Economic Dispatch Problem Including Renewable Energy Using Generalized Normal Distribution Optimization And Bald Eagle Search Optimization Algorithm

Abstract

Economic Dispatch (ED) problem is an essential optimization problem in electrical power system.It is to schedule the committed generating units outputs so as to meet the required load demand at minimum operating cost while satisfying all units and system equality and inequality constraints. Furthermore, renewable energy resources such as wind and solar have been a promising option due to environmental concerns as fossil fuel reserves are depleted, fuel prices rise quickly, and emissions rise. However, the uncertain nature of wind and solar irradiation due to weather and climate change and the integration of renewable power generation systems complicates the ED formulation. The Bald Eagle Search (BES) Optimization algorithm and Generalized Normal Distribution Optimization (GNDO) are proposed to solve the ED problem. To show the effectiveness of the proposed algorithm, four case studies are used to illustrate the proposed algorithm's ability. Finally, the results of the proposed algorithm are compared to other optimization techniques such as WOA, FPA, MODE, GA, PSO, and GSA. The results indicate that BES and GNDO can achieve lower total costs than the other optimization techniques.