiency)
($000s)
Working
Capital
Surplus/
(Deficiency)
(%)
a b c d a - b + c - d e f e - f (e/f)-1
2020 110,694 139,109 1,145 11,515 (38,785) 211,653 47,077 164,575 350%
2021 445,293 469,267 2,227 11,515 (33,262) 189,905 159,570 30,335 19%
2022 545,838 533,627 2,046 17,276 (3,018) 186,887 181,993 4,894 3%
2023 556,361 541,735 2,028 17,276 (621) 186,266 184,808 1,458 1%
2024 556,922 543,639 1,925 17,276 (2,067) 184,199 185,916 (1,716) -1%
2025 555,121 543,720 1,985 17,276 (3,889) 180,310 186,453 (6,143) -3%
2026 554,190 551,493 1,903 17,276 (12,676) 167,634 189,470 (21,836) -12%
2027 553,316 556,757 1,721 17,276 (18,995) 148,639 191,885 (43,246) -23%
2028 553,165 566,687 1,396 17,276 (29,401) 119,238 195,934 (76,697) -39%
2029 550,808 569,985 1,183 17,276 (35,270) 83,967 198,148 (114,181) -58%
2030 548,923 581,521 386 17,276 (49,488) 34,479 203,224 (168,745) -83%
NPV of Net Margin:(176,175)
1 Net Margin includes Net Operating Income less Debt Service. The net present value (NPV) of the
Net Margin is determined using a 4% discount rate and is as of Year 2020. The discount rate
is equal to the interest rate on the long-term debt.
Year
Operating
Revenues
($000s)
Total Operating
Expenses Plus
Contingency/ Rate
Stabilization Fund
($000s)
Non-Operating
Revenues/
(Expenses)
($000s)
Debt Service
($000s)
Net Margin1
($000s)
Working Capital
Fund ($000s)
Working Capital
Target ($000s)
Working Capital
Surplus/
(Deficiency)
($000s)
Working
Capital
Surplus/
(Deficiency)
(%)
a b c d a - b + c - d e f e - f (e/f)-1
2020 117,525 150,875 1,235 12,330 (44,445) 223,724 50,583 173,141 342%
2021 472,491 504,655 2,323 12,330 (42,170) 193,883 170,117 23,766 14%
2022 579,072 568,848 2,082 18,499 (6,192) 187,691 192,494 (4,803) -2%
2023 590,222 575,366 2,044 18,499 (1,600) 186,092 194,836 (8,745) -4%
2024 590,817 570,966 1,962 18,499 3,314 189,406 194,067 (4,662) -2%
2025 588,906 566,609 2,098 18,499 5,896 195,302 193,284 2,019 1%
2026 587,918 570,586 2,132 18,499 966 196,268 195,171 1,096 1%
2027 586,991 571,282 2,109 18,499 (681) 195,587 196,227 (640) 0%
2028 586,831 576,506 1,991 18,499 (6,182) 189,405 198,875 (9,470) -5%
2029 584,330 574,978 2,033 18,499 (7,113) 182,292 199,652 (17,361) -9%
2030 582,330 581,643 1,541 18,499 (16,270) 166,022 203,279 (37,257) -18%
NPV of Net Margin:(100,693)
1 Net Margin includes Net Operating Income less Debt Service. The net present value (NPV) of the
Net Margin is determined using a 4% discount rate and is as of Year 2020. The discount rate
is equal to the interest rate on the long-term debt.
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Table ES-12 CCA Annual Operating Results, AWG Jurisdictions Aggressive Scenario
H. Feasibility Outcome Summary
The two primary factors driving forecasted feasibility results
for the CCA include: 1) the competitiveness of CCA rates
against PG&E and SCE rates; and 2) the long-term financial
viability of the enterprise. Under all participation scenarios,
because the rate comparisons show most rate classes paying
more for power supplied by the CCA than from the
incumbent utilities and because the CCA does not maintain
sufficient revenues and working capital throughout the Study
period, the CCA is deemed infeasible Regarding rate
competitiveness, forecasted CCA revenue requirements are
primarily driven by power procurement costs and the Cost
Responsibility Surcharge (CRS), which consists of the
Competitive Transition Charge (CTC), the Department of
Water Resources Bond Charge (DWR-BC), and the Power
Cost Indifference Adjustment (PCIA). Together, these two
components represent 78% of the total of the overall
projected CCA revenue requirement and are thus primary drivers of rate competitiveness against the
two incumbent utilities.
Recent historical movements in the CRS and the allocation of incumbent utility revenue requirements
between generation and delivery (i.e., transmission and distribution) appear to disadvantage the CCA
program. The delivery portion of customers’ bills is paid equally by CCA and bundled IOU customers.
Generally speaking, in recent years the incumbent utilities appear to have been shifting costs from
generation to delivery, as discussed in more detail in Section II.E.1 Feasibility Drivers. The CCA only
competes against the incumbent utilities on generation. Given the assumptions of this Study, SCE and
PG&E forecasted generation rates are not high enough to support CCA feasibility at the forecasted level
of CCA power procurement and operational costs. Regarding long-term financial viability, the CCA would
Year
Operating
Revenues
($000s)
Total Operating
Expenses Plus
Contingency/ Rate
Stabilization Fund
($000s)
Non-Operating
Revenues/
(Expenses)
($000s)
Debt Service
($000s)
Net Margin1
($000s)
Working Capital
Fund ($000s)
Working Capital
Target ($000s)
Working Capital
Surplus/
(Deficiency)
($000s)
Working
Capital
Surplus/
(Deficiency)
(%)
a b c d a - b + c - d e f e - f (e/f)-1
2020 131,724 168,193 1,428 13,746 (48,788) 250,176 55,745 194,431 349%
2021 528,600 562,520 2,607 13,746 (45,059) 218,863 187,370 31,493 17%
2022 647,505 633,619 2,361 20,623 (4,375) 214,487 211,809 2,679 1%
2023 659,933 646,015 2,318 20,623 (4,388) 210,100 215,901 (5,801) -3%
2024 660,598 637,896 2,227 20,623 4,307 214,407 214,025 381 0%
2025 658,462 633,821 2,370 20,623 6,388 220,795 213,325 7,469 4%
2026 657,357 640,581 2,395 20,623 (1,452) 219,343 216,041 3,302 2%
2027 656,320 642,137 2,343 20,623 (4,096) 215,247 217,353 (2,106) -1%
2028 656,142 648,050 2,187 20,623 (10,344) 204,903 220,206 (15,303) -7%
2029 653,345 646,843 2,185 20,623 (11,936) 192,967 221,079 (28,111) -13%
2030 651,109 652,739 1,647 20,623 (20,605) 172,362 224,476 (52,114) -23%
NPV of Net Margin:(120,434)
1 Net Margin includes Net Operating Income less Debt Service. The net present value (NPV) of the
Net Margin is determined using a 4% discount rate and is as of Year 2020. The discount rate
is equal to the interest rate on the long-term debt.
In no participation or renewable
energy content scenario were the
CCA program’s rates competitive with
PG&E or SCE. Given the
underperformance of the CCA in
terms of being rate competitive,
consistently having negative net
margins, and failing to meet the
target for working capital, the CCA
under the assumptions used in the
Study is neither reliably solvent nor
financially feasible.
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need additional rate increases around the year 2026 timeframe to maintain adequate working capital and
increase net margins, further decreasing rate competitiveness.
I. Sensitivity Analysis Results
Upon completion of the Study outcomes for each participation and renewable energy content scenario,
additional sensitivity cases were examined against the AWG Jurisdictions participation scenario to
determine how changes in key inputs affect feasibility outcomes. These sensitivities included: (1) Decreases
in power procurement costs; (2) Increases in IOU rate escalation; and (3) Decreases in staffing costs. Each
sensitivity was examined individually to determine the point at which the CCA could be feasible. As
discussed in more detail in Section II.E.2, Pro Forma Sensitivity Analysis, in order for the CCA to be
feasible:
xPower procurement costs would have to decrease 40% over the Study forecast, or
xPG&E and SCE rates would have to escalate at an additional 4.0% per year above the Study
forecast.
