Estimating the Profile of Incentive-Based Demand Response (IBDR) by Integrating Technical Models and Social-Behavioral Factors
| Autor: | Qingxin Shi, Fangxing Li, Andrea Mammoli, Chien-fei Chen |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
General Computer Science
Computer science business.industry 020209 energy media_common.quotation_subject 020208 electrical & electronic engineering 02 engineering and technology Environmental economics Grid Payment Load profile Demand response Load management Electric power system Incentive HVAC 0202 electrical engineering electronic engineering information engineering business media_common |
| Zdroj: | IEEE Transactions on Smart Grid. 11:171-183 |
| ISSN: | 1949-3061 1949-3053 |
| DOI: | 10.1109/tsg.2019.2919601 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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