Optimal schedule for networked microgrids under deregulated power market environment using model predictive control

Abstract

Microgrids are considered as a key technology for the introduction of renewable energy systems in the electrical market. Nevertheless, microgrids are subject to random conditions such as changes in the energy forecast or component failures which will force microgrids to incur in the penalty costs applied in real time markets. In order to minimize the aforementioned costs, an optimal Energy Management System (EMS) for the economic re-schedule of a network of interconnected microgrids with hybrid Energy Storage System (ESS) under failure conditions is developed and validated using Model Predictive Control (MPC). The algorithm is specifically designed to achieve lower economic losses under failure conditions through the establishment of a local energy market in the network of microgrids than participating in the intraday or real-time markets.