Implementation of oppositional slime mould algorithm in power dispatch problem

被引:0
|
作者
Pawani, Kanchan [1 ]
Singh, Manmohan [1 ]
机构
[1] St Longowal Inst Engn & Technol, Dept Elect & Instrumentat, Sangrur, Punjab, India
关键词
benchmark functions; CEC; 14; functions; constraints; constraint handling; ELD; economic load dispatch; generators; heuristic techniques; no free lunch theorem; opposition learning; optimisation technique; slime mould algorithm; BACKTRACKING SEARCH ALGORITHM; SCALE ECONOMIC-DISPATCH; GREY WOLF OPTIMIZATION; LOAD DISPATCH; DIFFERENTIAL EVOLUTION; FLOW;
D O I
10.1504/IJCSM.2024.139924
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Economic load dispatch (ELD) is crucial for power system operation, balancing electricity supply and demand while minimising costs. The goal of ELD is to minimise the overall cost of generating electricity and meet operational constraints. These constraints make the system complex. The complexity increases with the dimensionality of the problem. To tackle the complexities of the problem, a hybrid optimisation technique is implemented. This paper introduces an optimised opposition slime mould algorithm to solve this problem. The proposed algorithm uses slime reproductive behaviour and an opposition learning strategy to avoid exploitation and balance exploration. The accessibility of the proposed algorithm is calculated by the fuel cost and the compact solution. The performance and effectiveness are verified through benchmark functions, the CEC 14 functions and real-world load dispatch problems. The applied algorithm has yielded better results on ELD problems, benchmark functions and CEC14 functions than popular algorithms.
引用
收藏
页码:1 / 20
页数:21
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