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Inequitable access to distributed energy resources due to grid infrastructure limits in California


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.

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Fig. 1: Household access varies by DER type and location.
Fig. 2: Results for household access to PV and load DERs.
Fig. 3: Results for household access to PV DERs considering grid (remaining plus existing capacity) and building suitability limits.
Fig. 4: Hosting capacity results for race and ethnicity variables.
Fig. 5: Hosting capacity for additional demographic variables.

Data availability

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 Source data are provided with this paper.

Code availability

The code is available at


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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.).

Author information

Authors and Affiliations



A.M.B., J.C. and D.C. conceptualized the research. A.M.B. and J.C. performed the research and wrote the paper. D.C. guided the research and edited the paper.

Corresponding author

Correspondence to Duncan Callaway.

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Competing interests

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.

Additional information

Peer review informationNature 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.

Extended data

Extended Data Fig. 1 Grid limits for distributed energy resources: PV.

High-resolution version of Fig. 1a, showing hosting capacity limits for PV per household across PG&E and SCE service territories.

Extended Data Fig. 2 Grid limits for distributed energy resources: PV, with OpFlex limits.

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.

Extended Data Fig. 3 Grid limits for distributed energy resources: Load.

High-resolution version of Fig. 1c, showing hosting capacity limits for Load per household across PG&E and SCE service territories.

Supplementary information

Supplementary Information

Supplementary Notes 1–9, Figs. 1–8, Tables 1–8 and references.

Source data

Source Data Fig. 1

Statistical and geospatial source data (PGE_limitsdemo.csv, SCE_limitsdemo.csv and GridLimits.gdb).

Source Data Fig. 2

Statistical source data (fig2a_sourcedata.csv and fig2b_sourcedata.csv).

Source Data Fig. 3

Statistical source data (fig3a_sourcedata.csv and fig3b_sourcedata.csv).

Source Data Fig. 4

Statistical source data (fig4a_sourcedata.csv and fig4b_sourcedata.csv).

Source Data Fig. 5

Statistical source data (fig5a_sourcedata.csv, fig5b_sourcedata.csv, fig5c_sourcedata.csv, fig5d_sourcedata.csv, fig5e_sourcedata.csv and fig5f_sourcedata.csv).

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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).

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