Grey Wolf Optimizer for Solving Economic Dispatch Problems

Wong, Lo Ing and M. H., Sulaiman and Mohd Rusllim, Mohamed and Hong, Mee Song (2014) Grey Wolf Optimizer for Solving Economic Dispatch Problems. In: IEEE International Conference on Power and Energy (PECON 2014) , 1-3 December 2014 , Kuching, Sarawak. pp. 1-5., 3 (2). ISSN 2321-7308 (print); 2319-1163 (online) (Unpublished)

[img] PDF
fkee-2014-wong-Grey Wolf Optimizer-conf.pdf
Restricted to Repository staff only
Download (255kB) | Request a copy
[img]
Preview
 PDF
fkee-2014-wong-Grey Wolf Optimizer-conf-pg1.pdf
Download (109kB) | Preview

Abstract

This work proposes a new meta-heuristic called Grey Wolf Optimizer (GWO) which inspired by grey wolves (Canis lupus). The GWO algorithm mimics the leadership hierarchy and hunting mechanism of grey wolves in nature. Four types of grey wolves such as alpha, beta, delta, and omega are employed for simulating the leadership hierarchy. In addition, the three main steps of hunting, searching for prey, encircling prey, and attacking prey, are implemented. The algorithm is then benchmarked on 20 generating units in economic dispatch, and the results are verified by a comparative study with Biogeography-based optimization (BBO), Lambda Iteration method (LI), Hopfield model based approach (HM), Cuckoo Search (CS), Firefly, Artificial Bee Colony (ABC), Neural Networks training by Artificial Bee Colony (ABCNN), Quadratic Programming (QP) and General Algebraic Modeling System (GAMS). The results show that the GWO algorithm is able to provide very competitive results compared to these well-known meta-heuristics.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Economic Dispatch; Grey Wolf Optimizer; Loss minimization; Meta-heuristic technique;
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Faculty/Division: Faculty of Electrical & Electronic Engineering
Depositing User: Noorul Farina Arifin
Date Deposited: 26 Nov 2014 06:16
Last Modified: 11 Apr 2018 03:15
URI: http://umpir.ump.edu.my/id/eprint/7539
Download Statistic: View Download Statistics

Actions (login required)

View Item View Item