Firefly algorithm technique for solving economic dispatch problem

Link to publisher's homepage at http://ieeexplore.ieee.org/

Saved in:
Bibliographic Details
Main Authors: Mohd Herwan, Sulaiman, Dr., Mohd Wazir, Mustafa, Prof. Dr., Zetty Nurazlinda, Zakaria, Omar, Aliman, Siti Rafidah, Abdul Rahim
Other Authors: herwan@ump.edu.my
Format: Working Paper
Language:English
Published: Institute of Electrical and Electronics Engineers (IEEE) 2013
Subjects:
Online Access:http://dspace.unimap.edu.my/xmlui/handle/123456789/26523
Tags: Add Tag
No Tags, Be the first to tag this record!
id my.unimap-26523
record_format dspace
spelling my.unimap-265232013-07-09T03:44:43Z Firefly algorithm technique for solving economic dispatch problem Mohd Herwan, Sulaiman, Dr. Mohd Wazir, Mustafa, Prof. Dr. Zetty Nurazlinda, Zakaria Omar, Aliman Siti Rafidah, Abdul Rahim herwan@ump.edu.my wazir@fke.utm.my zetty@unimap.edu.my omaraliman@ump.edu.my rafidah@unimap.edu.my Continuous genetic algorithm Economic dispatch Firefly algorithm Link to publisher's homepage at http://ieeexplore.ieee.org/ This paper presents the implementation of Firefly Algorithm (FA) in solving the Economic Dispatch (ED) problem by minimizing the fuel cost and considering the generator limits and transmission losses. ED is one of the most challenging problems of power system since it is difficult to determine the optimum generation scheduling to meet the particular load demand with the minimum fuel cost and transmission loss. Until now, there are a lot of researches that have been done to seek for closest optimum result in determining the power generation of each generator especially in large scale power system. FA is a meta-heuristic algorithm which is inspired by the flashing behavior of fireflies. The primary purpose of firefly's flash is to act as a signal system to attract other fireflies. In this paper, 26-bus system is utilized to show the effectiveness of the FA in solving the ED problem. Comparison with Continuous Genetic Algorithm (CGA) and conventional method are also given. 2013-07-09T03:44:43Z 2013-07-09T03:44:43Z 2012-06-06 Working Paper p. 90-95 978-146730661-4 http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6230841&tag=1 http://hdl.handle.net/123456789/26523 en Proceedings of the International Power Engineering and Optimization Conference (PEOCO 2012) Institute of Electrical and Electronics Engineers (IEEE)
institution Universiti Malaysia Perlis
building UniMAP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Perlis
content_source UniMAP Library Digital Repository
url_provider http://dspace.unimap.edu.my/
language English
topic Continuous genetic algorithm
Economic dispatch
Firefly algorithm
spellingShingle Continuous genetic algorithm
Economic dispatch
Firefly algorithm
Mohd Herwan, Sulaiman, Dr.
Mohd Wazir, Mustafa, Prof. Dr.
Zetty Nurazlinda, Zakaria
Omar, Aliman
Siti Rafidah, Abdul Rahim
Firefly algorithm technique for solving economic dispatch problem
description Link to publisher's homepage at http://ieeexplore.ieee.org/
author2 herwan@ump.edu.my
author_facet herwan@ump.edu.my
Mohd Herwan, Sulaiman, Dr.
Mohd Wazir, Mustafa, Prof. Dr.
Zetty Nurazlinda, Zakaria
Omar, Aliman
Siti Rafidah, Abdul Rahim
format Working Paper
author Mohd Herwan, Sulaiman, Dr.
Mohd Wazir, Mustafa, Prof. Dr.
Zetty Nurazlinda, Zakaria
Omar, Aliman
Siti Rafidah, Abdul Rahim
author_sort Mohd Herwan, Sulaiman, Dr.
title Firefly algorithm technique for solving economic dispatch problem
title_short Firefly algorithm technique for solving economic dispatch problem
title_full Firefly algorithm technique for solving economic dispatch problem
title_fullStr Firefly algorithm technique for solving economic dispatch problem
title_full_unstemmed Firefly algorithm technique for solving economic dispatch problem
title_sort firefly algorithm technique for solving economic dispatch problem
publisher Institute of Electrical and Electronics Engineers (IEEE)
publishDate 2013
url http://dspace.unimap.edu.my/xmlui/handle/123456789/26523
_version_ 1643794972906881024
score 13.222552