Metaheuristic optimization algorithms for multi-area economic dispatch of power systems: Part I-a comprehensive survey

被引:1
|
作者
Wang, Yang [1 ]
Xiong, Guojiang [1 ]
机构
[1] Guizhou Univ, Coll Elect Engn, Guizhou Key Lab Intelligent Technol Power Syst, Guiyang 550025, Peoples R China
基金
中国国家自然科学基金;
关键词
Multi-area economic dispatch; Metaheuristic optimization algorithm; Literature review; Survey; DIFFERENTIAL EVOLUTION ALGORITHM; LEARNING-BASED OPTIMIZATION; SCALE COMBINED HEAT; SWARM OPTIMIZATION; LOAD DISPATCH; SEARCH OPTIMIZATION; STRATEGY; NETWORK; SOLVE;
D O I
10.1007/s10462-024-11070-0
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Multi-area economic dispatch (MAED) provides an indispensable component for the security and economic operation of contemporary power systems. Over recent years, numerous metaheuristic optimization algorithms (MOAs) have surfaced for addressing the MAED problem. However, none of the literature to date conducted a comprehensive statistical research work on the MAED problem. In part I of this series, we present a comprehensive survey on this problem. (1) We collect all eleven reported MAED cases studied over the years. These cases have different structures, scales, and constraints. We illustrate the structures of all cases and provide their corresponding system parameters. (2) We collect all the MOA solution algorithms. These algorithms are inspired by different ways, and we categorize them in detail and review them comprehensively. (3) We list the detailed applications of MOAs on different cases and count the percentage of studies on each case. (4) Finally, we summarize the current research progress and point out the future research directions in terms of MAED models and solution methods, respectively. This survey provides an extensive overview of the MAED cases and its solution methods. It can provide applicable and reference suggestions for future research on the MAED problem.
引用
收藏
页数:48
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