Hybrid Microgrid Energy Management System Using a Fuzzy-PI Controller (Case Study: Adama General Hospital)

Abstract

It is a well-known fact that the number of populations increases from time to time throughout the world. It parallels an increase in energy demand. It can be balanced using replenished energy sources that are known as renewable energy sources. They are ideal for the production of power due to their infinite existence and ecologically benign character. Solar and wind energy sources are the basic types of renewable energy. To obtain better energy service and improve reliability, a hybrid system is recommended over a standalone system. The fitful nature of solar and wind energy sources causes a power quality and sustainability problem. As a result, continuous monitoring, controlling, and optimization of generation system performance are required using different software and algorithms. This process is known as an energy management system (EMS). In essence, a good management system effectively supplies the needed power demand. In this thesis, the generation of wind and solar hybrid microgrid EMS is designed and presented using adaptive fuzzy-PI control as a case study of the Adama general hospital energy distribution system. A fuzzy inference system employing in utilized in solar energy sources to track photovoltaic panels' greatest power points. whereas the wind energy converter is managed by a proportional integral (PI) controller. In addition, a fuel cell is used as a backup power source when neither solar nor wind energy is available, much like a battery does when solar and wind electricity is turned off. The simulation results show that effective stability and distribution of power without interruption are obtained by using the fuzzy-PI control algorithm. Hence, the required power demand is supplied effectively with an increase in reliability for the users.