An Operational Planning Framework for Large-Scale Thermostatically Controlled Load Dispatch

This paper proposes an operational planning framework for large-scale thermostatically controlled load (TCL) dispatch. The proposed framework consists of a day-ahead scheduling stage and a real-time operation stage. A thermal comfort model is employed to estimate the occupants' thermal comfort degree. A self-adaptive TCL grouping method is proposed to group the TCLs based on the similarity of the TCL model parameters. Then, a hierarchical day-ahead scheduling model is proposed to make the optimal dispatch plan for the TCL aggregators based on the day-ahead forecasted information. In the real-time operation stage, a predictive control model is proposed for the TCL aggregators to make the real-time TCL dispatch decision based on the updated real-time information. The simulation results prove the efficiency of the proposed framework.