Abstract
As renewable electricity generation continues to increase in the United States (US), considerable effort goes into matching heterogeneous supply to demand at a subhour time-step. As a result, some electric providers offer incentive-based programs for residential consumers that aim to reduce electric demand during high-demand periods. There is little research into determinants of consumer response to incentive-based programs beyond typical sociodemographic characteristics. To add to this body of literature, this paper presents the findings of a dichotomous choice contingent valuation (CV) survey targeting US ratepayers’ participation in a direct-load-control scheme utilizing a smart thermostat designed to reallocate consumer electricity demand on summer days when grid stress is high. Our results show approximately 50% of respondents are willing to participate at a median willingness-to-accept (WTA) figure of USD 9.50 (95% CI: 3.74, 15.25) per month that lasts for one summer (June through August)—or slightly less than USD 30 per annum. Participation is significantly affected by a respondent’s attitudes and preferences surrounding various environmental and institutional perspectives, but not by sociodemographic characteristics. These findings suggest utilities designing direct-load-control programs may improve participation by designing incentives specific to customers’ attitudes and preferences.
Highlights
IntroductionThe United States (US) electric grid has seen ongoing modernization efforts to incorporate renewable energy sources (e.g., hydroelectric, wind, biomass, solar, and geothermal) as well as increasing reliability and resilience (e.g., battery storage, distributed-feeder microgrids)
The United States (US) electric grid has seen ongoing modernization efforts to incorporate renewable energy sources as well as increasing reliability and resilience
Three versions of Equation (1) are estimated: (1) a parsimonious model in which only the offered payment amount is considered, (2) a model which includes the attitudes and preferences listed in Table 2, and (3) a model which includes all the covariates listed in Interpretation of these point estimates is that a one-unit increase from the mean, on average, results in a point estimate percent change in the likelihood of a respondent voting yes to the smart thermostat program
Summary
The United States (US) electric grid has seen ongoing modernization efforts to incorporate renewable energy sources (e.g., hydroelectric, wind, biomass, solar, and geothermal) as well as increasing reliability and resilience (e.g., battery storage, distributed-feeder microgrids). Wind and solar generation generally do not correspond to the demand cycles of residential customers, with a majority of production occurring throughout the day when customers are away from their homes This mismatch has spurred investments and research into programs designed to reduce residential electricity use during peak hours, collectively known as demand response programs [2]. Price-based schemes attempt to alter residential electricity consumption by shifting demand to off-peak times through a dynamic pricing structure These programs charge more for electricity when the grid is strained, and the marginal cost of production is high, and charge less when the demand is low. A large majority of demand response research centers around price-based programs and their efficacy and retention rate
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