california energy commission 2015 iepr self-generation forecast sacramento, ca 7/07/2015 asish...

California Energy Commission

2015 IEPR Self-Generation Forecast

Sacramento, CA

7/07/2015

Asish Gautam

Demand Analysis Office

Energy Assessments Division

[email protected] / 916-654-3900

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Data Sources• Rebate program data vs interconnection data• In prior IEPR demand forecast, staff relied on rebate

program data to track DG installations– California Solar Initiative, New Solar Homes

Partnership, Emerging Renewables Program, Self-Generation Incentive Program

• As programs sunset but strong interest in installing DG (mainly PV) – challenge for staff collecting installation data

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Data Sources

• 2013 IEPR demand forecast – utilities pointed out discrepancy in PV capacity relative to staff’s estimate of PV stock

• Generally due to continued interest by utility customers in installing PV without seeking rebates:– Driven by PV cost reduction, financing options,

and availability of Federal tax credit

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Data Sources

By 2013 difference in PV capacity addition becomes more pronounced.

Annual PV Additions (MW)

Utility CEC % Difference Utility CEC % DifferencePGE 180 184 2% 260 163 -37%SCE 136 163 20% 184 161 -12%SDGE 37 31 -16% 67 32 -52%

353 378 7% 510 356 -30%

2012 2013

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Data/Model Updates

• Updated PV production profile based on data provided by CPUC

• Updated PV peak factors to better reflect impact coincident with utility system peak

• PV cost data/trend from CPUC Net Metering Public Tool (Draft version)

• Residential model redone to use actual electric tariffs (IOUs) instead of average sector rate

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Data/Model Updates

• Using residential load shape data to model net metering

• Assuming that current electric rates and net metering compensation structure will stay in place over forecast period– CPUC currently examining revisions to residential

retail rates and developing alternative net metering compensation program

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Data/Model Updates

• DG incentive program EM&V reports• CEC sponsored report on CHP market

assessment (ICF CHP Policy Analysis)• Revised electric and gas rates • Revised housing data and floor space

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Forecasting Approach• Underlying structure similar to payback/cash

flow model used by EIA/NREL• Payback calculations based on system and

maintenance costs, incentives, and fuel rates• Estimated payback applied to a Bass Diffusion

adoption curve• Results for adoption differ by demand scenario

since projected fuel rates and number of homes/floor space vary by scenario

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Statewide Non-PV Self-Gen Energy ImpactsAll 3 scenarios close to one another and slightly above CED 2013 Mid case

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Statewide Non-PV Self-Gen Peak ImpactsAll 3 scenarios close to another and ~100 MW higher than CED 2013 Mid case

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Statewide PV Self-Gen Energy ImpactsAll 3 scenarios above CED 2013 Mid Case. Impacts range between 21,000 GWH to 25,000 GWH representing 9% - 11% of electricity Consumption. Slower growth after 2016 due to expiration/step-down of Federal tax credit.

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Statewide PV Self-Gen Peak ImpactsAll 3 scenarios above CED 2013 Mid Case. Impacts range between 4,500 MW to 5,400 MW and correspond to installed capacity of 12,000 MW to 14,000 MW

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Optional Scenario – PV Capacity under IOU Rate ReformPV adoption ~1,200 MW lower with rate reform compared to CED 2015 Residential Mid Case.

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Next Steps

• Near Term (Revised Forecast):– Update historical installation data– Other Updates

• Net metering, Residential Rate Reform, Storage, and Distribution Resource Planning Proceeding

• Longer Term (2017 IEPR):– Refinement to long term peak demand forecast methodology to

integrate impacts from DG, EE, storage, and transportation using a

common framework

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