OPTIMAL ALLOCATION OF DISTRIBUTION GENERATOR FOR RADIAL DISTRIBUTION NETWORK USING GREY WOLF OPTIMIZER

Electric power utilities are paying a lot of attention right now to the optimal location and size of distributed generation (DG) at the radial distribution grids with the goal of minimizing real power loss. Power loss minimization has several built-in advantages, such as reducing the power flow on reducing the power flow on the feeder lines, relieving stress on feeder loading to extend their life, increasing the possibility of using the current facility to meet any increase in load demand, avoiding the need to buy power from the grid, saving money on loss-compensating equipment, lowering customer bills, etc. In this paper, the optimal location and size of distributed generation (DG) units will be addressed using one of the most popular metaheuristic optimization techniques, namely the Grey Wolf Optimizer (GWO). The main aim of this paper is to minimize the real power losses on the distribution network, improve the voltage profiles, and enhance the voltage stability index by adding DG units to the optimal location and determining the optimal size while satisfying the equality and inequality constraints. The approach proposed determining the optimal location by reconfiguring the DG on all buses, calculating the real power losses, and improving the voltage deviation. The optimal location is achieved on a bus with the lowest real power losses. The optimal sizing of the DG unit can be achieved by using Grey Wolf Optimizer (GWO). GWO is a meta- heuristics optimization technique inspired by the social behavior of gray wolves. The IEEE 69 bus power system and Babylon Radial Distribution Network (BRDN) will be tested to prove the superiority and efficiency of the proposed algorithm. According to the simulation results that were obtained and the evaluation of the various cases that were taken into consideration, the placement of DG units results in a large loss reduction with a favorable voltage profile as well as a release in the line loading in the power distribution networks.