Modeling Distributed Generation Adoption using Electric Rate Feedback Loops

1. Modeling Distributed Generation Adoption using Electric Rate Feedback Loops USAEE Austin, TX – November 2012 Mark Chew, Matt Heling, Colin Kerrigan, Dié (Sarah) Jin, Abigail Tinker, Marc Kolb, Susan Buller, Liang Huang

2. Contents • Background/Motivation • Methodology • Results and Next Steps

3. Background (1/2) What is DG? In this context, DG is generation (primarily solar PV) on the customer side of the meter, where most of the power displaces grid-supplied energy. How Much DG is in PG&E’s Service Area? • 27% of nationwide rooftop systems are located within our service area, compared to 5% population • 69,000 rooftop PV systems installed as of July 31, 2012, growing at approximately 1,000/month • 693 MW -- 290 MW Res, 403 Non-Res solar DG, compared to over 20 GW max demand What are the Key Drivers? • Declining costs of PV technology • Availability of attractive ownership structures (lease, PPA) • High percentage of customer base is green-minded • High marginal customer rates, which customers can avoid paying through DG • Supportive policy in California (eg. direct subsidies, Net Energy Metering (NEM), Virtual NEM) • Political climate in California strongly supportive of DG

4. Background (2/2) Why is it significant to PG&E? • Continued growth without fundamental changes in rates will allow DG adopters to avoid paying for grid and other services that they receive • In California, residential customers are charged in 4 tiers, with marginal rates increasing with increasing monthly usage • Residential customers with the largest monthly usage are most incentivized to adopt DG; revenues lost from these adopters are much larger than costs avoided • “Cost shift” refers to the increase in costs among non-adopters, when policy allows DG adopters to pay less than their share of costs to the utility they generate • Because of present rate structure, a shrinking population high-use customers (those most likely to adopt) will cover these costs through higher rates Why is a model needed? • In a decoupled environment, high rates drive DG adoption; DG adoption drives rates even higher • Impacts of different policies are hard to intuitively predict because of the positive feedback dynamic • The model guides PG&E’s leadership on how to best enable a sustained DG industry without unfairly harming non-adopters  Goal of analytical effort is to evaluate the impact of different DG policies

5. Contents • Background/Motivation • Methodology • Results and Next Steps

6. DG Model Structure LCOE Levelized Cost of Energy Adoption LVOE Rates Levelized Value of Energy • LVOEs depend on previous years’ rates; LCOEs are based on technology cost and performance assumptions. • Adoption is based on Cost Effectiveness, which is based on the Levelized Cost of Energy (LCOE) of DG technologies and the Levelized Value (LVOE) produced by the DG units. • Rates module uses adoption information to calculate the new rates, which in turn are fed back into the LVOE module to restart the loop

7. Cost-Effectiveness Module Common Inputs • Capacity factor • Degradation rates • Discount rate LCOE Inputs LVOE Inputs • Capital costs (including finance structure) • O&M costs • Fuel costs • Electric efficiency • Thermal efficiency • Tax benefits • Incentives • Electric rates (forecast) • Gas rates (forecast) • Generation profiles • Compensation mechanisms (e.g., NEM, FiT) DG Technology Cost-Effectiveness Adoption Module

8. Customers Segmented to Forecast Adoption Historic Customer Characteristics • Adoption Behavior • Usage • Rate Type • Income • Homeownership • Geography Adoption and Energy Impacts to Rates Regression Model on Adoption from 2003-2010 Adoption Module Historic Cost Effectiveness Projected Cost Effectiveness Inputs from Cost Effectiveness Module

9. DG Adoption Causes Rate Increase 2 Cost of doing business RATE 1a v Procurement Cost Customer Charge Number of Customers * Capacity Cost Rev. Collected Rev.Required DemandCharge * Maximum KW Integration Cost Interconnection Cost kWh consumption Energy Charge * 1a Incentives & Admin Cost 1b Although RRQ will decrease because of net avoided cost (expense), this does not offset the lost revenue from decreasing kW and kWh sales.

10. Contents • Background/Motivation • Methodology • Results and Next Steps

11. Results Main Insights from ModelThe DG model is being used to prepare for high DG scenarios • The scenario that would create the greatest cost shift is “virtual net metering” – where all customers could count remotely located PV against their current consumption, under the current rate structure • Because of rate structure, costs caused by DG are shifted to customers who are unable to lower their usage or adopt DG – a fairness issue • Rate changes to address high bill impacts also significantly reduce cost shift from DG • Cost Shift • $

12. Next Steps Work with stakeholders on rate reform • Seek sustainable future with healthy DG market and customer choice • Explore alternatives to Net Energy Metering (NEM) that provide fair compensation • Reduce the highest rate tiers • Make rate structure less volumetric, to reflect actual costs of service

13. Thank You Mark Chew mark.chew@pge.com