On the Network Value of Behind-the-Meter Solar PV plus Energy - PowerPoint PPT Presentation

On the Network Value of Behind-the-Meter Solar PV plus Energy Storage: The Importance of Retail Rate Design Richard Boampong and David P. Brown Presented By: David P. Brown Assistant Professor University of Alberta 36 th Annual USAEE/IAEE North American Conference

Distributed Energy Resources • Dramatic decline in costs of solar and storage technologies (Bloomberg NEF) – 65% decline in total PV install costs 2010 – 2017 – 80% decline in Li-ion battery prices 2010 – 2017 • Favorable policies and cost reductions ➔ substantial increase in rooftop solar – 2017: 16,224 MWs of rooftop solar in the U.S. (EIA, 2018) • Energy Storage Mandates by 2030: California 1000 MWs; New York 1500 MWs, New Jersey 2000 MWs - California’s Self Generation Incentive Program (SGIP): >200 MWhs BTM • Anticipate continued growth in behind-the- meter solar PV and solar PV plus storage distributed energy resources (DERs)

Key Regulatory Issues 1. Solar PV output growth • Suppresses prices midday, but increase evening prices (Bushnell and Novan, 2018) • Can elevate the value of energy storage • Existing retail prices have on-peak hours from 12 – 6 PM 2. Cost-Shifting Concerns • Growing concerns that utility revenues decline faster than avoided costs as distributed solar is deployed • Driven in part by volumetric retails rates utilized to recover fixed and variable network costs – Under common Net Energy Metering (NEM) policies • Cost-shifting concerns to non-solar consumers Challenges have led to heated debates over retail rate design and DER compensation policies Source: CAISO • 2017: 249 regulatory actions were taken in the U.S. • Debates over levels and features of rates

Research Methodology Context : – California commercial and industrial (C&I) consumer’s face three -part tariffs • Time-of-Use volumetric rates, demand charges, and fixed charges – Growing interest in behind-the-meter battery storage (particular for C&I consumers) – Demand charges can reflect 30 – 70% of a C&I consumer’s bill (NREL, 2017) – Two common rate structures: Maximum Demand-Charges (MDCs) or Volumetric dominant • Both have the same cost-recovery features (SCE, 2017) Proposed Rate Changes: – New rates shifts on-peak periods from 12:00PM – 6:00 PM to 4:00 PM – 9:00 PM – Separate rates specifically targeted to customers with DER (“TOUR” rates) ❖ This Paper: • Analyze the impact of existing and proposed retail tariffs on the private investment decisions, network value (avoided cost), and cost-shifting concerns of behind-the-meter rooftop solar and rooftop solar plus energy storage – Prior work largely focuses on solar PV or impacts on rates on the private financial viability of battery storage – Key additional feature: Operational behavior of a battery system changes as rates vary

Research Methodology • Utilize DER-CAM (LBNL, 2018) – Dynamic Programming Problem – Optimal Capacity Investment – Optimal Charge and Discharge Decisions • Hourly demand data of 22 commercial and industrial facilities in Southern California from EnerNoC’s (2013) – Diverse set of load profiles • Geo-located Hourly solar radiation and weather information from the National Solar Radiation Data • Southern California Edison’s (SCE) existing and proposed C&I rates – Existing and Proposed Rates (TOUB and TOUR) – Counterfactual Coin. Peak MDCs

Research Methodology • Avoided Cost Model [ACM] (E3, 2018) – Computes marginal avoided cost at the hourly level – Breaks CA down into 16 Climate Zones – Decomposes costs into various components – ACM utilized to design TOU rate structures (CPUC, 2015) • Instrument to understand the value of DERs • Captures broader time-varying energy and capacity-related costs • Consider two cases: (i) Endogenous Capacity (ii) Exogenous Capacity (sized to a facility’s demand profile) • Use data on demand + solar irradiation + tariff structures + avoided costs + DER technology costs, efficiencies, and characteristics – Simulate out a representative year – Compare to 20-year levelized cost values Focus: Exogenous Capacity Case

Avoided Cost by Cost Category

Primary Findings: Private Financial Value • Existing Tariffs generate sizable savings – most pronounced under TOUR • Savings decline substantially under Proposed Tariffs – lower prices for midday solar output • Bill savings of energy storage magnified under TOUB rate class – driven by MDC savings via battery discharge on high demand days

Primary Findings: Battery Discharge Decisions • TOUB: Target Private On-Peak MDCs • TOUR: Arbitrage on peak to off-peak differential • Change in on-peak period + unique incentives impact discharge decisions in important ways

Primary Findings: Avoided Costs • Solar PV avoided costs largely energy-related (77%) – capacity constraints arise in the evening • Storage elevates avoided costs, but effects vary critically across tariffs • TOUB to TOUB Proposed ➔ lower capacity-related avoided costs – Driven by incentive to avoid private MDCs rather than system constraints • TOUR to TOUR Proposed results in a sizable increase in capacity-related avoided costs

Primary Findings: Cost-Shifting Concerns • Existing tariffs yield sizable cost-shifting concerns (particularly, under TOUR) • Shift to proposed tariffs systematically reduces these cost-shifting concerns • Cost-shifting measure higher under TOUR rate class (high volumetric charges) compared to TOUB (heavier reliance on MDCs) • Addition of storage elevates cost-shifting measure under current tariffs

Conclusions • Retail rate features have important impacts on financial value, avoided costs, and cost-shifting concerns – Important when regulator is limited in their instruments • Shift in on-peak hour to better reflect system constraints does not necessarily elevate avoided costs (e.g., TOUB Proposed) – Does elevate capacity- related avoided costs substantially under TOUR rate class (which is the “DER rate class”) • Shift in on-peak rates alleviates cost-shifting concerns substantially – Reduced solar PV compensation – Cost-shifting measure is highest under high volumetric dominant tariffs (lowest with MDC-heavy tariffs) – Battery storage can increase cost-shifting measure • Tariffs that maximize avoided costs may be at conflict with those that minimize cost-shifting concerns • Results carry over to the setting with endogenous capacity investment – Existing Tariffs: High solar PV investment, avoided costs, and cost-shifting concerns – Proposed Tariffs: Limited solar PV investment, lower avoided costs, and cost-shifting concerns – Battery investment largely driven by incentive to avoid MDCs, limited investment under TOUR rate class • Future Work: More granular avoided cost estimates, consider different solar PV configurations (e.g., west- facing panels), and consider alternative rate designs (e.g., with increased time-varying granularity)

Appendix: Maximum Demands Results

Appendix: NPV Results

Appendix: Aggregated Results

Appendix: Endogenous Results

Appendix: Endogenous Results

Appendix: Endogenous Results

Appendix: Endogenous Results