Stochastic Dynamic Programming Based Optimal Energy Management for an Islanded Microgrid

Intelligence and data have never been more significant factors in providing clean and profitable energy than today. As consumption capacity increases, effective strategies based on new technologies become more complex. This paper presents an optimal energy management strategy for a smart microgrid which contains three renewable energy sources as well as an energy storage system. This microgrid works in islanded mode and the optimal day-ahead scheduling of the generators using renewable energy resources is performed using a stochastic-dynamic programming method. The method demonstrated focuses not only on the daily cost optimization of the microgrid, but also aims to extend the life cycle of the batteries, making sure that the system is not characterized by excessive charging or discharging. The results obtained this way will be compared with results obtained via the MILP algorithm, and some conclusions will be drawn.