Optimization Under Uncertainty of Thermal Storage-Based Flexible Demand Response With Quantification of Residential Users’ Discomfort

摘要: This paper presents a two-stage stochastic programming model for provision of flexible demand response (DR) based on thermal energy storage in the form hot water and/or building material. Aggregated residential electro-thermal technologies (ETTs), such as electric heat pumps and (micro-) combined power, are modeled unified nontechnology specific way. Day-ahead optimization is carried out considering uncertainty outdoor temperature, electricity consumption, dwelling occupancy, imbalance prices. Building flexibility exploited through specification deadband around set temperature or price discomfort applied to deviations from temperature. A new expected (ETD) metric defined quantify user discomfort. The efficacy exploiting various ETT following two approaches analyzed. utilization ETD facilitate quantification total (energy discomfort) cost also demonstrated. Such may be useful determination DR contracts up by service companies. Case studies U.K. users’ aggregation exemplify proposed possible reductions that achievable under different scenarios.