Optimal loop power flow control of power distribution system using advanced meta-heuristic algorithms

This study uses advanced metaheuristic algorithms to solve energy-saving problems in the loop distribution network. An initiative energy management system (EMS) is suggested to deliver optimal commands to the loop power controller (LPC) whose operation is optimized by combining a metaheuristic algorithm with a ladder iterative technique. Here, the performance of state-of-the-art metaheuristic algorithms applied in the proposed EMS–LPC solution is compared and evaluated by simulation in a real-world case study. Simulation results show that all metaheuristic algorithms meet the optimization objective of reducing distribution loss in which the artificial ecosystem-based optimization (AEO) algorithm outperforms with both the lowest optimum value and the fastest convergence time. Consequently, the proposed EMS–LPC method results in a daily energy savings of 18% in comparison with the base case. Then, the proposed solution has potential for real-time applications to save grid power and reduce operating expenses due to the perfect performance of the suggested EMS–LPC approach.