Noninferior Solution Grey Wolf Optimizer with an Independent Local Search Mechanism for Solving Economic Load Dispatch Problems

Jianzhong Xu, Fu Yan, Kumchol Yun, Lifei Su, Fengshu Li and Jun Guan
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Jianzhong Xu: School of Economics and Management, Harbin Engineering University, 145 Nantong Street, Harbin 150001, China
Fu Yan: School of Economics and Management, Harbin Engineering University, 145 Nantong Street, Harbin 150001, China
Kumchol Yun: School of Economics and Management, Harbin Engineering University, 145 Nantong Street, Harbin 150001, China
Lifei Su: College of Resources and Environment, Northeast Agricultural University, 600 Changjiang Road, Harbin 150030, China
Fengshu Li: School of Economics and Management, Harbin Engineering University, 145 Nantong Street, Harbin 150001, China
Jun Guan: College of Economics and Management, Northeast Forestry University, 26 Hexing Road, Harbin 150040, China

Energies, 2019, vol. 12, issue 12, 1-26

Abstract: The economic load dispatch (ELD) problem is a complex optimization problem in power systems. The main task for this optimization problem is to minimize the total fuel cost of generators while also meeting the conditional constraints of valve-point loading effects, prohibited operating zones, and nonsmooth cost functions. In this paper, a novel grey wolf optimization (GWO), abbreviated as NGWO, is proposed to solve the ELD problem by introducing an independent local search strategy and a noninferior solution neighborhood independent local search technique to the original GWO algorithm to achieve the best problem solution. A local search strategy is added to the standard GWO algorithm in the NGWO, which is called GWOI, to search the local neighborhood of the global optimal point in depth and to guarantee a better candidate. In addition, a noninferior solution neighborhood independent local search method is introduced into the GWOI algorithm to find a better solution in the noninferior solution neighborhood and ensure the high probability of jumping out of the local optimum. The feasibility of the proposed NGWO method is verified on five different power systems, and it is compared with other selected methods in terms of the solution quality, convergence rate, and robustness. The compared experimental results indicate that the proposed NGWO method can efficiently solve ELD problems with higher-quality solutions.

Keywords: grey wolf optimizer (GWO); noninferior solution; local search mechanism; economic load dispatch problems (ELD); optimization algorithms (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

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