Stochastic Model Predictive Control for Microgrid Management Based on PV Power Prediction

Abstract

This paper is concerned with a stochastic model predictive control (SMPC) method for power management of a microgrid with large-scale photovoltaic (PV) energy supply. Recently, PV power generation has been increasing in total energy supply of electric power grids. For the management of microgrids, it is important to explicitly take account of the prediction of PV power generation because it heavily depends on the weather and hence is unstable. We propose a method for microgrid management by combining the SMPC and the PV power prediction. In our method, the PV power is predicted by Just-In-Time modeling from the weather forecast data. We demonstrate the effectiveness of the proposed method by numerical simulations.