Economic and Emission Dispatch Solution Using Evolutionary Mating Algorithm

This paper presents the Evolutionary Mating Algorithm (EMA) as a novel evolutionary algorithm for addressing economic emission load dispatch (EELD) problems. The optimization of power systems with respect to economic and emission considerations is of utmost importance in contemporary power system engineering. Emphasizing cost and emission reduction is essential for efficient power system operation. In this study, the economic and emission dispatch problem is tackled using the Evolutionary Mating Algorithm (EMA). The performance of the EMA algorithm is evaluated on a 10 and 40-unit generator test system. Comparative analyses are conducted with other algorithms, namely the Cuckoo Search Algorithm (CSA), Flower Pollination Algorithm (FPA), and Barnacles Mating Optimizer (BMO). The results indicate the effectiveness of the Evolutionary Mating Algorithm in solving economic emission dispatch problems, thereby demonstrating the efficacy of the proposed EMA approach for addressing EELD problems.