Persistent social disparities in the adoption of distributed energy resources (DERs) have prompted calls for enabling more equitable uptake. However, there are indications that limits inherent to grid infrastructure may hinder DER adoption. In this study we analysed grid limits to new DER integration across California’s two largest utility territories. We found that grid limits reduce access to solar photovoltaics to less than half of households served by these two utilities, and may hinder California’s electric vehicle adoption and residential load electrification goals. We connected these results to demographic characteristics and found that grid limits also exacerbate existing inequities: households in increasingly Black-identifying and disadvantaged census block groups have disproportionately less access to new solar photovoltaic capacity based on circuit hosting capacity. Our results illuminate the need for equity goals to be an input in the design of policies for prioritizing grid upgrades.
This is a preview of subscription content, access via your institution
Open Access articles citing this article.
npj Urban Sustainability Open Access 30 June 2023
Nature Energy Open Access 06 February 2023
Charging infrastructure access and operation to reduce the grid impacts of deep electric vehicle adoption
Nature Energy Open Access 22 September 2022
Access Nature and 54 other Nature Portfolio journals
Get Nature+, our best-value online-access subscription
$29.99 / 30 days
cancel any time
Subscribe to this journal
Receive 12 digital issues and online access to articles
$119.00 per year
only $9.92 per issue
Rent or buy this article
Prices vary by article type
Prices may be subject to local taxes which are calculated during checkout
The definitions of features used in the demographic analyses are available in Supplementary Information Note 9 for convenience. Utility circuit data are available publicly from repositories that update approximately monthly and currently lack archive capability. The specific circuit data used in this study (from the last circuit map updates in 2019) are available at https://github.com/Energy-MAC/GridLimitsforDERs. Source data are provided with this paper.
The code is available at https://github.com/Energy-MAC/GridLimitsforDERs.
Carley, S. & Konisky, D. M. The justice and equity implications of the clean energy transition. Nat. Energy 5, 569–577 (2020).
Johnson, O. W. et al. Intersectionality and energy transitions: a review of gender, social equity and low-carbon energy. Energy Res. Soc. Sci. 70, 101774 (2020).
Reames, T. G. Distributional disparities in residential rooftop solar potential and penetration in four cities in the United States. Energy Res. Soc. Sci. 69, 101612 (2020).
Barbose, G., Forrester, S., Darghouth, N. & Hoen, B. Income Trends among U.S. Residential Rooftop Solar Adopters. Technical Report (Lawrence Berkeley National Laboratory, 2020).
Yu, J., Wang, Z., Majumdar, A. & Rajagopal, R. DeepSolar: a machine learning framework to efficiently construct a solar deployment database in the United States. Joule 2, 2605–2617 (2018).
Sunter, D. A., Castellanos, S. & Kammen, D. M. Disparities in rooftop photovoltaics deployment in the United States by race and ethnicity. Nat. Sustain. 2, 71–76 (2019).
Lukanov, B. R. & Krieger, E. M. Distributed solar and environmental justice: exploring the demographic and socio-economic trends of residential PV adoption in California. Energy Policy 134, 110935 (2019).
Feldman, D., Brockway, A. M., Ulrich, E. & Margolis, R. Shared Solar: Current Landscape, Market Potential, and the Impact of Federal Securities Regulation Report No. NREL/TP-6A20-63892 (National Renewable Energy Laboratory, 2015).
Margolis, R., Gagnon, P., Melius, J., Phillips, C. & Elmore, R. Using GIS-based methods and lidar data to estimate rooftop solar technical potential in US cities. Environ. Res. Lett. https://doi.org/10.1088/1748-9326/aa7225 (2017).
Gagnon, P., Margolis, R., Melius, J., Phillips, C. & Elmore, R. Estimating rooftop solar technical potential across the US using a combination of GIS-based methods, lidar data, and statistical modeling. Environ. Res. Lett. https://doi.org/10.1088/1748-9326/aaa554 (2018).
O’Shaughnessy, E., Barbose, G., Wiser, R., Forrester, S. & Darghouth, N. The impact of policies and business models on income equity in rooftop solar adoption. Nat. Energy 6, 84–91 (2021).
Coddington, M. et al. Updating Interconnection Screens for PV System Integration Report No. NREL/TP-5500-54063 (National Renewable Energy Laboratory, 2012); https://doi.org/10.2172/1036038
Smith, J., Rylander, M., Broderick, R. J. & Mather, B. Alternatives to the 15% Rule: Modified Screens and Validation (Electric Power Research Institute, 2015).
