Choosing PSO under Different Overloads to Provide Best Power Flow for IEEE - 57 Bus

Abstract

This study investigates the impact of Particle Swarm Optimization (PSO) on power loss and production cost reduction in overloaded transmission lines. PSO is used to manage power flow in congested transmission lines and reduce power losses. The proposed technique was tested using the IEEE large-scale 57-bus test system. Optimal power flow (OPF) is crucial for modern power systems, aiming to minimize active and reactive power distribution while considering technological and economic constraints. PSO is presented as a solution to the OPF problem, focusing on actual power losses, hypothetical power losses, and overload consequence. PSO is presents.as a solution, and various methods, such as genetic algorithms and linear programming, will be used to compare PSO results. The suggested PSO yields reduced power losses with higher loads in case studies. The approach is evaluated for IEEE -57 buses and produces superior results when used with the MATLAB environment. PSO reduces the target function's real power loss from its starting condition (24.98) MW to its ideal state (16.75) MW with a reduction of 8.23 MW. Additionally, PSO reduces the target function's active power loss by 20% overload from its initial state (56.042 MW) to the optimal state of 46.23 MW with a reduction of 9.812 MW.

Keywords

• Optimal Power Flow; Real Power Loss; PSO, Power Loss Minimization; Overload; IEEE-57 bus