A utility-level analysis of residential electricity use: Governance, pricing, and incentive programs in the Southeastern U.S.

This study examines utility-level variation in annual residential electricity consumption across Georgia and North Carolina, focusing on utility governance, electricity pricing, service-territory characteristics, and utility-run incentive programs. We construct a hand-collected inventory of 699 residential energy programs across 193 electric utilities and merge it with utility-level data, such as electricity consumption, rate, energy burden, climate, demographics and housing conditions, and EV charging-station data. The analytic sample includes 105 utilities with complete consumption and covariate data. Our results show that each additional EV program is associated with approximately 310 kWh (2.5%) higher annual per-household use, even after controlling for public EV charging-station density. Cooperative utilities initially exhibit higher household consumption than municipal utilities, but this difference loses statistical significance after accounting for program offerings and demographic factors. A one-cent/kWh higher electricity rate is associated with a 227 kWh (1.8%) to 334 kWh (2.7%) reduction in annual per-household electricity consumption, which may reflect both efficiency-driven conservation and energy-limiting behaviors. Prevalence of energy burden is associated with more electricity use after controlling for income, suggesting structural inefficiency in high-burden utility territories. These findings indicate that utility incentive programs should be paired with managed charging, demand response, targeted efficiency investment, and time-of-use pricing.

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Publication Details

Journal
Energy Policy
Published
2026-06-09
DOI
https://doi.org/10.1016/j.enpol.2026.115413
Primary Topic
Smart Grid Energy Management
Type
article
Field-Weighted Citation Impact
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article

A utility-level analysis of residential electricity use: Governance, pricing, and incentive programs in the Southeastern U.S.

Chien Chen, John Dong-Yoon Kim, Brian An, Geyu Lyu et al.
Energy Policy
Smart Grid Energy Management
article

A utility-level analysis of residential electricity use: Governance, pricing, and incentive programs in the Southeastern U.S.

Chien Chen, John Dong-Yoon Kim, Brian An, Geyu Lyu, Yu Wang
article en

Abstract

This study examines utility-level variation in annual residential electricity consumption across Georgia and North Carolina, focusing on utility governance, electricity pricing, service-territory characteristics, and utility-run incentive programs. We construct a hand-collected inventory of 699 residential energy programs across 193 electric utilities and merge it with utility-level data, such as electricity consumption, rate, energy burden, climate, demographics and housing conditions, and EV charging-station data. The analytic sample includes 105 utilities with complete consumption and covariate data. Our results show that each additional EV program is associated with approximately 310 kWh (2.5%) higher annual per-household use, even after controlling for public EV charging-station density. Cooperative utilities initially exhibit higher household consumption than municipal utilities, but this difference loses statistical significance after accounting for program offerings and demographic factors. A one-cent/kWh higher electricity rate is associated with a 227 kWh (1.8%) to 334 kWh (2.7%) reduction in annual per-household electricity consumption, which may reflect both efficiency-driven conservation and energy-limiting behaviors. Prevalence of energy burden is associated with more electricity use after controlling for income, suggesting structural inefficiency in high-burden utility territories. These findings indicate that utility incentive programs should be paired with managed charging, demand response, targeted efficiency investment, and time-of-use pricing.

Energy PolicyVol. 217
University of North Carolina at Charlotte (US), Georgia Institute of Technology (US), Korea Advanced Institute of Science and Technology (KR), Iowa State University (US), NOAA National Weather Service (US), Transcend Engineering (United States) (US)
Openalex Percentile: Top 10%
Smart Grid Energy Management
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