article · 2025
Comparative Study of Multi-energy Multi-objective Optimal Scheduling in Microbalance Area Based on Several Meta-heuristic Algorithms
Xichao Zhou, Bing Wang, Zishang Xu, Jinyang Zhao, Cheng Xu
Cited by 0Abstract and details only
Abstract
Facing the requirement of efficient balanced operation of multiple distributed energy sources and loads, the multi-objective optimal scheduling task for microbalanced area grids relies on more advanced algorithms day by day. Some metaheuristic intelligent self-trending optimization methods such as particle swarm algorithms, dung beetle optimization algorithms, etc., have been used to improve energy scheduling efficiency. Along these works, this paper further extends and generalizes some recently proposed metaheuristic algorithms, e.g., Walrus optimization, Optical microscope optimization, and Crayfish optimization, to investigate which type of methods are more effective in solving the energy scheduling optimization problem in microbalancing zones. Simulation of the algorithm shows that the Walrus optimization method performs better for optimal energy scheduling of microbalanced area in terms of convergence speed and optimization capability level.
Cite this paper
Zhou, X., Wang, B., Xu, Z., Zhao, J., & Xu, C. (2025). Comparative Study of Multi-energy Multi-objective Optimal Scheduling in Microbalance Area Based on Several Meta-heuristic Algorithms. https://doi.org/10.1109/aeees64634.2025.11019927
Zhou, Xichao, et al. “Comparative Study of Multi-energy Multi-objective Optimal Scheduling in Microbalance Area Based on Several Meta-heuristic Algorithms.” 2025, pp. 1340–45, https://doi.org/10.1109/aeees64634.2025.11019927.
Zhou, Xichao, Bing Wang, Zishang Xu, Jinyang Zhao, and Cheng Xu. 2025. “Comparative Study of Multi-energy Multi-objective Optimal Scheduling in Microbalance Area Based on Several Meta-heuristic Algorithms.” https://doi.org/10.1109/aeees64634.2025.11019927.
Zhou, X. et al. (2025) ‘Comparative Study of Multi-energy Multi-objective Optimal Scheduling in Microbalance Area Based on Several Meta-heuristic Algorithms’. Available at: https://doi.org/10.1109/aeees64634.2025.11019927.
@article{zhou2025comparative,
title = {{Comparative Study of Multi-energy Multi-objective Optimal Scheduling in Microbalance Area Based on Several Meta-heuristic Algorithms}},
author = {Zhou, Xichao and Wang, Bing and Xu, Zishang and Zhao, Jinyang and Xu, Cheng},
pages = {1340--1345},
year = {2025},
doi = {10.1109/aeees64634.2025.11019927}
}Made from the index record. Check names, capitalisation and page numbers against the paper. Need another style? AI for Research has over 10,000.
Related papers
Remarks on Algorithm 2, Algorithm 3, Algorithm 15, Algorithm 25 and Algorithm 26
James Hardy Wilkinson · Communications of the ACM · 1961
Cited by 2Open access
Remarks on Algorithm 332: Jacobi polynomials: Algorithm 344: student's t -distribution: Algorithm 351: modified Romberg quadrature: Algorithm 359: factoral analysis of variance
Ahj Sale · Communications of the ACM · 1970
Cited by 0Open access
Treatment-Decision Algorithm of Child TB: Evaluation of WHO Algorithm and Development of Indonesia Algorithm
Rina Triasih, Finny Fitry Yani, Diah Asri Wulandari et al. · Tropical Medicine and Infectious Disease · 2025
Cited by 4Open access
Remarks on algorithms 372 [A1]: An algorithm to produce complex primes, csieve and Algorithm 401 [A1]: an improved algorithm to produce complex primes
Paul Bratley · Communications of the ACM · 1970
Cited by 0Open access
A Novel Effective Meta-Heuristic Algorithm for BI-Objective Dispatch of Power Systems
Thang Trung Nguyen, Hai Van Tran · International Journal on Electrical Engineering and Informatics · 2018
Cited by 0Open access