Publication | Closed Access
Estimating the Profile of Incentive-Based Demand Response (IBDR) by Integrating Technical Models and Social-Behavioral Factors
125
Citations
32
References
2019
Year
EngineeringApplied EconomicsEnergy EfficiencyConsumer ResearchLoad ControlExperimental EconomicsEconomic AnalysisSocial-behavioral FactorsElectricity SupplyQuantitative ManagementEnergy Demand ManagementConsumer ChoiceDemand ManagementEconomicsPublic PolicyTechnical ModelsDemand ForecastingIbdr ParticipationMarketingBehavioral EconomicsSmart GridEnergy ManagementEnergy PolicyBusinessPeak LoadIncentive-centered DesignDemand ResponseIncentive-based Demand ResponseIncentive Model
Demand response (DR) has been widely recognized as an important approach to balance the power grid and reduce peak load of power systems. In order to better estimate the capability and the expense of peak load reduction through DR, we need to obtain the residential load profile and customers' attitudes toward DR programs. Based on a large-scale online survey collected among over 1500 customers from New York and Texas in the U.S., this paper investigates the relationships among household appliance activities (e.g., electric water heater and air conditioner), load profiles, and incentive-based DR (IBDR) participation for peak load curtailment through reward payment. The daily load profiles of major home appliances are developed. Additionally, this paper estimates the expense of reducing the yearly peak of the local grid load. Finally, this paper addresses the importance of investigating the multifaceted factors of affecting IBDR participation and provides useful suggestions to utility companies when implementing DR programs.
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