Manta ray foraging optimization algorithm with mathematical spiral foraging strategies for solving economic load dispatching problems in power systems

被引:19
|
作者
Zhang, Xing-Yue [1 ]
Hao, Wen-Kuo [1 ]
Wang, Jie-Sheng [1 ]
Zhao, Xiao-Rui [1 ]
Zhu, Jun-Hua [1 ]
Zheng, Yue [1 ]
机构
[1] Univ Sci & Technol Liaoning, Sch Elect & Informat Engn, Anshan, Liaoning, Peoples R China
关键词
Economic load dispatching; Manta ray foraging opti; mization algorithm; Mathematical spiral; Transmission loss; Valve point effect; PARTICLE SWARM OPTIMIZATION; GREY WOLF OPTIMIZATION; BEE COLONY ALGORITHM; SEARCH ALGORITHM;
D O I
10.1016/j.aej.2023.03.017
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Economic Load Dispatch (ELD) is an effective dispatch strategy to improve economic efficiency while ensuring the safety and stability of the power system. It minimizes production costs by rationally allocating the power generated by each power system unit. In this paper, an Manta Ray Foraging Optimization (MRFO) algorithm based on the mathematical spiral foraging strategy is proposed to solve the ELD problem in power systems considering transmission losses. Eight dif-ferent mathematical spirals were introduced into the MRFO algorithm's foraging strategy, includ-ing the Rose spiral, Archimedes spiral, Fermat spiral, Cycloid spiral, Hypotrochoid spiral, Epitrochoid spiral, Inverse spiral and Lituus spiral. The mathematical spiral foraging strategy can enhance the global search ability of the MRFO algorithm and improves its convergence veloc-ity. To verify the performance of the proposed improved MRFO algorithm, 30 benchmark func-tions are tested and the optimization performances are compared with BOA, AOA, SCA, HHO, WOA, RSA, and GWO. The simulation experimental results show that the performance and appli-cation of the manta ray foraging optimization algorithm based on the mathematical spiral foraging strategy outperform other intelligent optimization algorithms tested on 30 benchmark functions. Finally, two ELD cases with total demands of 2500 MW and 10500 MW are selected and solved using the improved manta ray foraging optimization algorithm. Comparing the simulation results with other optimization algorithms, it is shown that the proposed improved algorithm obtains the best fuel cost and smaller transmission loss in almost every test case, which canl help to improve the economic efficiency of the power system and achieve the goal of economic load dispatch.(c) 2023 THE AUTHORS. Published by Elsevier BV on behalf of Faculty of Engineering, Alexandria University. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/ licenses/by-nc-nd/4.0/).
引用
收藏
页码:613 / 640
页数:28
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