Energy management strategy for hybrid power systems based on moving average filters and power forecasting

This paper presents a new algorithm of electric energy management of hybrid power systems for self-consumption in isolated areas. This algorithm is inspired by the frequency separation method. Indeed, it is based on the calculation of sliding averages using centered moving average filters, which allow simultaneous and natural processing of measurement data (past) and load and sunshine forecast (future). Moreover, this algorithm has no limits of degrees of freedom and can handle more than two sources of energy without resorting to complex problems. The algorithm is tested on a hybrid system composed of solar panels as a renewable energy source, a fuel cell as a secondary source, a battery bank and a supercapacitor bank as energy storage systems. The main aim of the proposed strategy is to minimize the total operating cost of the system while satisfying the constraints required by the energy storage systems. Furthermore, the robustness of the proposed method is highly improved through the addition of an automatic correction process. The simulation results are convincing and validate the proposed energy management strategy.