Grey Wolf Optimization to Solve Load Frequency Control of an Interconnected Power System: GWO Used to Solve LFC Problem

被引:4
|
作者
Guha, Dipayan [1 ]
Roy, Provas Kumar [2 ]
Banerjee, Subrata [3 ]
机构
[1] Dr BC Roy Engn Coll Durgapur, Dept Elect Engn, Durgapur, India
[2] Jalpaiguri Govt Engn Coll, Dept Elect Engn, Jalpaiguri, India
[3] Natl Inst Technol Durgapur, Durgapur, India
关键词
Grey Wolf Optimization; Least Average Error; Load Frequency Control; Quasi-Oppositional Based Learning; Sensitivity Analysis;
D O I
10.4018/IJEOE.2016100104
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
In this article, a novel optimization algorithm called grey wolf optimization (GWO) with the theory of quasi-oppositional based learning (Q-OBL) is proposed for the first time to solve load frequency control (LFC) problem. An equal two-area thermal power system equipped with classical PID-controller is considered for this study. The power system network is modeled with governor dead band and time delay nonlinearities to get better insight of LFC system. 1% load perturbation in area-1 is considered to appraise the dynamic behavior of concerned power system. Integral time absolute error and least average error based fitness functions are defined for fine tuning of PID-controller gains employing the proposed method. An extensive comparative analysis is performed to establish the superiority of proposed algorithm over other recently published algorithms. Finally, sensitivity analysis is performed to show the robustness of the designed controller with system uncertainties.
引用
收藏
页码:62 / 83
页数:22
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