Comparative Performance Analysis of DG and DSTATCOM Using Improved PSO Based on Success Rate for Deregulated Environment

Abstract

A new and improved particle swarm optimization (PSO) technique with adaptive inertia weight ( w ) based on success rate is proposed to find the optimal allocation of distributed generation (DG) and distribution static compensator (DSTATCOM) considering security limits. For the optimal sizing and siting of the device, technical, economic, and social objectives are considered. Logical and innovative indexes namely voltage profile enhancement index, benefit cost ratio, and emission cost benefit index are formulated to judge the impact of the device on the system. The developed algorithm is executed for both full search space (all load bus locations) and reduced search space (only unhealthy zone/locations) to prove that the optimal allocation is obtained only at the unhealthy zone. For the IEEE 33 and IEEE 69 bus systems, the proposed algorithm is compared with other techniques such as differential evolution, real-coded genetic algorithm, and PSO based on randomized inertia weight, and PSO based on linearly decreasing inertia weight. The best performance in terms of computational efficiency and solution quality is achieved for the proposed method. Further, a comparative performance analysis is presented between DG and DSTATCOM based on the economic, technical, and social impacts.