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Solving Economic Dispatch Problems with Practical Constraints Utilizing Grey Wolf Optimizer

This paper presents the application of a new meta-heuristic called Grey Wolf Optimizer (GWO) which inspired by grey wolves (Canis lupus) for solving economic dispatch (ED) problems. The GWO algorithm mimics the leadership hierarchy and hunting mechanism of grey wolves in nature. Four types of grey w...

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Main Authors: Lo, Ing Wong, M. H., Sulaiman, Mohd Rusllim, Mohamed
Format: Article
Language:English
Published: scientific.net 2015
Subjects:
TK Electrical engineering. Electronics Nuclear engineering
Online Access:http://umpir.ump.edu.my/id/eprint/10366/1/Solving%20Economic%20Dispatch%20Problems%20with%20Practical%20Constraints%20Utilizing%20Grey%20Wolf%20Optimizer.pdf
http://umpir.ump.edu.my/id/eprint/10366/
http://www.scientific.net/AMM.785.511
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spelling my.ump.umpir.103662018-03-07T03:48:24Z http://umpir.ump.edu.my/id/eprint/10366/ Solving Economic Dispatch Problems with Practical Constraints Utilizing Grey Wolf Optimizer Lo, Ing Wong M. H., Sulaiman Mohd Rusllim, Mohamed TK Electrical engineering. Electronics Nuclear engineering This paper presents the application of a new meta-heuristic called Grey Wolf Optimizer (GWO) which inspired by grey wolves (Canis lupus) for solving economic dispatch (ED) problems. 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. In this paper, GWO was demonstrated and tested on two well-known test systems with practical constraints. A comparison of simulation results is carried out with those published in the recent literatures. The results show that the GWO algorithm is able to provide very competitive results for nonlinear characteristics of the generators such as ramp rate limits, prohibited zone and non-smooth cost functions compared to the other well-known meta-heuristics techniques. scientific.net 2015 Article PeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/10366/1/Solving%20Economic%20Dispatch%20Problems%20with%20Practical%20Constraints%20Utilizing%20Grey%20Wolf%20Optimizer.pdf Lo, Ing Wong and M. H., Sulaiman and Mohd Rusllim, Mohamed (2015) Solving Economic Dispatch Problems with Practical Constraints Utilizing Grey Wolf Optimizer. Applied Mechanics and Materials, 785. pp. 511-515. ISSN 1662-7482 http://www.scientific.net/AMM.785.511 DOI: 10.4028/www.scientific.net/AMM.785.511
institution Universiti Malaysia Pahang
building UMP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Pahang
content_source UMP Institutional Repository
url_provider http://umpir.ump.edu.my/
language English
topic TK Electrical engineering. Electronics Nuclear engineering
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Lo, Ing Wong
M. H., Sulaiman
Mohd Rusllim, Mohamed
Solving Economic Dispatch Problems with Practical Constraints Utilizing Grey Wolf Optimizer
description This paper presents the application of a new meta-heuristic called Grey Wolf Optimizer (GWO) which inspired by grey wolves (Canis lupus) for solving economic dispatch (ED) problems. 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. In this paper, GWO was demonstrated and tested on two well-known test systems with practical constraints. A comparison of simulation results is carried out with those published in the recent literatures. The results show that the GWO algorithm is able to provide very competitive results for nonlinear characteristics of the generators such as ramp rate limits, prohibited zone and non-smooth cost functions compared to the other well-known meta-heuristics techniques.
format Article
author Lo, Ing Wong
M. H., Sulaiman
Mohd Rusllim, Mohamed
author_facet Lo, Ing Wong
M. H., Sulaiman
Mohd Rusllim, Mohamed
author_sort Lo, Ing Wong
title Solving Economic Dispatch Problems with Practical Constraints Utilizing Grey Wolf Optimizer
title_short Solving Economic Dispatch Problems with Practical Constraints Utilizing Grey Wolf Optimizer
title_full Solving Economic Dispatch Problems with Practical Constraints Utilizing Grey Wolf Optimizer
title_fullStr Solving Economic Dispatch Problems with Practical Constraints Utilizing Grey Wolf Optimizer
title_full_unstemmed Solving Economic Dispatch Problems with Practical Constraints Utilizing Grey Wolf Optimizer
title_sort solving economic dispatch problems with practical constraints utilizing grey wolf optimizer
publisher scientific.net
publishDate 2015
url http://umpir.ump.edu.my/id/eprint/10366/1/Solving%20Economic%20Dispatch%20Problems%20with%20Practical%20Constraints%20Utilizing%20Grey%20Wolf%20Optimizer.pdf
http://umpir.ump.edu.my/id/eprint/10366/
http://www.scientific.net/AMM.785.511
_version_ 1643666373481594880
score 13.211869

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