A staffing cost reduction alone is not expected to affect program feasibility. Although not examined as
part of this Study, some combination of changes to the Study assumptions could result in a more feasible
outcome. Like all feasibility studies, assumptions used herein are based on a forecast of future conditions
which may or may not occur. Various market and regulatory drivers may change resulting in different
outcomes from those assumed herein. The assumptions used in the Study are reasonable for the purposes
of analyzing the feasibility of CCA within the Tri-County Region, but no warranties as to the accuracy of
outcomes are implied or should be inferred.
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Abbreviated Technical
Review of Community
Choice Energy
2017
CITY OF SAN LUIS OBISPO AND UNICORPORATED COUNTY OF SAN
LUIS OBISPO
PILOT POWER GROUP | 8910 University Center Lane, Suite 520 San Diego, CA 92122
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Table of Contents
Executive Summary ................................................................................................................................... 2
Model Assumptions .................................................................................................................................. 4
Scenarios ................................................................................................................................................... 4
City of San Luis Obispo .............................................................................................................................. 5
Load Profile and Shape ......................................................................................................................... 6
Scenario 1 – RPS Compliant (Baseline) ................................................................................................. 7
Alternative - RPS Compliant with a Rate Reduction ............................................................................. 8
Simulation Analysis ............................................................................................................................... 9
Scenario 2 – 50% Renewable Energy .................................................................................................. 10
Alternative – 50% Renewable Energy with a Rate Reduction ............................................................ 10
Simulation Analysis ............................................................................................................................. 11
Unincorporated County of San Luis Obispo ............................................................................................ 12
Load Profile and Shape ....................................................................................................................... 13
Scenario 1 – RPS Compliant (Baseline) ............................................................................................... 14
Alternative - RPS Compliant with a Rate Reduction ........................................................................... 15
Simulation Analysis ............................................................................................................................. 16
Scenario 2 – 50% Renewable Energy .................................................................................................. 17
Alternative – 50% Renewable Energy with a Rate Reduction ............................................................ 17
Simulation Analysis ............................................................................................................................. 18
City and Unincorporated County of San Luis Obispo, combined ............................................................ 19
Scenario 1 – RPS Compliant (Baseline) ............................................................................................... 20
Scenario 1 Alternative - RPS Compliant with a Rate Reduction .......................................................... 21
Simulation Analysis ............................................................................................................................. 21
Scenario 2 – 50% Renewable Energy .................................................................................................. 22
Alternative – 50% Renewable Energy with a Rate Reduction ............................................................ 22
Simulation Analysis ............................................................................................................................. 23
Glossary of Terms.................................................................................................................................... 24
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Executive Summary
California Community Choice Energy (CCE) laws and regulations allow cities and counties to procure
electricity for their residents, businesses and municipal facilities. A CCE program provides citizens with an
alternative to a single monopoly electric supplier and local control over a number of key electric
procurement related choices. The local control can result in rate savings, cleaner energy, local economic
development, customized programming, and many other community-based possibilities.
Adopted in 2002, California Assembly Bill 117 (AB 117), as later supplemented in 2011 by California Senate
Bill 790, provides the broad framework under which CCE operates. Under AB 117, local governments
procure electricity for retail customers aggregated within their boundaries, while the investor-owned
utility (IOU) continues to provide transmission, distribution, metering, billing, payment collection,
customer care, and other services.
When a CCE is ready to begin service to customers, all of the CCE jurisdictional customers are
automatically enrolled in the CCE electric procurement service. Any customer who prefers to continue to
receive procurement service from the IOU may, without penalty, opt-out of the CCE. Because the CCE is
now procuring electricity for the CCE customer, the charge for the CCE electric procurement appears on
the IOU bill, along with an additional charge called the Power Charge Indifference Adjustment (PCIA). The
PCIA is imposed on CCE customers to ensure that customers opting out of CCE service are not financially
impacted by the formation and operation of the CCE.
Since Marin Clean Energy launched in 2010, seven additional CCE programs have become operational.
About half a dozen CCE programs are very close to launching, and much more are under serious
consideration. Nearly all of the operational, and most of the planned, CCE programs are multi-
jurisdictional joint powers authorities. The City of Lancaster has, however, operated a single-jurisdiction
CCE for almost three years, and plans for other single-jurisdiction CCE programs are currently underway.
This abbreviated technical review is provided to the County of San Luis Obispo (SLO County) and the City
of San Luis Obispo (SLO City) as a preliminary evaluation of the financial viability of establishing a CCE
program. However, this review is by no means a complete analysis of a CCE. If SLO County, SLO City or
both elect to take the next steps in moving forward with establishing a CCE, it is strongly encouraged that
a full technical analysis and review be completed by a management consulting firm to determine the
feasibility of establishing a CCE.
There are several initial assumptions used in the “baseline” feasibility model. These assumptions include
an uncollected factor of 0.25%; the opt-out rate of 20%; and renewable purchase to follow the standard
RPS schedule. There is no consideration is made for rate stabilization fund, project and programming fund,
or accounting for debt service. These items would have to come out of available headroom and are specific
to each CCE structure. It is best to establish a “baseline” and make adjustments to the model from the
baseline. This way one can identify the impact of making a change to the model.
The review evaluates the financial viability of a City, County and Combined CCE program by:
• Forecasting the electricity load requirements and potential customers by class;
• Estimating the costs of procuring the electric supply;
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• Estimating the costs of administering the CCE program;
• Evaluating the impact of changes to the review assumptions on the projected feasibility outcomes
by completing two scenarios based on the renewable content and customer rate reduction.
Two (2) scenarios were completed for each jurisdiction, identifying the possible headroom available to
the CCE:
• Scenario 1 – Renewable Portfolio Standard (RPS) Compliant
• Scenario 2 - 50% Renewable Energy
A summary of the results of the expected outcomes and sensitivity analysis is outlined below:
The results of the feasibility model provided positive headroom for all years, for all scenarios and
jurisdictions. In Scenario 1 the most headroom is made available for the CCE. This scenario, in all
jurisdictions, provides the minimum renewable energy needed to remain compliant with the RPS rules
outlined by the California Public Utilities Commission (CPUC). The CCE portfolio content will have 29%
renewable energy beginning in 2018 and will increase by 2% each and every year there afterward.
Scenario 1 assumes as close to what the IOU’s renewable energy portfolio would be over a ten-year
period.
The primary difference between the County results and the City results is the size of load and number of
accounts. The County energy load is much larger than the City energy load, with the largest contributors
being large commercial and agriculture making up approximately 43.3% of the overall load. Whereas, the
City energy load is relatively evenly split between residential, small, medium and large commercial
customer.
In Scenario 2, there was positive headroom for all years and for all jurisdictions. However, as expected,
the headroom has decreased due to the higher percentage of renewable energy in the portfolio,
increasing to 50% for all years. The cost of renewable energy is purchased at a premium to the cost of
system energy. However, the CCE still have available headroom and would be rate competitive with the
IOU.
