Control and Implementation of an Energy Management Strategy for a PV–Wind–Battery Microgrid Based on an Intelligent Prediction Algorithm of Energy Production

This paper describes an energy management strategy for a DC microgrid that utilizes hybrid renewable system (HRES) composed of photovoltaic (PV) module, wind turbine based on permanent magnetic synchronous generator (PMSG), and battery storage (BESS). The is designed to provide flexible reliable architecture ensures continuous power supply loads under all conditions. control scheme the generation reference source currents flux. To optimize supply–demand balance ensure optimal sharing, employs artificial intelligence algorithms use previous data, constantly updated forecasts (such as weather local production data), other factors components in manner. A double-input single-output DC–DC converter used extract maximum point tracking (MPPT) from each source. allows still transfer one another even if sources unable generate power. In this HRES configuration, are connected parallel through common converter. also includes long short-term memory (LSTM) network-based forecasting approach predict available state charge (SOC). tested using Matlab/Simulink validated experimentally laboratory setting.