ANN based Novel Control Power Quality Improvement of Hybrid Renewable Energy Sources based AC Microgrid

Hybrid AC Microgrid powered by different renewable energy sources is popular worldwide to reduce pollution as well as to meet local load demand. A standalone system must be established to supply power to local loads where no access of power grid. 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. Generally, AC loads are operating in a distribution system. Hence an inverter is considered in this paper to supply AC power to loads from a DC link. Usually conventional PI controllers suffer from fixed gains tuned at particular instant. Hence, Artificial Neural Network (ANN) based controllers are implemented on control methods of various converters to maintain stable voltages at load point. Various cases are studied to evaluate the obtained results by developing Hardware-in the-Loop (HIL) through OPAL-RT modules.