Year Criteria Scenario 1 Scenario 2 Scenario 1 Scenario 2 Scenario 1 Scenario 2
Probability Revenue is > $0.00 76%65%63%48%67%51%
Expected Revenue*$1,615,225 $854,189 $2,285,884 $198,967 $3,908,504 $1,060,548
Certainty Level**45.29% 46.63% 45.46% 46.80% 47.09% 46.67%
Probability Revenue is > $0.00 100% 100% 100%99% 100%98%
2018-2022 Expected Revenue $14,093,511 $10,834,614 $27,171,335 $18,248,709 $41,260,248 $29,078,711
Certainty Level 58.69% 58.11% 58.94% 58.77% 59.59% 58.72%
Probability Revenue is > $0.00 100% 100% 100% 100% 100% 100%
Expected Revenue $34,330,515 $29,331,450 $70,516,335 $56,847,625 $104,815,718 $86,147,916
Certainty Level 87.25% 86.98% 86.62% 87.01% 86.51% 87.61%
Potential rate reduction***5.58% 4.77% 4.26% 3.44% 4.62% 3.80%
City County County and City
*** "Potential rate reduction" provides a rough estimate of annual reduction across all rate classes if all net revenue were applied to reducing rates
* "Expected Revenue" indicates the net revenue as predicted by the model
** "Certainty level" indicates probability of net revenue equaling or exceeding the expected model outcome
2018
2018-2027
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The certainty level is relatively the same between jurisdictions. However, the certainty level is slightly
higher in Scenario 2 versus Scenario 1 due to the higher component of system energy which is more
volatile than renewable energy. Although, both renewable energy and system energy is subject to market
fluctuation.
Model Assumptions
The Model has the flexibility to modify multiple assumptions, the Baseline assumptions are highlighted in
red. Furthermore, the descriptive statistics are provided on any variable that was allowed to fluctuate
during the sensitivity analysis.
• Rate Reduction – 0%, unless the scenario requires it
• Uncollected Factor – 0.25%
• Opt-out Rate – 20%, sensitivity analysis allows opt-out rate to fluctuate using a normal distribution
with parameters: mean 20% and standard deviation 2.0%
• Renewable Purchase – Standard RPS schedule, unless the scenario requires a specific percentage
• GHG Purchase – 0%
• Rate Stabilization Fund – 0%
• Renewable Category 2 Override – No
• Opt-up 100% Renewable Program – 0%
• NP15 On Peak – Sensitivity analysis allows on-peak prices to fluctuate using a lognormal
distribution with parameters: mean $37.77, the standard deviation of $8.25, and coefficient to NP
15 Off Peak of 0.98. Statistical information based on historical NP 15 On Peak prices between 2009
– 2016.
• NP15 Off Peak - Sensitivity analysis allows off-peak prices to fluctuate using a lognormal
distribution with parameters: mean $29.50, the standard deviation of $8.16, and coefficient to NP
15 On Peak of 0.98. Statistical information based on historical NP 15 Off Peak prices between
2009 – 2016.
Scenarios
Two (2) scenarios were completed for SLO City, SLO County, and SLO City and County combined. Each
scenario identified the possible headroom available to the CCE. All scenarios consisted of a combination
of renewable energy component and some level of rate reduction.
• Scenario 1 - RPS Compliant (following the CPUC RPS Compliance Rules) and zero rate reduction
are given to customers. This scenario is considered the baseline.
• Scenario 2 - 50% Renewable Energy and zero rate reduction given to customers.
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5 October 20, 2017
City of San Luis Obispo
Based on historical utility load data provided by Pacific Gas & Electric (PG&E), the total annual load was
271,342 MWh with 22,971 accounts. Direct Access load was removed from the analysis since it is unknown
whether a Direct Access customer would elect to participate in the CCE. The consumption between rate
class is relatively evenly distributed between small commercial, medium commercial, large commercial,
and residential ranging from 51,000 MWh to 79,000 MWh. However, looking at accounts by rate class,
the majority of the accounts are residential at 18,764 or 81.7%.
Using the data provided, the model increases load and accounts year-over-year by 0.25% and 0.50%,
respectively. The growth assumptions were provided by the California Energy Commission (CEC)
California Energy Demand Forecast for 2015 – 2025. A baseline opt-out rate of 20% was utilized for all
rate classes for all years, resulting in a decrease of overall accounts remaining in the CCE. Although other
CCEs has experienced lower opt-out rates, it is believed 20% is a conservative case to use in the feasibility
analysis. The sensitivity analysis does allow the opt-out rate to fluctuate between 15% and 25%. At
launch, following the increases in load and accounts by 2018, there would be ~18,543 accounts remaining
in the CCE. The annual retail load associated with the accounts remaining would be ~219,406 MWh in the
first year of the CCE, but would marginally increase year-over-year due to increased customer accounts
and load. The total CAISO required load would be ~231,935 in the first year, the delta between retail load
and CAISO load is considered the energy waste resulting from the transmission of electrical energy across
power lines or line losses.
Customer Accounts 2018 2019 2020 2021 2022 2023
Residential 15,124 15,162 15,200 15,238 15,276 15,314
Small Commercial 2,898 2,905 2,912 2,919 2,927 2,934
Medium Comercial 244 244 244 244 244 244
Large Commercial 110 110 110 110 110 110
Agricultural 8 8 8 8 8 8
Lighting 160 160 160 160 160 160
Total Accounts 18,543 18,588 18,634 18,679 18,724 18,770
Customer Load (MWh)2018 2019 2020 2021 2022 2023
Residential 64,067 64,388 64,709 65,033 65,358 65,685
Small Commercial 49,746 49,995 50,245 50,496 50,748 51,002
Medium Comercial 41,489 41,696 41,905 42,114 42,325 42,536
Large Commercial 64,276 64,597 64,920 65,245 65,571 65,899
Agricultural 100 100 100 100 100 100
Lighting 821 821 821 821 821 821
Total Retail Load (MWh)219,406 220,499 221,597 222,700 223,809 224,923
Total CAISO Load (MWh)231,935 233,090 234,250 235,417 236,589 237,767
Rate Class Bundled Accounts Rate Class Percentage
AGRICULTURE 10 0.0%
LARGE COMMERCIAL 137 0.6%
MEDIUM COMMERCIAL 305 1.3%
OUTDOOR LIGHTING 160 0.7%
RESIDENTIAL 18,764 81.7%
SMALL COMMERCIAL 3,595 15.7%
Total 22,971 100.0%
Rate Class Annual MWh Rate Class Percentage
AGRICULTURE 125 0.0%
LARGE COMMERCIAL 79,152 29.2%
MEDIUM COMMERCIAL 51,091 18.8%
OUTDOOR LIGHTING 821 0.3%
RESIDENTIAL 78,895 29.1%
SMALL COMMERCIAL 61,259 22.6%
Total 271,342 100.0%
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6 October 20, 2017
Load Profile and Shape
It is the responsibility of the CCE to procure energy and related services. Forecasting, profiling, and risk
management are the primary tasks conducted for energy procurement. In doing so, one must evaluate
the load data provided by the utility.
Using data provided by PG&E, we are able to illustrate the forecasted hourly load shape by month. The
Forecasted Hourly Shape graph demonstrates the expected load consumed in each hour over a 24-hour
period by month. As expected, there is a higher demand for energy during the peak demand over a day.
Furthermore, we are able to illustrate the forecasted total monthly load over the calendar year. As
expected, there is a higher expected consumption during the winter months due to shorter daylight hours.
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7 October 20, 2017
Finally, we are able to illustrate the forecasted on-peak and off-peak block shape by month. This
information is vital when purchasing block energy from the wholesale market.
