FOR ALAMEDA COUNTY MRW & Associates Oakland, California DRAFT - - PowerPoint PPT Presentation

CCA FEASIBILITY STUDY FOR ALAMEDA COUNTY DRAFT RESULTS

MAY 4, 2016

MRW & Associates Oakland, California

mef@mrwassoc.com 510.834-1999

Item 4b May 25, 2016

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TONIGHT’S PRESENTATION

 Loads and Forecasts  Analysis Approach  Results  Risks and Sensitivities  Energy Efficiency Impacts/Implications  Macroeconomic Implications  Conclusions/Next Steps

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LOADS AND FORECAST

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LOAD BY JURISDICTION

OTHERS 15% OAKLAND 25% FREMONT 16% HAYWARD 10% BERKELEY 9% PLEASANTON 7% SAN LEANDRO 6% UNINCORPORATED 6% LIVERMORE 6%

 Power supply procurement objectives

• Balancing hourly supply/demand
• Meet resource adequacy requirements
• Meet RPS requirements /CCA renewable targets
• Local generation
• Compete with PG&E rates

 This Analysis:

• RPS portfolio ratio of 45:45:10 solar:wind:baseload (e.g., geothermal)
• Up to 10% of renewable supply by 2030 from local solar resources
• Balance of supply from non-renewable market purchases
• RPS contract and non-renewable market prices same for CCA and PG&E
• RPS prices driven by assumptions regarding future tax credits
• Premium for Alameda County solar included in cost forecast
• Solar generation projects in Alameda Co: 15% cost premium
• Smaller local projects (<3 MW): 55% premium over large projects

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POWER SUPPLY PROCUREMENT

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ANALYSIS APPROACH: POWER SUPPLY

Powe

• wer

r Suppl ply y Costs Renewabl ewable e Powe

• wer

Energy gy Excess Supply Capacity RECs Non- Renewabl ewable e Powe

• wer

Energy gy Natural ral Gas Greenhouse Gas Allowances Capac acity ty

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RENEWABLE POWER SUPPLY PRICES

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FORECAST BY RATE CLASS

1. Minimum RPS Compliance: 33%50% qualifying renewables 2. More Aggressive: Initially 50% with lower GHG emissions 3. Ultra-Low GHG: 50%80% by year 5

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RESULTS: THREE SCENARIOS

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RENEWABLE BUILD-OUT

SCENARIO 3 SCENARIO 1

200 400 600 800 1000 1200 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 MWs (Cumulative) Small Solar (in county) (<3MW) Large Solar (in county) Large Solar Wind 200 400 600 800 1000 1200 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 MWs (Cumulative) Small Solar (in county) (<3MW) Large Solar (in county) Large Solar Wind

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RESULTS: SCENARIO 1 (RPS)

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AVERAGE BILL SAVINGS - RESIDENTIAL

Residential Monthly Consumption (kWh) Bill with PG&E ($) Bill with Alameda CCA ($) Difference ($) 2017 650 148 141 7 2020 650 160 144 16 2030 650 202 186 15

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RESULTS: SCENARIO 2(ACCELERATED RPS)

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RESULTS: SCENARIO 3 (80% BY YEAR 5)

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RESULTS: GHG SAVINGS

Total GHG savings (MMTonnes) Scenario 2 1/3 Hydro Scenario 2 2/3 Hydro Scenario 3 1/3 Hydro Scenario 3 2/3 Hydro 2017-2030 1.8 4.6 11.2 13.2

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PRO FORMA SENSITIVITIES

Risk Description Diablo Canyon relicensed + 25% PG&E generation rates 2024-2030 Low PG&E portfolio costs

• 10% PG&E generation rates 2017-2030

High renewable prices + 20 % RPS prices 2017-2030 High PCIA + 60% PCIA fee 2017-2030 High natural gas price + 60% Natural Gas prices 2017-2030

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SENSITIVITY RESULTS

RIS ISK MIT ITIG IGATION ON Rate Competitiveness Rate stabilization fund Communications to CCA customers Good portfolio management (short- medium- and long-term contracts) Carbon Content Contract with low-carbon sources for non-RPS resources Adve verse se Legislat slative e or Regulat latory Ac Actions ions Include regulatory and legislative personnel or contractors; work with a CCA regulatory alliance. Finance/Liquidity Risks Reserve fund; maintain credit line Participation (JPA participation and individual opt-outs) Have commitments from communities before locking in procurement

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RISKS & MITIGATIONS

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CCA-RUN ENERGY EFFICIENCY

Market Environment  Legislative and regulatory initiatives

• SB350 – doubles utility goals for energy efficiency by 2020

 Current EE Delivery Capacity in Alameda County

• BayREN – 3 programs applicable to Alameda County in 2015
• PG&E – 70 EE programs applicable to Alameda County in 2015

 Existing California CCA DSM Portfolio Activity

• Marin Clean Energy is only CCA service as program administrator in

2015

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ENERGY EFFICIENCY FUNDING OPPORTUNITIES

 Funding models for electric energy efficiency programs

• Based on public program purposes charges paid by all customers
• Program Administrator
• For CCA customer only
• For CCA and PG&E customers
• Non-Administrator

 Other Funding Sources

• Gas energy efficiency programs charges
• Income from CCA Operations

Program Administrator - CCA customer only $3,350,000 Program Administrator – CCA and PG&E customers $3,941,000 Non-Administrator (PG&E EE Portfolio based on Alameda PPP contributions) $26,278,000

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ENERGY EFFICIENCY MODELING

Inputs  Program for CCA customers only  Development Timeline

• 3 years fully phase-in CCA
• 1 year for filing and development of EE programs, launch in 2021

 Energy and Demand Savings Potential

• Budget assumes public program purpose funds for CCA customers only

 Economic Activity Related to Energy Efficiency

Activity 2021 2022 2023 2024 2025….. 2030 Baseline Budget $3.7 $3.8 $3.9 $4.0 $4.2 ….. $4.7 Customer Out of Pocket $9.6 $9.8 $10.1 $10.3 $10.6 ….. $12.1 Annual Invest Needed $13.3 $13.7 $14.0 $14.4 $14.8 ….. $16.9 Annual incremental savings (GWh) 5.7 5.8 5.9 5.9 6.0 ….. 6.3 Annual incremental savings (MW) 0.9 0.9 0.9 0.9 0.9 ….. 1.0

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WHAT ENERGY EFFICIENCY PROGRAMS COULD A CCA DEVELOP?

