Toward Optimal Energy Management of Microgrids via Robust Two-Stage Optimization

Abstract

This paper considers energy management in a grid-connected microgrid which has multiple conventional generators (CGs), renewable generators and energy storage systems (ESSs). A robust two-stage optimization approach is presented to schedule the energy generation under uncertainties, aimed at minimizing the long-term average operating cost subject to realistic operational and service constraints. The first stage of optimization determines hourly unit commitment of the CGs via a day-ahead scheduling, and the second stage performs economic dispatch of the CGs, ESSs, and energy trading via a real-time scheduling. The combined solution meets the need of handling large uncertainties in the load demands and renewable generation, and provides an efficient solution under limited computational resource which approximately optimizes the long-term average operating cost while meeting the quality-of-service requirements. The performance of the proposed strategy is evaluated by simulations based on real load demand and renewable generation data.