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 36th 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

• 2017: 249 regulatory actions were taken in the U.S.
• Debates over levels and features of rates

Source: CAISO

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