Optimizing Economic Load Dispatch Using a Hybrid PSO-SA Algorithm: A Novel Approach

Economic Load Dispatch (ELD) is a crucial power system optimization task. It aims to minimize the total cost of electricity generation by strategically allocating power output among available generating units to meet the system's demand while respecting operational limits. This paper investigates how soft computing methods can improve the effectiveness of Electronic Logging Device (ELD) solutions. Specifically, Particle Swarm Optimization (PSO) and Simulated Annealing (SA) algorithms are employed to minimize generation costs for a power system comprising three generating units. The optimization process considers loss coefficients, generation limits, and a predefined cost function. Initially, PSO is used to determine near-optimal solutions, which are further refined using SA to avoid local minima. A hybrid PSO-SA method integrates the global exploration of Particle Swarm Optimization (PSO) with the local refinement of Simulated Annealing (SA) to enhance convergence and solution quality. 1 This approach was implemented in MATLAB and validated through a case study. Simulation results demonstrate that the hybrid method consistently yields high-quality solutions with reduced computational effort, proving its robustness and reliability for solving ELD problems. Combining metaheuristic algorithms shows promise for real-world power system optimization