Performace Comparison of Metaheuristic Algorithms on Solving the Optimal Power Flow in a Active Distribution Network

The active distribution networks (ADN) are increasing in popularity, due to the accelerated penetration of renewable and distributed energy sources. In this context, optimal coordination between numerous devices is necessary in order to assure the optimal operational conditions. This paper's main objective is to conduct a performance analysis of six state-of-the-art metaheuristic algorithms, Grey Wolf Optimizer (GWO), Salp Swarm Algorithm (SSA), Marine Predators Algorithm (MPA), Sine-Cosine Algorithm (SCA), Ant-Lion Optimizer (ALO) and Whale Optimization Algorithm (WOA), in solving the optimal power flow problem, on an active distribution grid. The results reveal that the MPA delivers the best performance followed closely by GWO and WOA.