Scenario 1 – RPS Compliant (Baseline)
The RPS Compliant or baseline scenario would
demonstrate the profitability of the CCE if it
followed the minimum RPS requirement outlined
by the CPUC. In the CCE Revenue and Expense
charge, each colored section represents the fees
associated with a CCE. The purple section is the
net CCE revenue or headroom off the CCE. The
largest expense associated with a CCE is power
supply costs, identified in the red section. The
blue section represents non-bypassable charges,
which are fees associated with the PG&E and
include, but limited to, franchise fees, PCIA
charges, and DWR Bond fees. The non-
bypassable charges are forecasted to decline
with the elimination of the bond fee, and the cost
of PG&E’s resources is increasing. However, if
prices decline further, that would have upward
pressure on the PCIA charges, putting pressure
on headroom for the CCE. In the simulation
analysis, the PCIA is allowed to fluctuate due to
changes in the market prices. Finally, the green
section represents O&M fees associated with
running a CCE. As no structure has been outlined
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by the county or city, an average of cost was applied similarly to the administrative costs associated with
Sonoma Clean Power and Marin County Energy. The CCE Headroom chart provides a closer view of the
forecasted year-over-year annual headroom for the CCE. The red line is the cumulative CCE headroom
over the ten-year period.
Alternative - RPS Compliant with a Rate Reduction
As an alternative to Scenario 1, any available
headroom could be applied as a rate reduction
over a 10-year period. When applying the
available headroom as a rate reduction, the CCE
will have zero ($0) at the end of the 10 years. This
provides an average rate reduction of 5.58% over
the 10 years. When comparing a customer’s
monthly billing, the rate reduction lowers the
monthly bill by an average of $88.91 per annum
over a ten-year period. The chart illustrates the
average monthly invoice, across all rate classes
and a consumption of 500 kWh per month and a
delivery rate of $0.1394 per kWh.
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9 October 20, 2017
Simulation Analysis
Compared with many other CCA feasibility studies, this
abbreviated study takes a modified approach to sensitivity
analysis, instead of the conventional low-medium-high
approach, this study utilizes a Monte Carlo simulation to
determine a range of values and probabilities. The Monte
Carlo simulation randomly generates a range of values for
the assumption that has been pre-defined. The inputs
feed into defined forecast cells, providing a range of
possible outcomes, which are expressed as a distribution
graph. The distribution can be used to provide an
estimate of the probability or certainty of a particular
outcome. Pilot considers this approach to provide a more
accurate and meaningful analysis.
For the sensitivity, three periods of cumulative CCE
headroom are highlighted in the analysis: year 2018, years
2018-2022, and years 2018-2027. Allowing variables such
as opt-out rates and forward prices on system generation
to fluctuate, the probability of 2018 City CCE headroom to
be greater than the expected outcome is 45.29%. The
modeled expected headroom is $1,615,225, with a mean
of $1,334,612 and a median of $1,402,297. The
probability of the City 2018-2022 CCE headroom to be
greater than the modeled expected outcome of
$14,093,511 is 58.69%, with a mean of $14,947,479 and a
median of $15,059,219. Finally, the probability of the City CCE 2018-2027 headroom to be greater than
the modeled expected outcome of $34,330,315 is 87.25%, with a mean of $42,904,220 and a median of
$43,084,122.
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10 October 20, 2017
Scenario 2 – 50% Renewable Energy
In the second scenario, the renewable component
has increased to 50% exceeding the RPS
requirements outlined by the CPUC. There is no
rate reduction applied in this scenario. Under the
higher renewable energy scenario, the headroom
for the CCE falls by ~$761,000 each year. The
lower headroom is due to the cost or premium
paid to purchase additional renewable energy
over and above the RPS compliance requirement.
Alternative – 50% Renewable Energy with a Rate Reduction
As an alternative in Scenario 2, any available
headroom could be applied as a rate reduction
over a 10-year period. When applying the available
headroom as a rate reduction, the CCE will have
zero ($0) at the end of the 10 years. This provides
an average rate reduction of 4.77% over the 10
years. When comparing a customer’s monthly
billing, the rate reduction lowers the monthly bill
by an average of $76.68 per annum over a ten-year
period. The chart illustrates the average monthly
invoice, across all rate classes and a consumption
of 500 kWh per month and a delivery rate of
$0.1394 per kWh.
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11 October 20, 2017
Simulation Analysis
We performed a sensitivity analysis on multiple variables that are key to determine a probability of a
specific outcome, in this case, forecasted headroom. Using a statistical modeling simulation software, we
were able to derive probabilistic frequency curves. These curves are formulated by running thousands of
trials of the model which allow the key variables to fluctuate based on specific parameters.
For the sensitivity, again three periods of cumulative CCE
headroom are highlighted in the analysis: year 2018,
years 2018-2022, and years 2018-2027. Allowing
variables such as opt-out rates and forward prices on
system generation to fluctuate, the probability of 2018
City CCE headroom to be greater than the expected
outcome is 46.63%. The modeled expected headroom is
$854,189, with a mean of $617,382 and a median of
$707,329. The probability of the City 2018-2022 CCE
headroom to be greater than the modeled expected
outcome of $10,834,614 is 58.11%, with a mean of
$11,690,356 and a median of $11,686,958. Finally, the
probability of the City CCE 2018-2027 headroom to be
greater than the modeled expected outcome of
$29,331,450 is 86.98%, with a mean of $37,866,887 and
a median of $37,893,785.
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Unincorporated County of San Luis Obispo
Based on historical utility load data provided by PG&E, the total annual load was 745,275 MWh with
58,801 accounts. Direct Access load was removed from the analysis since it is unknown whether a Direct
Access customer would elect to participate in the CCE. As expected, the consumption between rate classes
would vary from the City data. Large commercial and agricultural load is taking a larger segment of
consumption at 25.9% and 17.4%, respectively, followed by residential customer load at 36.9%. However,
looking at accounts by rate class, the majority of the accounts are residential at 48,676 or 82.8%.
Using the data provided, the model increases load and account year-over-year by 0.25% and 0.50%,
respectively. The growth assumptions were provided by the California Energy Commission (CEC)
California Energy Demand Forecast for 2015 – 2025. A baseline opt-out rate of 20% was utilized for all
rate classes for all years, resulting in a decrease overall accounts remaining in the CCE. Other CCEs has
experienced lower opt-out rates. However, it is believed 20% is a conservative case to use in the feasibility
analysis. The sensitivity analysis does allow the opt-out rate to fluctuate between 15% and 25%. At launch
following the increases in load and accounts by 2018, there would be ~47,477 accounts remaining in the
CCE. The annual retail load associated with the accounts remaining would be ~601,400 MWh in the first
year of the CCE, but would marginally increase year-over-year due to increased customer accounts and
load. The total CAISO required load would be ~636,013 in the first year, the delta between retail load and
CAISO load is considered line loss. Line loss is energy waste resulting from the transmission of electrical
energy across power lines.
Customer Accounts 2018 2019 2020 2021 2022 2023
Residential 39,234 39,332 39,430 39,529 39,627 39,726
Small Commercial 5,091 5,104 5,116 5,129 5,142 5,155
Medium Comercial 244 244 244 244 244 244
Large Commercial 170 170 170 170 170 170
Agricultural 2,214 2,214 2,214 2,214 2,214 2,214
Lighting 525 525 525 525 525 525
Total Accounts 47,477 47,587 47,698 47,810 47,921 48,033
Rate Class Bundled Accounts Rate Class Percentage
AGRICULTURE 2,767 4.7%
LARGE COMMERCIAL 212 0.4%
MEDIUM COMMERCIAL 305 0.5%
OUTDOOR LIGHTING 525 0.9%
RESIDENTIAL 48,676 82.8%
SMALL COMMERCIAL 6,316 10.7%
Total 58,801 100.0%
Rate Class Annual MWh Rate Class Percentage
AGRICULTURE 129,855 17.4%
LARGE COMMERCIAL 193,117 25.9%
MEDIUM COMMERCIAL 59,149 7.9%
OUTDOOR LIGHTING 1,272 0.2%
RESIDENTIAL 275,069 36.9%
SMALL COMMERCIAL 86,813 11.6%
Total 745,275 100.0%
Customer Load (MWh)2018 2019 2020 2021 2022 2023
Residential 223,372 224,489 225,612 226,740 227,873 229,013
Small Commercial 70,498 70,850 71,204 71,560 71,918 72,278
Medium Comercial 48,033 48,273 48,514 48,757 49,001 49,246
Large Commercial 156,823 157,607 158,395 159,187 159,983 160,783
Agricultural 103,884 103,884 103,884 103,884 103,884 103,884
Lighting 1,272 1,272 1,272 1,272 1,272 1,272
Total Retail Load (MWh)601,400 603,881 606,375 608,881 611,400 613,931
Total CAISO Load (MWh)636,013 638,639 641,279 643,931 646,597 649,276
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13 October 20, 2017
Load Profile and Shape
It is the responsibility of the CCE to procure energy and related services. Forecasting, profiling, and risk
management are the primary tasks conducted for energy procurement. In doing so, one must evaluate
the load data provided by the utility.