Cohen, M. A. & Callaway, D. S. Effects of distributed PV generation on California’s distribution system, part 1: engineering simulations. Sol. Energy 128, 126–138 (2016).
O’Shaughnessy, E., Barbose, G. & Wiser, R. Patience is a virtue: a data-driven analysis of rooftop solar PV permitting timelines in the United States. Energy Policy 144, 111615 (2020).
McAllister, R., Manning, D., Bird, L., Coddington, M. & Volpi, C. New Approaches to Distributed PV Interconnection: Implementation Considerations for Addressing Emerging Issues Report No. NREL/TP-6A20-72038 (National Renewable Energy Laboratory, 2019).
Bird, L. et al. Review of Interconnection Practices and Costs in the Western States Report No. NREL/TP-6A20-71232 (National Renewable Energy Laboratory, 2018).
Barnes, C. Comparing Utility Interconnection Timelines for Small-Scale Solar PV (EQ Research, 2015).
Decision Adopting Settlement Agreement Revising Distribution Level Interconnection Rules and Regulations – Electric Tariff Rule 21 and Granting Motions to Adopt the Utilities’ Rule 21 Transition Plans (California Public Utilities Commission, 2012).
Horowitz, K. A. W., Palmintier, B., Mather, B. & Denholm, P. Distribution system costs associated with the deployment of photovoltaic systems. Renew. Sustain. Energy Rev. 90, 420–433 (2018).
Liu, Y., Bebic, J., Kroposki, B., de Bedout, J. & Ren, W. Distribution system voltage performance analysis for high-penetration photovoltaics. In IEEE Energy 2030 Conference (IEEE, 2008); https://doi.org/10.1109/ENERGY.2008.4781069
Widén, J., Wäckelgård, E., Paatero, J. V. & Lund, P. Impacts of distributed photovoltaics on network voltages: stochastic simulations of three Swedish low-voltage distribution grids. Electr. Power Syst. Res. 80, 1562–1571 (2010).
Hoke, A., Butler, R., Hambrick, J. & Kroposki, B. Steady-state analysis of maximum photovoltaic penetration levels on typical distribution feeders. IEEE Trans. Sustain. Energy 4, 350–357 (2013).
Navarro, A., Ochoa, L. F. & Randles, D. Monte Carlo-based assessment of PV impacts on real UK low voltage networks. IEEE Power and Energy Society General Meeting 1–5 (IEEE, 2013); https://doi.org/10.1109/PESMG.2013.6672620
Nguyen, A. et al. High PV penetration impacts on five local distribution networks using high resolution solar resource assessment with sky imager and quasi-steady state distribution system simulations. Sol. Energy 132, 221–235 (2016).
Wolske, K. S. More alike than different: profiles of high-income and low-income rooftop solar adopters in the United States. Energy Res. Soc. Sci. 63, 101399 (2020).
Wang, Q., Kwan, M.-P., Fan, J. & Lin, J. Racial disparities in energy poverty in the United States. Renew. Sustain. Energy Rev. 137, 110620 (2021).
Faust, J. et al. CalEnviroScreen 3.0: Update to the California Communities Environmental Health Screening Tool. Technical Report (California Environmental Protection Agency and Office of Environmental Health Hazard Assessment, 2017).
Canepa, K., Hardman, S. & Tal, G. An early look at plug-in electric vehicle adoption in disadvantaged communities in California. Transp. Policy 78, 19–30 (2019).
Hsu, C.-W. & Fingerman, K. Public electric vehicle charger access disparities across race and income in California. Transp. Policy 100, 59–67 (2021).
Hoke, A. & Komor, P. Maximizing the benefits of distributed photovoltaics. Electr. J. 25, 55–67 (2012).
Walling, R. A., Saint, R., Dugan, R. C., Burke, J. & Kojovic, L. A. Summary of distributed resources impact on power delivery systems. IEEE Trans. Power Deliv. 23, 1636–1644 (2008).
Katiraei, F. & Romero Aguero, J. Solar PV integration challenges. IEEE Power Energy Mag. 9, 62–71 (2011).
Ismael, S. M., Abdel Aleem, S. H. E., Abdelaziz, A. Y. & Zobaa, A. F. State-of-the-art of hosting capacity in modern power systems with distributed generation. Renew. Energy 130, 1002–1020 (2019).
Zain ul Abideen, M., Ellabban, O. & Al-Fagih, L. A review of the tools and methods for distribution networks’ hosting capacity calculation. Energies 13, 2758 (2020).
