California Energy Commission Customer-side Distributed Generation Impacts CED 2013 Preliminary Demand Analysis Working Group DG PUP June

California Energy Commissionwww.energy.ca.gov

Customer-side Distributed Generation Impacts

CED 2013 Preliminary

Demand Analysis Working Group

DG PUP

June 6, 2013

Asish GautamDemand Analysis Office

Electricity Supply Analysis Division

[email protected] / 916-654-3900

Key Sources of Data

• Annual/Quarterly power plant reporting to CEC (Form CEC 1304)

• Emerging Renewables Program• Self-Generation Incentive Program• California Solar Initiative • New Solar Homes Partnership• POU PV (SB 1 Report to CEC)• California Solar Initiative – Thermal


Key Sources of Data

• DG incentive program EM&V reportso CSI 2010 Impact Evaluation (2007 – 2010)o SGIP 11th Year Impact Evaluation (2002 –

2011)• DOE/EIA PV cost projections developed for

AEO 2013• CEC sponsored report on CHP market

potential (ICF CHP Policy Analysis)


Statewide Non-PV Energy Impact


Statewide Non-PV Peak Impact


Statewide PV Energy Impact


Statewide PV Peak Impact


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Key Uncertainties

• NEM redesign• Retail electric tariff redesign• Federal Tax Credit• CHP

o Interconnection o Standby and departing load charges


Statewide Onsite Use by Technology


Statewide Onsite Use by Sector


Statewide Non-Residential Onsite Use


Statewide Onsite PV Use by Sector


Statewide Onsite Non-PV Use by Sector


2012 PV Installed Capacity by County and Sector (Top Ten)


2012 Non-PV Installed Capacity by County and Sector (Top Ten)


Statewide Onsite Use by Source


2012 Onsite Use by Planning Area and Technology Type


QFER CHP Report


Year Capacity Export Only Onsite/Export Onsite Only Non-Operational Export Onsite Total Percent Export Percent Onsite Capacity Factor2002 8,036 4,721 2,864 355 96 39,479 10,766 50,245 79% 21% 71%2003 8,065 4,554 2,757 501 255 36,972 11,738 48,709 76% 24% 69%2004 7,912 4,603 2,762 458 89 37,483 11,684 49,168 76% 24% 71%2005 7,951 4,660 2,754 489 48 34,283 11,566 45,849 75% 25% 66%2006 7,939 4,551 3,002 350 36 32,272 11,524 43,796 74% 26% 63%2007 7,933 4,642 2,603 627 61 33,642 11,459 45,101 75% 25% 65%2008 7,875 4,540 2,431 725 179 31,849 11,946 43,796 73% 27% 63%2009 7,845 4,470 2,627 585 163 30,782 11,681 42,463 72% 28% 62%2010 7,878 4,340 2,739 582 217 29,595 11,738 41,333 72% 28% 60%2011 7,739 4,318 2,525 751 144 27,209 11,813 39,022 70% 30% 58%

Capacity Energy

Average PV Installed Cost and Rebate


Average Fuel Cell Cost and Rebate


Average Microturbine Costand Rebate


Average IC Engine Costand Rebate


Predictive Modeling(Residential Sector PV/SHW)

• 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 vary by scenario


Predictive Modeling(Residential Sector PV/SHW)

• PV system cost and performance data come from incentive program data and EIA’s AEO 2013 forecast report

• SHW system cost and performance data based on CSI Thermal program database and CPUC sponsored study

• Residential sector model output used for system sizing and valuing net surplus compensation


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Adoption Modeling


Predictive Modeling(Non-Residential Sector PV)

• No predictive model • Forecast based on trend analysis

o Examine rate of growth in adoption based on DG incentive program data

o Estimate growth and then estimated energy and peak impacts based on capacity/peak factors from DG EM&V reports


Predictive Modeling(Commercial Sector CHP)

• Meeting onsite demand for power and two thermal end-uses: hot water and space heating

• CEUS survey data used to compile and summarize building electric and gas demand o ~ 2900 sites represented in surveyo 12 Building Typeso 4 Building Size Categories



• Use DrCEUS building energy use simulation toolo DrCEUS uses eQUEST building energy use

software tool as a “front-end” to the more complex DOE 2.2 building energy use simulation tool which does the actual building energy demand simulation

o Develop load shapes for CHP thermal analysis and economic modeling


CEUS Site ElectricProfile – School


North Coastal South Coastal

CEUS Site ElectricProfile – College


South CoastalNorth Coastal

DrCEUS Analysis - Electric Demand Large Hotel Demand Forecast Zone 4 (North Coastal)


DrCEUS Analysis - Hot Water Demand Large Hotel Demand Forecast Zone 4 (North Coastal)


DrCEUS Analysis - Space Heating Demand Large Hotel Demand Forecast Zone 4 (North Coastal)


