Study into the Power Loss Reduction and Voltage Profile Improvement in Radial Distribution System by Optimal Placement of DSTATCOM Using PSO and GA Methods a case of Bishoftu Substation II

Abstract

With the rapid increase in electrical energy demand, optimizing distribution networks through advanced technologies has become a critical necessity, particularly in developing regions where infrastructure is under pressure. The radial distribution system of Bishoftu Substation II has been identified as a critical zone due to its high-power demand, wide coverage, and low voltage profile, which has led to considerable power losses and reliability issues. The primary challenge addressed in this study is minimizing total active and reactive power losses and improving voltage stability without violating the operational constraints of the system. To overcome these challenges, this thesis aims to determine the optimal placement and sizing of a Distribution Static Synchronous Compensator (DSTATCOM) in the Bishoftu Substation II distribution network. Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) techniques were employed to locate and size the DSTATCOM effectively. The research also addresses the existing methodological gap by comparing the performance of these two metaheuristic algorithms on identical network configurations. Load flow analysis was conducted using MATLAB 2022b to simulate different scenarios: the base case, PSO-optimized, and GA-optimized cases. The results revealed significant improvements in system performance due to DSTATCOM integration. Total active power loss was reduced with GA & PSO, achieving approximately 29.3% and 27.4% loss reduction, respectively. Reactive power loss also achieving approximately 23.6% and 24.7% loss reduction (GA&PSO respectively) . Voltage profile analysis showed that the minimum bus voltage improved from 0.981 p.u. in the base case to 0.989 p.u. with GA and 0.9987 p.u. with PSO, indicating enhanced voltage stability. Additionally, branch-level power loss analysis confirmed performance improvements across critical feeders. In general, the strategic integration of DSTATCOM optimized by PSO and GA significantly enhances voltage stability and reduces power losses in the Bishoftu Substation II distribution network. PSO showed slightly superior performance, but both algorithms demonstrated effectiveness, validating metaheuristic-based DSTATCOM planning as a powerful approach for improving the reliability, efficiency, and economic operation of modern distribution systems.