Financial impacts of net-metered PV on utilities and ratepayers: A scoping study of two prototypical U.S. utilities

TLDR: Satchwell et al. as mentioned in this paper proposed Satchwell, Andrew; Mills, Andrew, Barbose, Galen; Wiser, Ryan; Cappers, Peter; Darghouth, Naim

Abstract: Author(s): Satchwell, Andrew; Mills, Andrew; Barbose, Galen; Wiser, Ryan; Cappers, Peter; Darghouth, Naim

Figures

Figure 23. Sensitivity of PV Impacts to Rate Design

Table 7. Rate Design Sensitivity Cases (Percent of Total Utility Revenues, without PV)

Figure 14. Reduction in Achieved After-Tax ROE

Table 1. Prototypical Utility Characterization: Key Inputs

Table 2. Sources of Modeled Reductions in Utility Costs from Customer-Sited PV

Figure 10. Reduction in Utility Revenue Requirements with Customer-Sited PV

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Lawrence Berkeley National Laboratory
Recent Work
Title
Financial Impacts of Net-Metered PV on Utilities and Ratepayers: A Scoping Study of Two
Prototypical U.S. Utilities
Permalink
https://escholarship.org/uc/item/0g70p291
Authors
Satchwell, Andrew
Mills, Andrew
Barbose, Galen
et al.
Publication Date
2014-09-24
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University of California

Financial Impacts of Net-Metered PV
on Utilities and Ratepayers: A Scoping
Study of Two Prototypical U.S.
Utilities
Primary authors
Andrew Satchwell, Andrew Mills, Galen Barbose
Contributing authors
Ryan Wiser, Peter Cappers, Naїm Darghouth
Environmental Energy
Technologies Division
September 2014
This work was supported by the Office of Energy Efficiency and Renewable Energy
(Solar Energy Technologies Office) of the U.S. Department of Energy under Contract
No. DE-AC02-05CH11231.
E
RNEST
O
RLANDO
L
AWRENCE
BERKELEY NATIONAL LABORATORY

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Ernest Orlando Lawrence Berkeley National Laboratory is an equal opportunity
employer.

Financial Impacts of Net-Metered PV on Utilities and Ratepayers:
A Scoping Study of Two Prototypical U.S. Utilities
Prepared for the
Office of Energy Efficiency and Renewable Energy
Solar Energy Technologies Office
U.S. Department of Energy
Primary Authors
Andrew Satchwell, Andrew Mills, Galen Barbose
Contributing Authors
Ryan Wiser, Peter Cappers, Naїm Darghouth
Ernest Orlando Lawrence Berkeley National Laboratory
1 Cyclotron Road, MS 90R4000
Berkeley CA 94720-8136
September 2014
This work was supported by the Office of Energy Efficiency and Renewable Energy (Solar
Energy Technologies Office) of the U.S. Department of Energy under Contract No. DE-AC02-
05CH11231.

ii
Acknowledgements
This work was supported by the Office of Energy Efficiency and Renewable Energy (Solar
Energy Technologies Office) of the U.S. Department of Energy under Contract No. DE-AC02-
05CH11231. We would particularly like to thank Elaine Ulrich, Kelly Knutsen, Christina
Nichols, and Minh Le of the U.S. Department of Energy (US DOE) for their support of this
project, and for supporting development of the financial model used in this study, we would like
to thank Larry Mansueti (US DOE). For providing comments on a draft of the report, the
authors would like to thank Susan Buller, Michael Bogyo, and Walter Campbell (Pacific Gas &
Electric), Beth Chacon (Xcel Energy), Leland Snook (Arizona Public Service), Mike Taylor and
Ted Davidovich (Solar Electric Power Association), Rick Gilliam (Vote Solar), Ron Binz (Public
Policy Consulting), Ron Lehr (America’s Power Plan), Steve Kihm (Energy Center of
Wisconsin), Carl Linvill (Regulatory Assistance Project), Tim Woolf and Jennifer Kallay
(Synapse Energy Economics), Michele Chait (Energy and Environmental Economics), Sonia
Aggarwal (Energy Innovation), Warren Leon (Clean Energy Group), Lisa Schwartz (Lawrence
Berkeley National Laboratory), Aliza Wasserman (National Governors Association), Virginia
Lacy (Rocky Mountain Institute), Wilson Rickerson (Meister Consultants Group), Joseph
Wiedman (Keyes, Fox & Wiedman LLP), Rebecca Johnson (Western Interstate Energy Board),
Ammar Qusaibaty and Daniel Boff (Mantech, contractor to the US DOE SunShot Program), and
Cynthia Wilson (US DOE). Of course, any remaining omissions or inaccuracies are our own.
We would also like to thank and acknowledge members of the Project Advisory Group for their
valuable feedback and input throughout the entire project:
Justin Baca Solar Energy Industry Association (SEIA)
Lori Bird National Renewable Energy Laboratory (NREL)
Nadav Enbar Electric Power Research Institute (EPRI)
Miles Keogh National Association of Regulatory Utility Commissions (NARUC)
Kelly Knutsen U.S. Department of Energy, SunShot Program
Virginia Lacy Rocky Mountain Institute (RMI)
Carl Linvill Regulatory Assistance Project (RAP)
Eran Mahrer Solar Electric Power Institute (SEPA)
Christina Nichols U.S. Department of Energy, SunShot Program
Lindsey Rogers Electric Power Research Institute (EPRI)
Richard Sedano Regulatory Assistance Project (RAP)
Tom Stanton National Regulatory Research Institute (NRRI)
Joseph Wiedman Keyes, Fox & Wiedman LLP

Frequently asked questions

Q1. What are the contributions mentioned in the paper "Financial impacts of net-metered pv on utilities and ratepayers: a scoping study of two prototypical u.s. utilities" ?

