ANN based Novel Energy Management System of Hybrid Renewable Energy Sources based DC Microgrid

Abstract

Hybrid power supply system's especially powered by renewable energy sources is more popular and frequently establishing at many places in the world. Among many, wind and solar energies are available at every place and commonly used as renewable energy sources for electric power generation. However both the sources are rapidly changes depends on weather conditions. Hence a storage device like battery is required to maintain power balance among all devices in Microgrid. Therefore, a battery is incorporated to the dc-link. PMSG is coupled with wind turbine for electric power generation from wind energy. Photovoltaic (PV) is used to produce electricity from solar energy. Hence, wind system, PV system and battery are connected to a common dc-link through their respective converters for establishing DC Microgrid. Usually conventional PI controllers suffer from fixed gains tuned at particular instant. Hence, Artificial Neural Network (ANN) controllers are implemented on control methods of various converters in this paper to maintain stable voltage at dc-link. Various cases are studied to evaluate results by developing Hardware-in the-Loop (HIL) through OPAL-RT modules.