Wind Power Integrated Economic Dispatch Solution Using Nature-Inspired Bald Eagle Search Algorithm

Abstract

This paper utilizes the Bald Eagle Search (BES) algorithm to address the economic dispatch problem with the integration of stochastic wind power. The primary goals of the BES algorithm are to minimize the costs of both thermal generation and stochastic wind power while factoring in emissions, power losses, and voltage deviations. To evaluate the effectiveness of the BES algorithm in solving the optimal power flow (OPF) problem, modified IEEE 30-bus test system incorporating stochastic wind power generators is employed. A comprehensive comparative analysis is conducted to showcase the efficiency of the BES algorithm against other recent metaheuristic algorithms, such as the Equilibrium Optimizer (EO), Slime Mold Algorithm (SMA), Marine Predator Algorithm (MPA), and Artificial Ecosystem Optimizer (AEO), along with other well-established methods. The analysis demonstrates that the BES algorithm achieves consistently superior performance across all evaluated metrics.