Mulenga, E., Bollen, M. H. J. & Etherden, N. A review of hosting capacity quantification methods for photovoltaics in low-voltage distribution grids. Electr. Power Energy Syst. 115, 105445 (2020).
Final Integration Capacity Analysis Working Group Report (Integration Capacity Analysis Working Group, California Public Utilities Commission, 2017).
Final Integration Capacity Analysis Working Group Long Term Refinements Report (Integration Capacity Analysis Working Group, California Public Utilities Commission, 2018).
Statistics and Charts (2020) (California Solar Initiative Program Administrators, GRID Alternatives, California Investor Owned Utilities & California Public Utilities Commission, accessed 28 March 2020); https://www.californiadgstats.ca.gov/charts/
California’s Distributed Energy Resources Action Plan: Aligning Vision and Action (California Public Utilities Commission, 2017).
2019 Building Energy Efficiency Standards for Residential and Nonresidential Buildings (California Energy Commission, 2018).
Borenstein, S. Private net benefits of residential solar PV: the role of electricity tariffs, tax incentives, and rebates. J. Assoc. Environ. Resour. Econ. https://doi.org/10.1086/691978 (2017).
2021 General Rate Case: Grid Modernization, Grid Technology, and Energy Storage (Southern California Edison, California Public Utilities Commission, 2019).
Order Instituting Rulemaking to Consider Streamlining Interconnection of Distributed Energy Resources and Improvements to Rule 21 (California Public Utilities Commission, 2017).
Brockway, A. M. & Delforge, P. Emissions reduction potential from electric heat pumps in California homes. Electr. J. 31, 44–53 (2018).
Joint Reply Comments of Southern California Edison Company (U 338-E), San Diego Gas & Electric Company (U 902-E), and Pacific Gas and Electric Company (U 39-E) on the Administrative Law Judge’s Ruling Requesting Comments on Refinements to the Integration Capacity Analysis (Southern California Edison, Pacific Gas and Electric, and San Diego Gas and Electric, California Public Utilities Commission, 2019).
Sergi, B. J. et al. Optimizing emissions reductions from the U.S. power sector for climate and health benefits. Environ. Sci. Technol. 54, 7513–7523 (2020).
Krieger, E. M., Casey, J. A. & Shonkoff, S. B. C. A framework for siting and dispatch of emerging energy resources to realize environmental and health benefits: case study on peaker power plant displacement. Energy Policy 96, 302–313 (2016).
Burillo, D. et al. Climate Change in Los Angeles County: Grid Vulnerability to Extreme Heat. A Report for California’s Fourth Climate Change Assessment Report No. CCCA4-CEC-2018-013 (California Energy Commission, 2018).
Esri. ArcGIS Desktop 10.6.1 quick start guide. (2017); https://desktop.arcgis.com/en/arcmap/10.6/get-started/setup/arcgis-desktop-quick-start-guide.htm
Patterson, W. Projection and Datum Guidelines. California Department of Fish and Wildlife (2018); https://nrm.dfg.ca.gov/FileHandler.ashx?DocumentID=109326&inline
2015 TIGER/Line Shapefiles (United States Census Bureau, accessed 28 September 2018); https://www.census.gov/geo/maps-data/data/tiger-line.html
California Protected Areas Database Version 2019b (GreenInfo Network, accessed 14 January 2020); https://data.cnra.ca.gov/dataset/california-protected-areas-database
California Conservation Easement Database Version 2019 (GreenInfo Network, accessed 14 January 2020); https://data.cnra.ca.gov/dataset/california-conservation-easement-database
Military Installations, Ranges, and Training Areas (2017) (United States Department of Defense, accessed 2 March 2019); https://catalog.data.gov/dataset/military-installations-ranges-and-training-areas
California Electric Utility Service Areas (California Energy Commission, 2015); https://www.energy.ca.gov/maps/serviceareas/electric_service_areas.html
Integration Capacity Analysis (ICA) Map and User Guide Version 1.4 (Pacific Gas and Electric, 2019); https://www.pge.com/en_US/for-our-business-partners/distribution-resource-planning/distribution-resource-planning-data-portal.page
Distribution Resources Plan External Portal: Customer Type Breakdown (2019) (Southern California Edison, accessed 18 September 2019); https://ltmdrpep.sce.com/drpep/
2011-2015 ACS 5-Year Estimates (2015) (United States Census Bureau, accessed 25 November 2018); https://www.census.gov/programs-surveys/acs/technical-documentation/table-and-geography-changes/2015/5-year.html
The R Project for Statistical Computing. R version 3.6.1. (2019); https://cran.r-project.org/src/base/R-3/
Distribution Resources Plan External Portal and Interactive User Guide (2019) (Southern California Edison, accessed 20 December 2019); https://ltmdrpep.sce.com/drpep/
Barbose, G. & Darghouth, N. Tracking the Sun: Pricing and Design Trends for Distributed Photovoltaic Systems in the United States (Lawrence Berkeley National Laboratory, 2019).
