Optimal Placement of Charging Station in OM Distribution Feeder of New Chabil Substation Considering Dynamic Nature of Electric Vehicle Load

Abstract

One of the major contributors of global warming and environmental changes which is considered as global problem is fossil operated internal combustion engines vehicles. To sort out this problem, enhanced battery technology and subsidies provided by the Government has caused rapid increase in number of electric vehicles (EVs) which requires charging station (CS) to connect the power grid and the transport network. The behaviour of EV is uncertain and CS random placement affects both the network simultaneously. So, in this paper demand of CS is obtained by Monte Carlo simulation (MCS) with the help of queuing theory for taking the dynamic characteristics of a CS serviceability into account. Optimal placement of CSs is structured as a multi-objective optimization problem, which is solved by non-dominated sorting genetic algorithm-II (NSGA-II) to obtain a set of compromised solutions from which best compromised solution is obtained by Fuzzy optimization technique. The objective functions to be optimized are minimization of electrical distribution loss, minimization of power loss occurring in EVs’ when travel towards CS location and maximization of utilization factor (UF). UF value provides an insight on how well the CS infrastructure is utilized and helps in determining the number of CSs required in a network. The proposed method is simulated on a real 12kV OM feeder of Nepal to show various results. Results show best location of CSs and parameters like voltage profile, CS utilization and demand uncertainty of CS are analyzed and presented.