LAUSR

A novel hierarchical Energy Management System (EMS) framework is proposed for the incorporation of Thermostatically Controlled Loads (TCLs) in the provision of ancillary services, namely frequency and voltage control of a microgrid. The TCL population is aggregated as a function of the ambient temperature, voltage and frequency using a neural network-based approach. The proposed EMS comprises primary and secondary control levels. TCLs’ participation in the primary control is selected to be semi-autonomous in order to obtain a fast response with low communication burden. The secondary control is centralized and aims to find the optimal dispatch of regulating resources including TCL clusters in order to minimize frequency and voltage deviations as well as grid operation cost. The secondary control relies on a Trust-Region Power Flow (PF)-based multi-objective optimization. Simulation results demonstrate that the participation of TCLs in the proposed EMS does not compromise customer comfort while short cycling and the number of switching events are minimized.