A harmonic estimator design with evolutionary operators equipped grey wolf optimizer

被引：40

作者：

Saxena, Akash ^{[1
]}

Kumar, Rajesh ^{[2
]}

Mirjalili, Seyedali ^{[3
]}

机构：

[1] Swami Keshvanand Inst Technol Management & Gmmoth, Dept Elect Engn, Jaipur, Rajasthan, India

[2] Malaviya Natl Inst Technol, Dept Elect Engn, Jaipur, Rajasthan, India

[3] Torrens Univ Australia, Ctr Artificial Intelligence Res & Optimisat, Brisbane, Qld 4006, Australia

来源：

EXPERT SYSTEMS WITH APPLICATIONS | 2020年 / 145卷

关键词：

Grey Wolf Optimizer (GWO); Mutation; Crossover; Harmonics; Power quality; Optimization; Algorithm; POWER-SYSTEM HARMONICS; ALGORITHM; TRACKING;

D O I：

10.1016/j.eswa.2019.113125

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Harmonic estimation is a challenging design problem in power networks. Accurate estimation of the inter, power and sub harmonics in networks can be a helpful aspect for designing potential solutions for elimination of these harmonics. Harmonic estimation design problem has been considered as an optimization problem with the amalgamation of least square algorithm in past. In this paper, we first propose an Evolutionary Operators Equipped Grey Wolf Optimizer (E-GWO). In this proposal a sinusoidal function enabled bridging is proposed and along with this tournament selection operator and crossover and mutation operation are incorporated at position updation phase. The variant is first benchmarked on latest CEC-2017 functions and then this design problem is addressed. After a meaningful comparison with the previously published approaches, we arrive at the conclusion that proposed modifications have positive implications on the performance of GWO. Proposed harmonic designs are robust when tested with different operating conditions. (C) 2019 Elsevier Ltd. All rights reserved.

引用

页数：16

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