Using data provided by PG&E, we are able to illustrate the forecasted hourly load shape by month. The
Forecasted Hourly Shape graph demonstrates the expected load consumed in each hour over a 24-hour
period by month. As expected, there is a higher demand for energy during the peak demand over a day.
Furthermore, we are able to illustrate the forecasted total monthly load over the calendar year. As
expected, there is a higher expected consumption during the winter months due to shorter daylight hours.
As well as, higher expected consumption during the summer months, possibly due to A/C usage in the
inland region.
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14 October 20, 2017
Finally, we are able to illustrate the forecasted on-peak and off-peak block shape by month. This
information is vital when purchasing block energy from the wholesale market.
Scenario 1 – RPS Compliant (Baseline)
The RPS Compliant or baseline scenario
demonstrates the profitability of the CCE if it
only followed the minimum RPS requirement
outlined by the CPUC. In the CCE Revenue and
Expense charge, each colored section
represents the fees associated with a CCE. The
purple section is the net CCE revenue or
headroom off the CCE. The largest expense
associated with a CCE is power supply costs,
identified in the red section. The blue section
represents non-bypassable charges, which are
fees associated with the PG&E and include, but limited to, franchise fees, PCIA charges, and DWR Bond
fees. The non-bypassable charges are forecasted to decline with the elimination of the bond fee, and the
cost of PG&E’s resources is increasing. However, if prices decline further, that would have upward
pressure on the PCIA charges, putting pressure on headroom for the CCE. In the simulation analysis, the
PCIA is allowed to fluctuate due to changes in the market prices. Finally, the green section represents
O&M fees associated with running a CCE. As no structure has been outlined by the county or city, an
average of cost was applied similarly to the administrative costs associated with Sonoma Clean Power and
Marin County Energy.
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15 October 20, 2017
The CCE Headroom chart illustrates a closer view
of the forecasted year-over-year annual
headroom for the CCE. The red line is the
cumulative CCE headroom.
Alternative - RPS Compliant with a Rate Reduction
As an alternative to Scenario 1, any available
headroom could be applied as a rate reduction
over a 10-year period. When applying the
available headroom as a rate reduction, the CCE
will have zero ($0) at the end of the 10 years. This
provides an average rate reduction of 4.26% over
the 10 years. When comparing a customer’s
monthly billing, the rate reduction lowers the
monthly bill by an average of $67.36 per annum
over a ten-year period. The chart illustrates the
average monthly invoice, across all rate classes
and a consumption of 500 kWh per month and a
delivery rate of $0.1394 per kWh.
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16 October 20, 2017
Simulation Analysis
We performed a sensitivity analysis on multiple
variables that are key to determine a probability of a
specific outcome, in this case, forecasted headroom.
Using a statistical modeling simulation software, we
were able to derive probabilistic frequency curves.
These curves are formulated by running thousands of
trials of the model which allow the key variables to
fluctuate based on specific parameters.
For the sensitivity, again three periods of cumulative
CCE headroom are highlighted in the analysis: year
2018, years 2018-2022, and years 2018-2027. Allowing
variables such as opt-out rates and forward prices on
system generation to fluctuate, the probability of 2018
City CCE headroom to be greater than the expected
outcome is 45.46%. The modeled expected headroom
is $2,285,884, with a mean of $1,447,631 and a median
of $1,709,989. The probability of the City 2018-2022
CCE headroom to be greater than the modeled
expected outcome of $27,171,335 is 58.94%, with a
mean of $29,629,721 and a median of $29,633,252.
Finally, the probability of the City CCE 2018-2027
headroom to be greater than the modeled expected
outcome of $70,516,335 is 86.62%, with a mean of
$93,924,794 and a median of $94,947,213.
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Scenario 2 – 50% Renewable Energy
In Scenario 2, the renewable component has
increased to 50% exceeding the RPS
requirements outlined by the CPUC. There is no
rate reduction applied in this scenario. Under
the higher renewable energy scenario, the
headroom for the CCE falls by ~$2,090,000 each
year. The lower headroom is due to the cost or
premium paid to purchase additional renewable
energy than the RPS compliance requirement.
Alternative – 50% Renewable Energy with a Rate Reduction
As an alternative to Scenario 2, any available
headroom is applied as a rate reduction over a
10-year period. When applying the available
headroom as a rate reduction, the CCE will have
zero ($0) at the end of the 10 years. This provides
an average rate reduction of 4.26% over the 10
years. When comparing a customer’s monthly
billing, the rate reduction lowers the monthly bill
by an average of $55.13 per annum over a ten-
year period. The chart illustrates the average
monthly invoice, across all rate classes and a
consumption of 500 kWh per month and a
delivery rate of $0.1394 per kWh.
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18 October 20, 2017
Simulation Analysis
We performed a sensitivity analysis on multiple variables
that are key to determine a probability of a specific
outcome, in this case, forecasted headroom. Using a
statistical modeling simulation software, we were able to
derive probabilistic frequency curves. These curves are
formulated by running thousands of trials of the model
which allow the key variables to fluctuate based on
specific parameters.
For the sensitivity, again three periods of cumulative CCE
headroom are highlighted in the analysis: year 2018, years
2018-2022, and years 2018-2027. Allowing variables such
as opt-out rates and forward prices on system generation
to fluctuate, the probability of 2018 City CCE headroom to
be greater than the expected outcome is 46.80%. The
modeled expected headroom is $198,967, with a mean of
($508,772) and a median of ($236,488). The probability of
the City 2018-2022 CCE headroom to be greater than the
modeled expected outcome of $18,248,709 is 58.77%,
with a mean of $20,470,588 and a median of $20,812,001.
Finally, the probability of the City CCE 2018-2027
headroom to be greater than the modeled expected
outcome of $56,847,625 is 87.01%, with a mean of
$80,311,648 and a median of $80,636,845.
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City and Unincorporated County of San Luis Obispo, combined
Finally, based on historical utility load data provided by PG&E, the total annual load was 1,016,617 MWh
with 81,772 accounts. Direct Access load was removed from the analysis since it is unknown whether a
Direct Access customer would elect to participate in the CCE. As expected, the consumption between rate
classes from the Combined data varies from the segregated City and County datasets. Large commercial
and residential load is taking a larger segment of consumption at 26.8% and 34.8%, respectively, followed
by agriculture load at 17.4%. However, looking at accounts by rate class, the majority of the accounts are
residential at 67,440 or 82.5%.
