What Drives U.S. Energy Storage Deployment? A State-Level Analysis of Residential, C&I, and Utility-Scale Markets

This study examines the factors associated with Energy Storage System (ESS) deployment across Residential, Commercial & Industrial (C&I), and Utility-scale markets in the United States. Using state-level data from the U.S. Energy Information Administration (EIA), the National Solar Radiation Database (NSRDB), and other public energy datasets, the analysis evaluates relationships between installed ESS capacity and solar resource availability (GHI), actual solar PV deployment, electricity prices, electricity demand, and grid reliability. Pearson and Spearman correlation analyses reveal substantial differences among these potential market drivers. Solar PV deployment demonstrates the strongest and most consistent positive association with ESS deployment across all three market segments, while underlying solar resource availability alone shows considerably weaker relationships. Electricity demand is particularly relevant to Utility-scale ESS deployment, whereas electricity prices exhibit more moderate and segment-dependent relationships. Grid reliability, measured by the System Average Interruption Duration Index (SAIDI), shows no statistically significant association with ESS deployment across the three segments. These findings suggest that current U.S. ESS deployment is more closely associated with realized solar-market development than with natural solar resources or grid reliability alone. The study provides a state-level analytical framework for understanding differences in ESS deployment across U.S. market segments and establishes a foundation for future research on solar-market growth and emerging energy-storage opportunities.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-09-05
DOI
https://doi.org/10.5281/zenodo.22313635
Primary Topic
Smart Grid Energy Management
Type
article
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article

What Drives U.S. Energy Storage Deployment? A State-Level Analysis of Residential, C&I, and Utility-Scale Markets

Ara Ko
Zenodo (CERN European Organization for Nuclear Research)
Smart Grid Energy Management
article

What Drives U.S. Energy Storage Deployment? A State-Level Analysis of Residential, C&I, and Utility-Scale Markets

Ara Ko
article en

Abstract

This study examines the factors associated with Energy Storage System (ESS) deployment across Residential, Commercial & Industrial (C&I), and Utility-scale markets in the United States. Using state-level data from the U.S. Energy Information Administration (EIA), the National Solar Radiation Database (NSRDB), and other public energy datasets, the analysis evaluates relationships between installed ESS capacity and solar resource availability (GHI), actual solar PV deployment, electricity prices, electricity demand, and grid reliability. Pearson and Spearman correlation analyses reveal substantial differences among these potential market drivers. Solar PV deployment demonstrates the strongest and most consistent positive association with ESS deployment across all three market segments, while underlying solar resource availability alone shows considerably weaker relationships. Electricity demand is particularly relevant to Utility-scale ESS deployment, whereas electricity prices exhibit more moderate and segment-dependent relationships. Grid reliability, measured by the System Average Interruption Duration Index (SAIDI), shows no statistically significant association with ESS deployment across the three segments. These findings suggest that current U.S. ESS deployment is more closely associated with realized solar-market development than with natural solar resources or grid reliability alone. The study provides a state-level analytical framework for understanding differences in ESS deployment across U.S. market segments and establishes a foundation for future research on solar-market growth and emerging energy-storage opportunities.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 19%
Smart Grid Energy Management
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