DrCEUS Analysis - Distribution of Annual End-Use Consumption by Fuel Type

North Coastal - Large Buildings


DrCEUS Analysis - Distribution of Annual End-Use Consumption by Fuel Type

North Inland- Large Buildings



• CEUS profiles are then benchmarked to QFER calibrated Commercial sector model output and floorspace projections

• Map CEUS site profiles to retail electric/gas tariffs

• Retail electric/gas tariff details escalated based electric/gas rate forecast developed for CED 2013 Preliminary




Id Utility Tarriff Seasonal ID Season Name TOU ID TOU Name TIER ID TIER Name TIER Minimum TIER Maximum Energy Rate ($/kWh) Demand Rate ($/kW) Generation ($/kWh) CTC ($/kWh) DWR ($/kWh) NDC ($/kWh) PPP ($/kWh)

1 PGE A-1 1 Summer 0 0 0 0 0.20495 0 0.09105 0.00095 0.00513 0.00055 0.01709

1 PGE A-1 1 Winter 0 0 0 0 0.14344 0 0.0576 0.00095 0.00513 0.00055 0.01709

5 PGE E-20 1 Summer 0 0 0 0 0 11.72 0 0 0 0 0

5 PGE E-20 1 Winter 0 0 0 0 0 11.72 0 0 0 0 0

5 PGE E-20 1 Summer 1 Peak 0 0 0 0.12313 14.21 0.09505 0.0008 0.00513 0.00055 0.01443

5 PGE E-20 1 Summer 1 Part-Peak 0 0 0 0.09069 3.13 0.06261 0.0008 0.00513 0.00055 0.01443

5 PGE E-20 1 Summer 1 Off-Peak 0 0 0 0.0693 0 0.04122 0.0008 0.00513 0.00055 0.01443

5 PGE E-20 1 Winter 1 Part-Peak 0 0 0 0.08608 0.23 0.058 0.0008 0.00513 0.00055 0.01443

5 PGE E-20 1 Winter 1 Off-Peak 0 0 0 0.07016 0 0.04208 0.0008 0.00513 0.00055 0.01443

9 SCE TOU-8 1 Summer 1 On-Peak 0 0 0 0.14583 16.08 0.12613 0.00586 0.00513 0.00009 0.0109

9 SCE TOU-8 1 Summer 1 Mid-Peak 0 0 0 0.09443 4.53 0.07473 0.00586 0.00513 0.00009 0.0109

9 SCE TOU-8 1 Summer 1 Off-Peak 0 0 0 0.06222 0 0.04252 0.00586 0.00513 0.00009 0.0109

9 SCE TOU-8 1 Winter 1 Mid-Peak 0 0 0 0.08372 0 0.06402 0.00586 0.00513 0.00009 0.0109

9 SCE TOU-8 1 Winter 1 Off-Peak 0 0 0 0.05871 0 0.03901 0.00586 0.00513 0.00009 0.0109

9 SCE TOU-8 0 0 0 0 0 0 12.66 0 0 0 0 0

12 SDGE Sch A6-TOU 1 Summer 1 On-Peak 0 0 0 0.09887 15.46 0.08528 0.00298 0.00513 0.00044 0.00698

12 SDGE Sch A6-TOU 1 Summer 1 Semi-Peak 0 0 0 0.08127 0 0.06907 0.00178 0.00513 0.00044 0.00698

12 SDGE Sch A6-TOU 1 Summer 1 Off-Peak 0 0 0 0.06159 0 0.04983 0.00139 0.00513 0.00044 0.00698

12 SDGE Sch A6-TOU 1 Winter 1 On-Peak 0 0 0 0.09365 5.46 0.08056 0.00255 0.00513 0.00044 0.00698

12 SDGE Sch A6-TOU 1 Winter 1 Semi-Peak 0 0 0 0.0862 0 0.074 0.00178 0.00513 0.00044 0.00698

12 SDGE Sch A6-TOU 1 Winter 1 Off-Peak 0 0 0 0.06641 0 0.05498 0.00139 0.00513 0.00044 0.00698

12 SDGE Sch A6-TOU 0 0 0 0 0 0 13.26 0 0 0 0 0

Sample tariff detail


• Estimate gas cost for CHP prime movero Start with daily border prices and add

transportation componento Use Malin border price for PGE and Southern

California Border for SCG/SDGEo Gas cost escalated based on recent EAO gas

forecast report



• CHP prime mover details come from CEC sponsored report conducted by ICFo Heat rate, installed cost, waste heat

recovery, maintenance cost, etco Use DrCEUS loadshapes and technology

profiles to estimate impacts: generation, onsite use, export, and grid purchase



• Incorporate SGIP incentives and Federal tax credit for CHP

• Adoption modeling same as Residential sector PV/SHW model


Next Steps• Data updates• Revise Residential Sector model

o Incorporate retail rateso Use RASS survey to develop residential

profiles similar to method used in profiling CEUS survey for commercial sector

o Incorporate NEM benefits• Finalize Non-Residential PV model


Documents

California Energy Commission Customer-side Distributed Generation Impacts CED 2013 Preliminary Demand Analysis Working Group DG PUP June