Using the data provided, the model increases load and account year-over-year by 0.25% and 0.50%,
respectively. The growth assumptions were provided by the California Energy Commission (CEC)
California Energy Demand Forecast for 2015 – 2025. A baseline opt-out rate of 20% was utilized for all
rate classes for all years, resulting in a decrease of overall accounts remaining in the CCE. Other CCEs have
experienced lower opt-out rates. However, it is believed 20% is a conservative case to use in the feasibility
analysis. The sensitivity analysis does allow the opt-out rate to fluctuate between 15% and 25%. At launch
following the increases in load and accounts by 2018, there would be ~66,020 accounts remaining in the
CCE. The annual retail load associated with the accounts remaining would be ~820,807 MWh in the first
year of the CCE, but would marginally increase year-over-year due to increased customer accounts and
load. The total CAISO required load would be ~867,948 in the first year, the delta between retail load and
Rate Class Annual MWh Rate Class Percentage
AGRICULTURE 129,980 12.8%
LARGE COMMERCIAL 272,269 26.8%
MEDIUM COMMERCIAL 110,240 10.8%
OUTDOOR LIGHTING 2,093 0.2%
RESIDENTIAL 353,963 34.8%
SMALL COMMERCIAL 148,072 14.6%
Total 1,016,617 100.0%
Rate Class Bundled Accounts Rate Class Percentage
AGRICULTURE 2,777 3.4%
LARGE COMMERCIAL 349 0.4%
MEDIUM COMMERCIAL 610 0.7%
OUTDOOR LIGHTING 685 0.8%
RESIDENTIAL 67,440 82.5%
SMALL COMMERCIAL 9,911 12.1%
Total 81,772 100.0%
Customer Load (MWh)2018 2019 2020 2021 2022 2023
Residential 287,440 288,877 290,321 291,773 293,232 294,698
Small Commercial 120,243 120,845 121,449 122,056 122,666 123,280
Medium Comercial 89,521 89,969 90,419 90,871 91,325 91,782
Large Commercial 221,098 222,204 223,315 224,432 225,554 226,681
Agricultural 103,984 103,984 103,984 103,984 103,984 103,984
Lighting 2,093 2,093 2,093 2,093 2,093 2,093
Total Retail Load (MWh)820,807 824,380 827,972 831,581 835,209 838,854
Total CAISO Load (MWh)867,948 871,730 875,530 879,349 883,187 887,045
Customer Accounts 2018 2019 2020 2021 2022 2023
Residential 54,358 54,494 54,630 54,766 54,903 55,041
Small Commercial 7,988 8,008 8,028 8,048 8,069 8,089
Medium Comercial 488 488 488 488 488 488
Large Commercial 279 279 279 279 279 279
Agricultural 2,222 2,222 2,222 2,222 2,222 2,222
Lighting 685 685 685 685 685 685
Total Accounts 66,020 66,176 66,332 66,489 66,646 66,803
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20 October 20, 2017
CAISO load is considered line loss. Line loss is energy waste resulting from the transmission of electrical
energy across power lines.
Scenario 1 – RPS Compliant (Baseline)
The RPS Compliant or baseline scenario
demonstrates the profitability of the CCE if it
only followed the minimum RPS requirement
outlined by the CPUC. In the CCE Revenue and
Expense charge, each colored section represents
the fees associated with a CCE. The purple
section is the net CCE revenue or headroom off
the CCE. The largest expense associated with a
CCE is power supply costs, identified in the red
section. The blue section represents non-
bypassable charges, which are fees associated
with the PG&E and include, but limited to,
franchise fees, PCIA charges, and DWR Bond fees. The non-bypassable charges are forecasted to decline
with the elimination of the bond fee, and the cost of PG&E’s resources is increasing. However, if prices
decline further, that would have upward pressure on the PCIA charges, putting pressure on headroom for
the CCE. In the simulation analysis, the PCIA is allowed to fluctuate due to changes in the market prices.
Finally, the green section represents O&M fees associated with running a CCE. As no structure, has been
outlined by the county or city, an average of cost was applied similarly to the administrative costs
associated with Sonoma Clean Power and Marin County Energy.
The CCE Headroom chart illustrates a closer view
of the forecasted year-over-year annual headroom
for the CCE. The red line is the cumulative CCE
headroom.
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21 October 20, 2017
Alternative - RPS Compliant with a Rate Reduction
As an alternative to Scenario 1, any available headroom is applied as a rate reduction over a 10-year
period. When applying the available
headroom as a rate reduction, the CCE will
have zero ($0) at the end of the 10 years. This
provides an average rate reduction of 4.62%
over the 10 years. When comparing a
customer’s monthly billing, the rate reduction
lowers the monthly bill by an average of
$73.11 per annum over a ten-year period. The
chart illustrates the average monthly invoice,
across all rate classes and a consumption of
500 kWh per month and a delivery rate of
$0.1394 per kWh.
Simulation Analysis
We performed a sensitivity analysis on multiple
variables that are key to determine a probability of a
specific outcome, in this case, forecasted headroom.
Using a statistical modeling simulation software, we
were able to derive probabilistic frequency curves.
These curves are formulated by running thousands of
trials of the model which allow the key variables to
fluctuate based on specific parameters.
Again, we focused on three outcomes: 2018
headroom, 2018-2022 cumulative headroom, and
2018-2027 cumulative headroom. Allowing variables
such as opt-out rates and forward prices on system
generation to fluctuate, the probability of 2018 City
CCE headroom to be greater than the expected
outcome is 47.09%. The modeled expected headroom
is $3,908,504, with a mean of $3,009,003 and a
median of $3,427,841. The probability of the City
2018-2022 CCE headroom to be greater than the
modeled expected outcome of $41,260,248 is 59.59%,
with a mean of $44,588,691 and a median of
$44,826,288. Finally, the probability of the City CCE
2018-2027 headroom to be greater than the modeled
expected outcome of $86,147,916 is 87.61%, with a
mean of $136,352,526 and a median of $137,544,563.
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Scenario 2 – 50% Renewable Energy
In the third scenario, the renewable component
has increased to 50% exceeding the RPS
requirements outlined by the CPUC. There is no
rate reduction applied in this scenario. Under the
higher renewable energy scenario, the
headroom for the CCE falls by ~$2,850,000 each
year. The lower headroom is due to the cost or
premium paid to purchase additional renewable
energy than the RPS compliance requirement.
Alternative – 50% Renewable Energy with a Rate Reduction
As an alternative to Scenario 2, any available
headroom is applied as a rate reduction over a
10-year period. When applying the available
headroom as a rate reduction, the CCE will have
zero ($0) at the end of the 10 years. This provides
an average rate reduction of 3.80% over the 10
years. When comparing a customer’s monthly
billing, the rate reduction lowers the monthly bill
by an average of $60.88 per annum over a ten-
year period. The chart illustrates the average
monthly invoice, across all rate classes and a
consumption of 500 kWh per month and a
delivery rate of $0.1394 per kWh.
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Simulation Analysis
We performed a sensitivity analysis on multiple variables that are key to determine a probability of a
specific outcome, in this case, forecasted headroom. Using a statistical modeling simulation software, we
were able to derive probabilistic frequency curves. These curves are formulated by running thousands of
trials of the model which allow the key variables to fluctuate based on specific parameters.
Again, we focused on three outcomes: 2018 headroom,
2018-2022 cumulative headroom, and 2018-2027
cumulative headroom. Allowing variables such as opt-out
rates and forward prices on system generation to
fluctuate, the probability of 2018 City CCE headroom to
be greater than the expected outcome is 46.67%. The
modeled expected headroom is $1,060,548, with a mean
of $52,607 and a median of $473,368. The probability of
the City 2018-2022 CCE headroom to be greater than the
modeled expected outcome of $29,078,711 is 58.72%,
with a mean of $32,098,164 and a median of $32,303,954.
Finally, the probability of the City CCE 2018-2027
headroom to be greater than the modeled expected
outcome of $86,147,916 is 87.61%, with a mean of
$118,194,123 and a median of $118,589,650.
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Glossary of Terms
aMW: Average annual Megawatt. A unit of energy output over a year that is equal to the energy
produced by the continuous operation of one megawatt of capacity over a period of time (8,760
megawatt-hours).
Basis Difference (Natural Gas): The difference between the price of natural gas at the Henry Hub
natural gas distribution point in Erath, Louisiana, which serves as a central pricing point for
natural gas futures, and the natural gas price at another hub location (such as for Southern
California).
