Grasshopper optimization algorithm based two stage fuzzy multiobjective approach for optimum sizing and placement of distributed generations, shunt capacitors and electric vehicle charging stations

In this paper a two stage Grasshopper Optimization Algorithm (GOA) based Fuzzy multiobjective approach is proposed for optimum sizing and placement of Distributed Generations (DGs), Shunt Capacitors (SCs) and Electric Vehicle (EV) charging stations for distribution systems. In the first stage Fuzzy GOA approach is used for optimum sizing and allocation of DGs and SCs for improving the substation power factor, real power loss reduction and voltage profile improvement of the distribution system. In the second stage distribution system integrated with DGs and SCs is considered and fuzzy GOA approach is used for identifying optimum locations for EV charging stations and number of vehicles at the charging stations. EV battery charging load models are developed from the Lithium ion battery charging characteristic curves for load flow analysis. Simulation results are shown to show the advantages of fast converging properties of GOA over GA and PSO techniques. Simulation results are demonstrated on 51 bus and 69 bus distribution networks to show the advantages of proposed methodology compared to conventional objective based simultaneous optimization approach. The effect of EV load growth and the effect of uncertainties in DGs and distribution system load are shown on the distribution system performance.