An Energy Management System Based on Adaptive Dynamic Programming for Microgrid Economic Operation

This paper proposes a new home energy management system (EMS) based on the adaptive dynamic programming (ADP) algorithm for economic dispatch problem of microgrid with distributed generations. The electricity price, maximum power output of renewable generation, and load are considered as uncontrollable state variables in this paper. Then two neural networks are used to implement the ADP to minimize a given utility function over a certain time horizon. In this work, the fluctuating amounts of available renewable energy are trained and evaluated in this ADP approach. EMS reduces the daily household energy costs, maximizing the PV self-consumption and increase customer benefits through economically managing the operation of the battery. Then demonstrated via computer simulation that the EMS can reduce the overall energy cost.