Buckets: Buckets 1-3 refer to different types of renewable energy contracts according to the
Renewable Portfolio Standards requirements. Bucket 1 are traditional contracts for delivery of
electricity directly from a generator within or immediately connected to California. These are the
most valuable and make up the majority of the RECS that are required for LSEs to be RPS
compliant. Buckets 2 and 3 have different levels of intermediation between the generation and
delivery of the energy from the generating resources.
Bundled Customers: Electricity customers who receive all their services (transmission,
distribution and supply) from the Investor-Owned Utility.
CAISO: The California Independent System Operator. The organization is responsible for
managing the electricity grid and system reliability within the former service territories of the
three California IOUs.
California Energy Commission (CEC): The state regulatory agency with primary responsibility for
enforcing the Renewable Portfolio Standards law as well as a number of other, electric-industry
related rules and policies.
California Public Utilities Commission (CPUC): The state agency with primary responsibility for
regulating IOUs, as well as Direct Access (ESP) and CCE entities.
Capacity Factor: the ratio of an electricity generating resource’s actual output over a period of
time to its potential output if it were possible to operate at full nameplate capacity continuously
over the same period. Intermittent renewable resources, like wind and solar, typically have lower
capacity factors than traditional fossil fuel plants because the wind and sun do not blow or shine
consistently.
Category 1: renewable energy and Renewable Energy Certificates (REC’s) from an RPS eligible
facility that is directly interconnected to the distribution or transmission grid within California
Category 2: renewable energy and REC’s from an RPS eligible facility but cannot be delivered to
a California balancing authority without substituting electricity from another source.
Category 3: procurement of unbundled RECs only or not meeting the conditions of Category 1
and 2.
Category 2 Override: the pro forma model will exchange Category 2 renewables for Category 1
renewables.
Climate Zone: A geographic area with distinct climate patterns necessitating varied energy
demands for heating and cooling.
Coincident Peak: Demand for electricity among a group of customers that coincides with peak
total demand on the system.
Community Choice Aggregation: Method available through California law to allow Cities and
Counties to aggregate their citizens and become their electric generation provider.
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Community Choice Energy: A City, County or Joint Powers Agency procuring wholesale power to
supply to retail customers.
Congestion Revenue Rights (CRRs): Financial rights that are allocated to Load Serving Entities to
offset differences between the prices where their generation is located and the price that they
pay to serve their load. These rights may also be bought and sold through an auction process.
CRRs are part of the CAISO market design.
Consumption: The use of energy or the amount of energy consumed by an individual or
organization.
Demand Response (DR): Electric customers who have a contract to modify their electricity usage
in response to requests from a utility or other electric entity. Typically, will be used to lower
demand during peak energy periods, but may be used to raise demand during periods of excess
supply.
Direct Access: Large power consumers which have opted to procure their wholesale supply
independently of the IOUs through an Electricity Service Provider.
DWR Bond Charge: an imposed bond charge to recover Department of Water Resources (DWR)
bond costs from bundled customers.
EEI (Edison Electric Institute) Agreement: A commonly used enabling agreement for transacting
in wholesale power markets.
Electric Service Providers (ESP): An alternative to traditional utilities. They provide electric
services to retail customers in electricity markets that have opened their retail electricity markets
to competition. In California the Direct Access program allows large electricity customers to
optout of utility-supplied power in favor of ESP-provided power. However, there is a cap on the
amount of Direct Access load permitted in the state.
Electric Tariffs: The rates and terms applied to customers by electric utilities. Typically have
different tariffs for different classes of customers and possibly for different supply mixes.
Enterprise Model: When a City or County establish a CCE by themselves as an enterprise within
the municipal government.
Federal Tax Incentives: There are two Federal tax incentive programs. The Investment Tax Credit
(ITC) provides payments to solar generators. The Production Tax Credit (PTC) provides payments
to wind generators.
Feed-in Tariff: A tariff that specifies what generators, who are connected to the distribution
system, are paid.
Forward Prices: Prices for contracts that specify a future delivery date for a commodity or other
security. There are active, liquid forward markets for electricity to be delivered at a number of
Western electricity trading hubs, including NP15 which corresponds closely to the price location
which the City of Davis will pay to supply its load.
Implied Heat Rate: A calculation of the day-ahead electric price divided by the day-ahead natural
gas price. Implied heat rate is also known as the ‘break-even natural gas market heat rate,
because only a natural gas generator with an operating heat rate (measure of unit efficiency)
below the implied heat rate value can make money by burning natural gas to generate power.
Natural gas plants with a higher operating heat rate cannot make money at the prevailing
electricity and natural gas prices.
Integrated Resource Plan: A utility's plan for future generation supply needs.
Investor-Owned Utility: For profit regulated utilities. Within California there are three IOUs -
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Pacific Gas and Electric, Southern California Edison and San Diego Gas and Electric.
ISDA (International Swaps and Derivatives Association): Popular form of bilateral contract to
facilitate wholesale electricity trading.
Joint Powers Agency (JPA): A legal entity comprising two or more public entities. The JPA
provides a separation of financial and legal responsibility from its member entities.
Load Data: Detailed information related to energy consumption by an individual, organization,
or community.
Load Forecast: A forecast of expected load over some future time horizon. Short-term load
forecasts are used to determine what supply sources are needed. Longer-term load forecasts are
used for budgeting and long-term resource planning.
Marginal Unit: An additional unit of power generation to what is currently being produced. At
and electric power plant, the cost to produce a marginal unit is used to determine the cost of
increasing power generation at that source.
MRTU: CAISO's Market Redesign and Technology Upgrade. The redesigned, nodal (as opposed to
zonal) market that went live in April of 2009.
Net Energy Metering: The program and rates that pertain to electricity customers who also
generate electricity, typically from rooftop solar panels.
Non-Coincident Peak: Energy demand by a customer during periods that do not coincide with
maximum total system load.
Non-Renewable Power: Electricity generated from non-renewable sources or that does not
come with a Renewable Energy Credit (REC).
NP15: Refers to a wholesale electricity pricing hub - North of Path 15 - which roughly corresponds
to PG&E's service territory. Forward and Day-Ahead power contracts for Northern California
typically provide for delivery at NP15. It is not a single location, but an aggregate based on the
locations of all the generators in the region.
Off Peak: time when demand for electricity is low between the hours of 11:00 pm to 6:59 am
during the week days and 24 hours during the weekends.
On-Bill Repayment (OBR): Allows electric customers to pay for financed improvements such as
energy efficiency measures through monthly payments on their electricity bills.
On-Peak: time when demand for electricity is high between the hours 7:00 am and 10:59 pm
during the weekdays.
Operate on the Margin: Operation of a business or resource at the limit of where it is profitable.
Opt-Out: Community Choice Aggregation is, by law, an opt-out program. Customers within the
borders of a CCE are automatically enrolled within the CCE unless they proactively opt-out of the
program.
Power Charge Indifference Adjustment (PCIA): A charge applied to customers who leave IOU
service to become Direct Access or CCE customers. The charge is meant to compensate the IOU
for costs that it has previously incurred to serve those customers.
PPA (Power Purchase Agreement): The standard term for bilateral supply contracts in the
electricity industry.
Rate Stabilization Fund: an amount allocated into a reserve fund to be utilized to offset higher
potential higher rates during rate setting.
Renewable Energy Credits (RECs): The renewable attributes from RPS-qualified resources which
must be registered and retired to comply with RPS standards.
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Resource Adequacy (RA): The requirement that a Load-Serving Entity own or procure sufficient
generating capacity to meet its peak load plus a contingency amount (15 percent in California)
for each month.
RPS (Renewable Portfolio Standards): The state-based requirement to procure a certain
percentage of load from RPS-certified renewable resources.
