Application of grey wolf optimisation algorithm in parameter calculation of overhead transmission line system

被引:32
|
作者
Shaikh, Muhammad Suhail [1 ]
Hua, Changchun [1 ]
Jatoi, Munsif Ali [2 ]
Ansari, Muhammad Mohsin [3 ]
Qader, Aleem Ahmed [4 ]
机构
[1] Yanshan Univ, Inst Elect Engn, Qinhuangdao 06600, Hebei, Peoples R China
[2] Barrett Hodgson Univ, Dept Biomed Engn, Karachi, Pakistan
[3] Zhejiang Univ, Dept Elect Engn, Hangzhou, Peoples R China
[4] Yanshan Univ, Sch Econ & Management, Qinhuangdao, Hebei, Peoples R China
关键词
CUCKOO SEARCH ALGORITHM; ARTIFICIAL BEE COLONY; ORDER PID CONTROL; DIFFERENTIAL EVOLUTION; GLOBAL OPTIMIZATION; TABU SEARCH; WIND; EXPLORATION; PERFORMANCE;
D O I
10.1049/smt2.12023
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
The transmission line is the main component in the power system consisting of inductance, capacitance, and resistance. These parameters are important during the transmission line design. This research work applies a novel optimisation technique, grey wolf optimisation (GWO), to calculate the overhead transmission line parameter. The best optimal value is estimated with the control variables. Furthermore, the effect of different bundle conductors, that is, two, three, and four bundle conductors, radius, and spacing between the conductors on the transmission line is also analysed. GWO is a recently developed nature-inspired meta-heuristic algorithm. Single-phase and three-phase transmission line test systems have been adopted for testing purposes. The proposed algorithm is inspired by the command hierarchy and hunting system of grey wolves. The algorithm is applied to 14 benchmark optimisation functions with dimension and number of search agents. The results of the GWO algorithms are optimised and are superior as compared to previously applied algorithms. The proposed algorithm achieved the best optimal solutions for most of these functions that have been validated statistically. From the results, it is identified that the proposed algorithm is computationally efficient and performs significantly better in terms of accuracy, robustness, and convergence speed.
引用
收藏
页码:218 / 231
页数:14
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