RT Journal Article
T1 Optimal reconfiguration of distribution systems considering reliability: Introducing long-term memory component AEO algorithm
A1 Ruiz Rodríguez, Francisco Javier
A1 Kamel, Salah
A1 Hassan, Mohamed H.
A1 Dueñas Díaz, José Antonio
AB 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 benchmarkfunctions. 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.
PB Elsevier
SN 0957-4174
YR 2024
FD 2024
LK https://hdl.handle.net/10272/23279
UL https://hdl.handle.net/10272/23279
LA eng
NO Ruiz-Rodríguez, F. J., Kamel, S., Hassan, M. H., & Dueñas, J. A. (2024). Optimal reconfiguration of distribution systems considering reliability: Introducing long-term memory component AEO algorithm. In Expert Systems with Applications (Vol. 249, p. 123467). Elsevier BV. https://doi.org/10.1016/j.eswa.2024.123467
NO Funding for open access charge: Universidad de Huelva/CBUA.
DS Repositorio Institucional de la Universidad de Huelva
RD 30 may 2026