Optimal Sizing and Siting of Distributed Generators by Hybrid Particle Swarm Optimization-Grey Wolf Optimization Algorithm

Abstract

In operation of the power system, minimization in loss of the power for Distributed System has implication in minimization of cost of operation. In this work, a new Hybrid Particle Swarm Optimization (PSO), and the Grey Wolf Optimization (GWO) technique, is examined in order to determine the optimal sizing, location, and quantity of Distributed Generators units in Distributed System. The aim of optimal positioning of the Distributed Generators issue is to reduce the loss of power in Distributed System because to experience the restraints like current limits, balance in power, Distributed Generators capacity limits, bus voltage limits, and Distributed Generators penetration limit. In order to solve the issue, the hybrid PSO-GWO algorithm is examined to concurrently discover the optimal sizing and siting of Distributed Generators units. Additionally, the optimal amount of Distributed Generators units can be attained through evaluating optimal consequences from various Distributed Generators in the issue. Finally, the developed approach is examined on the IEEE 33-bus, 69-bus, bus, and 118-bus Radial Distributed System (RDS). The consequence evaluations show that the developed approach can attain superior quality solutions than the conventional approaches for the represented scenarios for the test systems. Furthermore, the hybridization of the proposed method consents to accomplish the search procedure at superior speeds. Hence, the proposed technique is a capable technique in order to solve the issue of the optimal position of Distributed Generators units in Distributed System.