Optimal reconfiguration of distribution systems considering reliability: Introducing long-term memory component AEO algorithm

Abstract

This article introduces a modified version of the Artificial Ecosystem Optimization (AEO) algorithm, called Long-term Memory Component AEO (LMAEO), for optimizing the reconfiguration of radial distribution networks. The LMAEO algorithm incorporates a long-term memory component, enabling individuals in the population to make decisions based on past experiences. This integration of long-term memory allows the algorithm to explore a wider range of potential solutions during the optimization process, potentially leading to improved performance and better exploration of the solution space. To verify the effectiveness and superiority of the LMAEO technique, it is compared with the conventional AEO algorithm and other well-known algorithms using seven benchmark functions. The proposed LMAEO algorithm successfully addresses the reconfiguration of distribution systems considering reliability for the modified 12-bus, 33-bus and 69-bus IEEE test systems. Leveraging the strengths of AEO and the long-term memory component, the LMAEO algorithm achieves efficient solutions for this problem. To assess the performance of the proposed LMAEO, a comparison is made with the original AEO algorithm. The results demonstrate that the LMAEO technique surpasses the AEO optimizer in terms of optimal reconfiguration of distribution systems jointly considering reliability, system losses and voltage deviations.