Optimal Siting and Sizing of Renewable Energy Sources in Distribution System

Abstract

An optimal siting and sizing of renewable energy sources (RES) play a substantial role in achieving the efficient operation and planning of the distribution system. It majorly affects the active power loss and voltage stability of the system. Therefore, this study formulates a multi-objective function that optimally allocates and sizes the RES in the distribution network by minimizing the total active power losses (TAPL) and voltage deviation (VD) of the network buses. The proposed algorithm is validated on an IEEE 69-bus model having two types of loads, i.e. consumer load and charging load of an electric vehicle. The consumer load is modelled as a polynomial type of load, and a total of four electric vehicle charging stations (EVSs) are integrated into the model. The formulated objective function also optimally allocates these four EVSs to minimize the TAPL and VD of the system. The objective function is minimized using four different optimization techniques, i.e. genetic algorithm (GA), grey wolf optimizer (GWO), particle swarm optimization (PSO), and hybrid particle swarm grey wolf optimization (HPSGWO). The simulation studies showed that the HPSGWO is superior to all other algorithms as it provides the solution having the lowest TAPL and VD in the system.