Scheduling Coordinator: An entity that is approved to interact directly with CAISO to schedule
load and generation. All CAISO participants must be or have an SC.
Scheduling Agent: A person or service that forecasts and monitors short term system load
requirements and meets these demands by scheduling power resource to meet that demand.
Spark Spread: The theoretical grow margin of a gas-fired power plant from selling a unit of
electricity, having bought the fuel required to produce this unit of electricity. All other costs
(capital, operation and maintenance, etc.) must be covered from the spark spread.
Supply Stack: Refers to the generators within a region, stacked up according to their marginal
cost to supply energy. Renewables are on the bottom of the stack and peaking gas generators on
the top. Used to provide insights into how the price of electricity is likely to change as the load
changes.
Total CAISO Load: the total electricity need to procure from the CAISO taking in consideration
for line losses. Line losses is wasted electric energy due to inherent inefficiencies or defects in
the distribution or transmission system.
Total Retail Load: the total electricity consumed by consumers (residential and commercial) in a
given period.
Uncollected Factor: a model parameter allocating a percentage of revenue as uncollectable,
otherwise considered bad debt.
Weather-Adjusted: Normalizing energy use data based on differences in the weather during the
time of use. For instance, energy use is expected to be higher on extremely hot days when air
conditioning is in higher demand than on days with comfortable temperature. Weather
adjustment normalizes for this variation.
Wholesale Power: Large amounts of electricity that are bought and sold by utilities and other
electric companies in bulk at specific trading hubs. Quantities are measured in MWs, and a
standard wholesale contract is for 25 MW for a month during heavy-load or peak hours (7am to
10 pm, Mon-Sat), or light-load or off-peak hours (all the other hours).
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COMMUNITY CHOICE ENERGYCity Council Study Session – December 12, 20171City Council Study Session to receive update on Community Choice Energy feasibility studies and provide direction to staff on continued pursuit of the City’s involvement in a Community Choice Energy program12/12/2017 Item 1, Staff Presentation
1.Receive and file the Technical Feasibility Study on Community Choice Energy (CCE) for the Tri-County -San Luis Obispo County, Santa Barbara County, and Ventura County.2.Receive and file an initial feasibility study by Pilot Power Group for the intra-county region – City of San Luis Obispo and County of San Luis Obispo3.Provide staff with direction regarding community choice energy options as follows:a)Form a new CCE program; orb)Solicit proposals to identify an existing CCE program to join; or c)Discontinue or pause the pursuit of a CCE program at this time2Recommendations12/12/2017 Item 1, Staff Presentation
March 2015: City Council approved resolution No. 10609 confirming the City’s participation in the exploration of CCE. Authorized participation in an inter-jurisdictional investigation into CCE. Allowed technical consultants to acquire energy usage load from the electric distribution utility for analysis in feasibility studies. 3City Council Previous Review and Direction12/12/2017 Item 1, Staff Presentation
Outline1.About Community Choice Energy2.Steps to Forming a CCE program3.Update on Efforts Since Council Directiona)Tri-County Feasibility Studyb)Intra-County Feasibility Study4.Options for Council Consideration5.Questions for City Council deliberation412/12/2017 Item 1, Staff Presentation
5Enables local governments to leverage purchasing power of residents, businesses and governments to purchase or generate power for their communities:CCE purchases the electricity, sets the rates, and PG&E continues to deliver the electricity via their powerlines, and continue to provide metering, billing, and other customer service as they do now. About Community Choice Energy12/12/2017 Item 1, Staff Presentation
6Statewide CCE Developments9 operational CCE programs throughout California:More than 20 jurisdictions actively studying or developing CCEprograms.Several more programs expected to launch in 2018.Source: California Community Choice Association12/12/2017 Item 1, Staff Presentation
7Snapshot of CCE Portfolios30%22%35%40%35%53%50% 50%37%36%50%6%5%36%22%25%27%41%50%23%9%6%24%44%24%12%17%14%65% 65%13%25%50%36%23%0%10%20%30%40%50%60%70%80%90%100%RenewableLarge HydroNuclearCoalNatural GasUnspecifiedSource: California Community Choice Association12/12/2017 Item 1, Staff Presentation
8Launch•Launch the program •Hire staff/vendors •Purchase power•Set up power scheduling •Develop customer support program•Establish billing systems and processes with PG&E •Develop marketing materials•Notify customers of program launchSteps to forming a CCE programImplementation•If feasible, set up implementation plan (provides detail on how program will be launched and operated)•IOU service agreements with PG&E •Form JPA. •Get plan certified by CPUC. •Begin Community outreach and educationFeasibility•Feasibility study prepared by consultant•Obtain electricity consumption data from PG&E•Determine viability of CCEprogram based on geographic and RPS scenarios.•Determine rate competitiveness with PG&E12/12/2017 Item 1, Staff Presentation
9Update on Efforts Since Council Direction12/12/2017 Item 1, Staff Presentation
10Update on Efforts Since Council Direction12/12/2017 Item 1, Staff Presentation
11Update on Efforts Since Council Direction12/12/2017 Item 1, Staff Presentation
12Update on Efforts Since Council Direction12/12/2017 Item 1, Staff Presentation
13Update on Efforts Since Council DirectionCCE versus PG&E Rate Comparison, Unincorporated San Luis Obispo County Middle of the Road (50% Renewable) Scenario12/12/2017 Item 1, Staff Presentation
14Update on Efforts Since Council Direction12/12/2017 Item 1, Staff Presentation
15Update on Efforts Since Council Direction12/12/2017 Item 1, Staff Presentation
16Update on Efforts Since Council Direction12/12/2017 Item 1, Staff Presentation
17Update on Efforts Since Council Direction12/12/2017 Item 1, Staff Presentation
18Update on Efforts Since Council Direction12/12/2017 Item 1, Staff Presentation
19Options for Council Consideration12/12/2017 Item 1, Staff Presentation
20Options for Council Consideration12/12/2017 Item 1, Staff Presentation
21Options for Council Consideration12/12/2017 Item 1, Staff Presentation
22Comparison of CCE options1A regional approach (multiple jurisdictions) to reducing Greenhouse Gas Emissions in San Luis Obispo2At this time the results of the new study are unknownSpeed CostRisk Local Control Regionalism1Form a New CCE ProgramCity of SLO OnlyMed Low‐High Med/High High LowCity of SLO + other Jurisdictions Med Low/Med Med Med MedMonitor/Join Tri‐County Effort2Slow/? Med Med Med HighJoin an Existing ProgramFast Low Low Low LowDiscontinue or Pause Pursuitn/a n/a n/a n/a n/a12/12/2017 Item 1, Staff Presentation
23Questions for Council Consideration and DirectionQuestions for City Council directionYes NoA. Pursuit of Community Choice Energy (CCE)1. Continue pursuit of CCE2. Pause pursuit of CCE3. Discontinue pursuit of CCEA. Form a new Community Choice Energy program?1. City of San Luis Obispo Only?2. City of San Luis Obispo and pursue other jurisdictions?3. Continue to monitor the tri‐countyeffortandpossiblyjoinSantaBarbara?A. Join an Existing Program?1. Monterey Bay Community Power or similar?12/12/2017 Item 1, Staff Presentation
1.Receive and file the Technical Feasibility Study on Community Choice Energy (CCE) for the Tri-County -San Luis Obispo County, Santa Barbara County, and Ventura County.2.Receive and file an initial feasibility study by Pilot Power Group for the intra-county region – City of San Luis Obispo and County of San Luis Obispo3.Provide staff with direction regarding community choice energy options as follows:a)Form a new CCE program; orb)Olocit proposals to identify an existing CCE program to join; orc)Discontinue or pause the pursuit of a CCE program at this time24Recommendations12/12/2017 Item 1, Staff Presentation