An Optimal Day-Ahead Operation Strategy for Hybrid Energy Microgrid

Abstract

This paper proposes a strategy for optimal day-ahead operation of a microgrid. The latter includes hybrid energy resources and an energy storage system (ESS). The forecasted day-ahead hourly average of metrological data and loads are fed into the energy management system (EMS). Accordingly, it decides the day-ahead hourly active and reactive power shares of each energy source. It also identifies the ESS charging/discharging periods and the tap setting of the main grid coupling transformer. The overall objective is to maximize the microgrid profit satisfying all constraints. The microgrid purchases/sells active and reactive powers from/to the main grid with time-varying energy price. The day-ahead operation of the microgrid is formulated as an optimization problem solved by a combined rule base - heuristic approach. The modified particle swarm optimization (PSO) technique is used as optimization solver. Moreover, the efficacy of the proposed EMS is verified by performance comparison to recent literature.