 Increase participation rates in existing initiatives

• PG&E programs
• BayREN programs

 Leverage local government capacity to increase energy efficiency participation

• Integrate energy efficiency (and distributed energy) with core

City/County planning activities

• More stringent codes and standards
• Promote the use of market-ready funding and financing

mechanisms, such as enhanced energy infrastructure financing districts and PACE

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MACROECONOMIC ANALYSIS

Objective: Identify the changes in Business activity & associated Jobs from a CCA proposal Approach: Capture changes in economy from ….

• net Bill savings,
• Spending shifts for capacity, O&M, efficiency, & program admin

Applied a regional calibrated dynamic, forecasting economic model (Regional Economic Modeling Inc.)

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“INCREMENTAL” KEY ASSUMPTIONS FOR JOB GENERATION

• Required investment $ labor vs equipment split
• Renewable and efficiency purchases embody no in-state manufacturing
• Installation (O&M) expenditures engage within-region workforce
• County customer-sited large solar in Com’l segment, 100% self-funded
• Efficiency improvements require customer out-of-pocket
• REMI Construction sector annual compensation is representative of the

market conditions, i.e. a mix of work that is covered (by CBA) & not

• covered. Approx. a 20:80 split in California.
• FY 2016 CA DIR prevailing wage Construction trades 19% higher

Supply Scenario #1 - the BIG picture

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MACROECONOMIC IMPLICATIONS

CCA Bill Savings ($million)* CCA Renewable investment ($million) PG&E Foregone Investment ($million) CCA Renewable O&M ($million) PG&E averted O&M ($million) CCA Administration ($million) CCA Efficiency Investment ($million) Residential Commercial Industrial Government County Rest of State County Rest of State County Rest of State County Rest of State County staff expense Contract Prof. Services Contract Data Mngmnt Srvcs County 27% 73% 0% 100% 26% 74% 0% 100% 100% $737 $745 $346 $162 $2,299

• $1,946

$180

• $153

$51 $57 $166 $164 $1,991 all solar 32% wind; 68% solar 24% wind; 76% solar

* 2017-23030, net of PCIA net of customer-sited* RE/EE investments

Supply Scenario #1 – Regional Economic Changes (impacts)

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MACROECONOMIC IMPLICATIONS

Average Annual (2017 to 2030) Alameda County Jobs 1,720 GRP (bil $ 2015) $0.192 Rest of California Jobs 1,020 GRP (bil $ 2015) $0.140

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MACROECONOMIC IMPLICATIONS

• 500

500 1000 1500 2000 2500 3000 3500 4000 4500 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 Change in Jobs

Job Imp

• b Impacts

acts: Di : Direct ect & & Total

• tal

Al Co. Direct Al Co. Total roCA Direct roCA Total CA_Total

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MACROECONOMIC IMPLICATIONS

500 1,000 1,500 2,000 2,500 3,000

Alameda Co. CCA Scenario 1 Total Jobs Impacts by Source

all all ot

• ther

her CCA ef effect ects (19%) 19%) net net Bil ill l Sav aving ings ef effect ects (81%) 81%)

Impacts for County’s Construction Sector…

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MACROECONOMIC IMPLICATIONS

Alameda County

• Avg. Annual

Scenario Direct Jobs 143 as Construction 80 UNION (covered) 16 non-UNION 64 Scenario Total Jobs 1720 as Construction 282 UNION (covered) 56 non-UNION 226

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MACROECONOMIC IMPLICATIONS

100 200 300 400 500 600 Construction All Other Local Gov. Retail Trade Health Care and Social Assistance Accommodation and Food Services Professional, Scientific, and Technical Services Other Services, except Public Administration Manufacturing Administrative and Waste Management Services Wholesale Trade

2023 2023 Job I

• b Impacts

mpacts for

• r Top 11 S
• p 11 Sector

ectors

Total Direct

 An Alameda County CCA will likely to be able to meet

• r beat PG&E’s retail rates.

 Increasing RPS purchases can be cost-effective, but with some risk  Carbon reduction goals need more than just increased RPS purchasing to be met.  Legislative/Regulatory risks are the most serious

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CONCLUSIONS (S0 FAR)

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NEXT STEPS

 Complete REMI macroeconomic analysis  Integrate any feedback into analysis  Issue report in Mid-May

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MACROECONOMIC IMPLICATIONS

118.653 50 100 150 200 250 300 Utilities Management of Companies and… Information Manufacturing Local Gov. Wholesale Trade Professional, Scientific, and Technical… Construction Transportation and Warehousing Health Care and Social Assistance Finance and Insurance Retail Trade Other Services, except Public… Administrative and Waste Management… Real Estate and Rental and Leasing Arts, Entertainment, and Recreation Educational Services Accommodation and Food Services

2023 2023 Alameda Alameda County County Avg. Annual

• g. Annual Ear

arnings nings r rate te per per Wor

• rker

er (thous thousands ands $ nominal) $ nominal)