Real-Time Decision Making Model for Thermostatically Controlled Load Aggregators by Natural Aggregation Algorithm

With the development of Building-to-Grid (B2G) technology, Thermostatically Controlled Loads (TCLs) have been receiving increasing attention because promising candidates for Demand Response (DR) programs. This paper studies real-time operation schemes of TCL aggregators in the power market. The contribution of this paper is to consider TCL aggregators as bidding players participating in the day-ahead market, unlike existing works which often treat TCL aggregators as ancillary service providers. We investigate the real-time operations of TCL aggregators after the determinations of day-ahead load shedding volumes. The proposed model aims to minimize the operation costs of the TCL aggregator in the real-time regulation market. A Rolling Horizon Optimization (RHO) technique is utilized to mitigate the impacts of forecasting errors. And a new metaheuristic algorithm, i.e. Natural Aggregation Algorithm (NAA), is applied here to solve the proposed model. Experiments are conducted to validate the proposed method.