In this paper, the authors focus on the financial impact of solar PV systems on utility shareholders and ratepayers. 

Q2. What future works have the authors mentioned in the paper "Financial impacts of net-metered pv on utilities and ratepayers: a scoping study of two prototypical u.s. utilities" ?

Although by no means an exhaustive list, these areas for future research include the following, many of which will be addressed through followon work to the present study and refinements to LBNL ’ s utility financial model: • Benchmark the impacts of customer-sited PV against other factors affecting utility profitability and customer rates. In reality, however, the growth of customer-sited PV is often occurring in tandem with aggressive energy efficiency programs and other changes to electricity consumption patterns and end-uses, and adoption of distributed storage technologies could potentially expand greatly in the future. A wide variety of other measures have also been suggested and are worthy of further analysis, including ( among others ): stand-by rates, time-based pricing, two-way rates such as value-of-solar tariffs or feed-in tariffs, bi-directional distribution rates, non-fuel cost trackers, formula rates, multi-year rate plans, separate customer classes for PV customers, unbundled pricing of utility services, and performance-based ratemaking ( e. g., see Bird et al. Continued refinements to the methods and data used to estimate avoided costs – especially those related to avoided generation, transmission, and distribution capacity costs – will be critical to enabling reliable and utility-specific analyses of the shareholder and ratepayer impacts of customer-sited PV. 

Q3. how can a solar company reduce its ROE?

.......................................................................................................45 6.1 Decoupling and LRAM can moderate the ROE impacts from PV, though theireffectiveness depends critically on design and utility characteristics .......................... 46 6.2 Shareholder incentive mechanisms may be used to create utility earnings opportunities from customer-sited PV ................................................................................................ 49 6.3 Alternative ratesetting approaches may also significantly mitigate ROE impacts from customer-sited PV ........................................................................................................ 51 6.4 Increased fixed customer charges and demand charges can moderate the impact of PV on shareholder ROE, but in some cases may exacerbate those impacts ...................... 53 6.5 Utility ownership of customer-sited PV may offer sizable earnings opportunities, potentially offsetting much of the earnings impacts from PV that otherwise occur .... 56 6.6 Automatically counting customer-sited PV towards RPS compliance can substantiallymitigate the rate impacts from PV ................................................................................ 587. Conclusion ...............................................................................................................................60 7.1 Policy Implications ....................................................................................................... 60 7.2 Future Research ............................................................................................................ 

Q4. Why is the NE Utility able to achieve ROE?

Because the NE Utility does not own generation or transmission, the lost earnings opportunities from customer-sited PV are less severe, and thus impacts on earnings are similar to impacts on ROE, ranging from a 4% reduction under the low-end PV penetration scenario to a 15% reduction in earnings at the high-end PV penetration scenario. 

Q5. Why did the NE Utility achieve ROE reductions?

These ROE reductions occur because of the proportionally larger effect of customer-sited PV on utility revenues than on utility costs, under their base-case assumptions. 

Q6. What is the impact of customer-sited PV?

2 Specifically, penetration of customer-sited PV rises from zero in year-1 to levels ranging from 2.5% to 10% of retail sales in year-10, and then remains constant as a percentage of retail sales for the latter 10 years of the 20-year analysis period. 

Q7. What is the impact of customer-sited PV on earnings?

In the 2.5% PV penetration scenario, customersited PV led to a 0.1% increase in average rates for the SW Utility and a 0.2% increase for the NE Utility. 

Q8. What is the effect of customer-sited PV on earnings?

Under the scenario with PV penetration rising to 2.5% of retail sales (roughly the same order of magnitude as the current largest state markets), average achieved shareholder ROE was reduced by 2 basis points (a 0.3% decline in shareholder returns) for the SW utility and by 32 basis points (5%) for the NE Utility. 

Q9. What were the utility’s first and recent assumptions?

The utility shareholder and ratepayer impacts of customer-sited PV were first assessed under a set of base-case assumptions related to each utility’s regulatory and operating environment, in order to establish a reference point against which sensitivities and potential mitigation strategies could be measured. 

Q10. Why did the NE Utility have a larger ROE impact?

ROE impacts were larger for the wires-only NE utility, because of both its higher assumed growth in fixed costs and its proportionally smaller ratebase (as it does not own generation and transmission).• 

Q11. What is the highest penetration level of the study?

This is the highest penetration level examined within this study, and was used for the sensitivity cases in order to most clearly reveal the underlying relationships between the impacts of PV and the sensitivity variables (that is, to distinguish the signal from the noise). 

Q12. How did the average rates for the SW and NE Utilities compare?

Under the more aggressive 10% PV penetration scenario, average rates rose by 2.5% and 2.7% for the SW and NE Utilities, respectively.