Southern California Edison Company’s (U 338-E) Demonstration Projects A and B Final Reports (Southern California Edison, California Public Utilities Commission, 2016).
Rockzsfforde, R. R. Comparative Analysis of Utility Services and Rates in California (California Public Utilities Commission, 2015).
Gagnon, P. et al. Rooftop Solar Photovoltaic Technical Potential in the United States: A Detailed Assessment Report No. NREL/TP6A20-65298 (National Renewable Energy Laboratory, 2016).
Zip Code Tabulation Areas (2010) (United States Census Bureau, accessed 3 August 2020); https://www.census.gov/programs-surveys/geography/guidance/geo-areas/zctas.html
Szinai, J. K., Sheppard, C. J. R., Abhyankar, N. & Gopal, A. R. Reduced grid operating costs and renewable energy curtailment with electric vehicle charge management. Energy Policy 136, 111051 (2020).
Hurlbut, D., McLaren, J., Koebrich, S., Williams, J. & Chen, E. Electric Vehicle Charging Implications for Utility Ratemaking in Colorado. Background Research for the Colorado Public Utilities Commission Report No. NREL/PR-6A20-73303 (National Renewable Energy Laboratory, 2019); https://doi.org/10.2172/1503821
Palmgren, C., Stevens, N., Goldberg, M., Barnes, R. & Rothkin, K. 2009 California Residential Appliance Saturation Study Report No. CEC-200-2010-004-ES (KEMA, California Energy Commission, 2010).
Energy Efficiency Calculator: PG&E Residential Shape Viewer Version 2.0 (Energy and Environmental Economics, 2017); https://www.ethree.com/public_proceedings/energy-efficiency-calculator/
Several individuals provided valuable assistance: S. Elmallah on load DER capacity estimates, B. Dawson on SCE circuit data, J. Dees on spatial mapping in GIS and J. D. Lara on initial aid with utility circuit data. Additionally, we are grateful to the Energy Modeling, Analysis, and Control Research Group at UC Berkeley for helpful discussions. The authors acknowledge the generous support of the Sloan Foundation under grant no. G-2017-9812 (D.C.), and the National Science Foundation Graduate Research Fellowship under grant no. DGE 1752814 (A.M.B.).
The authors declare the following competing interests: since completing the research described herein, J.C. has accepted employment at SCE. A.M.B. and D.C. have no competing interests.
Peer review information Nature Energy thanks João P. S. Catalão, Antonio Moreno-Munoz and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
High-resolution version of Fig. 1a, showing hosting capacity limits for PV per household across PG&E and SCE service territories.
High-resolution version of Fig. 1b, showing hosting capacity limits for PV with Operational Flexibility limits enforced per household across PG&E and SCE service territories.
High-resolution version of Fig. 1c, showing hosting capacity limits for Load per household across PG&E and SCE service territories.
Statistical and geospatial source data (PGE_limitsdemo.csv, SCE_limitsdemo.csv and GridLimits.gdb).
Statistical source data (fig2a_sourcedata.csv and fig2b_sourcedata.csv).
Statistical source data (fig3a_sourcedata.csv and fig3b_sourcedata.csv).
Statistical source data (fig4a_sourcedata.csv and fig4b_sourcedata.csv).
Statistical source data (fig5a_sourcedata.csv, fig5b_sourcedata.csv, fig5c_sourcedata.csv, fig5d_sourcedata.csv, fig5e_sourcedata.csv and fig5f_sourcedata.csv).
About this article
Cite this article
Brockway, A.M., Conde, J. & Callaway, D. Inequitable access to distributed energy resources due to grid infrastructure limits in California. Nat Energy 6, 892–903 (2021). https://doi.org/10.1038/s41560-021-00887-6
This article is cited by
Nature Energy (2023)
Nature Energy (2023)
npj Urban Sustainability (2023)
Charging infrastructure access and operation to reduce the grid impacts of deep electric vehicle adoption
Nature Energy (2022)
Nature Communications (2022)