Oppositional Pigeon-Inspired Optimizer for Solving the Non-Convex Economic Load Dispatch Problem in Power Systems

Economic Load Dispatch (ELD) belongs to a non-convex optimization problem that aims reduce total power generation cost by satisfying demand constraints. However, solving the ELD is challenging task, because of its parity and disparity The Pigeon-Inspired Optimizer (PIO) recently proposed algorithm, which family swarm intelligence algorithms. PIO algorithm has benefit conceptual simplicity, provides better outcomes for various real-world problems. this drawback premature convergence local stagnation. Therefore, we propose an Oppositional (OPIO) algorithm—to overcome these deficiencies. employs Oppositional-Based Learning (OBL) enhance quality individual, exploring global search space. would be used determine load system, sustaining equality inequality constraints, diminish overall cost. In work, OPIO was applied solve small- (13-unit, 40-unit), medium- (140-unit, 160-unit) large-scale (320-unit, 640-unit) test systems. experimental results demonstrate efficiency over conventional other state-of-the-art approaches in literature. comparative results—in terms improved accuracy, higher rate, less computation time, reduced fuel cost—than approaches.