multi-course teaching learning based multi-objective optimization (mctlbo)

Solar photovoltaic (PV) systems with back-up battery energy storage system (BESS) mitigate power system related issues like ever-increasing load demand, power loss, voltage deviation and need for power system up-gradation as integration of electric vehicles (EVs) increases load while charging. This paper investigates the improvements of the system parameters like voltage, power loss and loading capabilities of IEEE-69 bus radial distribution system (RDS) with PV/BESS-powered EV charging stations (CSs). The RDS is divided into different zones depending on the total no. of EVs, EV charging time andavailable CS service time. One CS is assigned to each zone. An energy management strategy is developed to direct the power flow among the CS, PV panel, BESS, and the utility grid according to time of use of electricity price. The BESS is allowed to sell excess energy stored to the utility grid during peak hours. Multi-course teaching learning based multi-objective optimization (MCTLBO) is used to optimize the size of PV/BESS system and the locations of CSs in each zone in order to minimize both the annual CS operating cost and the system active power loss. The results validate the use of optimal PV/BESS to power CS for techno-economic improvement of the system.