An improved firefly algorithm for optimal microgrid operation with renewable energy

Lately, an electrical network in microgrid system becomes very important to rural or remote areas without connection from primary power grid system. Higher cost of fuels, logistic, spare parts and maintenance affect the cost for operation microgrid generation to supply electrical power for remote ar...

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Main Author:	Saleh, Syukur
Format:	Thesis
Language:	English English English
Published:	2017
Subjects:	TK3001-3521 Distribution or transmission of electric power
Online Access:	http://eprints.uthm.edu.my/870/1/24p%20SYUKUR%20SALEH.pdf http://eprints.uthm.edu.my/870/2/SYUKUR%20SALEH%20COPYRIGHT%20DECLARATION.pdf http://eprints.uthm.edu.my/870/3/SYUKUR%20SALEH%20WATERMARK.pdf
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id	my-uthm-ep.870
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spelling	my-uthm-ep.8702021-09-06T05:45:26Z An improved firefly algorithm for optimal microgrid operation with renewable energy 2017-07 Saleh, Syukur TK3001-3521 Distribution or transmission of electric power Lately, an electrical network in microgrid system becomes very important to rural or remote areas without connection from primary power grid system. Higher cost of fuels, logistic, spare parts and maintenance affect the cost for operation microgrid generation to supply electrical power for remote areas and rural community. This project proposes an Improved Firefly Algorithm (IFA), which is a improvement of classical Firefly Algorithm (FA) technique using characteristic approach of Lévy flights to solve the optimal microgrid operation. The IFA has been used for optimizing the cost of power generation in microgrid system where daily power balance constraints and generation limits are considered. The microgrid system for this case study considered both of renewable energy plant and conventional generator units. There are two test systems that have been considered as case study. The first test system is a simple microgrid system which consists of three generators. The second test system consists of seven generating units including two wind turbines, three fuel-cell plants and two diesel generators. The IFA method has been implemented using MATLAB software. The results obtained by IFA was compared to FA and other algorithms based on optimal cost, convergence characteristics and robustness to validate the effectiveness of the IFA. It shows that the IFA obtained better results in terms of operating costs compared to FA, Differential Evolution (DE), Particle Swarm Optimization (PSO) and Cuckoo Search Algorithm (CSA). 2017-07 Thesis http://eprints.uthm.edu.my/870/ http://eprints.uthm.edu.my/870/1/24p%20SYUKUR%20SALEH.pdf text en public http://eprints.uthm.edu.my/870/2/SYUKUR%20SALEH%20COPYRIGHT%20DECLARATION.pdf text en staffonly http://eprints.uthm.edu.my/870/3/SYUKUR%20SALEH%20WATERMARK.pdf text en validuser mphil masters Universiti Tun Hussein Onn Malaysia Fakulti Kejuruteraan Elektrik dan Elektronik
institution	Universiti Tun Hussein Onn Malaysia
collection	UTHM Institutional Repository
language	English English English
topic	TK3001-3521 Distribution or transmission of electric power
spellingShingle	TK3001-3521 Distribution or transmission of electric power Saleh, Syukur An improved firefly algorithm for optimal microgrid operation with renewable energy
description	Lately, an electrical network in microgrid system becomes very important to rural or remote areas without connection from primary power grid system. Higher cost of fuels, logistic, spare parts and maintenance affect the cost for operation microgrid generation to supply electrical power for remote areas and rural community. This project proposes an Improved Firefly Algorithm (IFA), which is a improvement of classical Firefly Algorithm (FA) technique using characteristic approach of Lévy flights to solve the optimal microgrid operation. The IFA has been used for optimizing the cost of power generation in microgrid system where daily power balance constraints and generation limits are considered. The microgrid system for this case study considered both of renewable energy plant and conventional generator units. There are two test systems that have been considered as case study. The first test system is a simple microgrid system which consists of three generators. The second test system consists of seven generating units including two wind turbines, three fuel-cell plants and two diesel generators. The IFA method has been implemented using MATLAB software. The results obtained by IFA was compared to FA and other algorithms based on optimal cost, convergence characteristics and robustness to validate the effectiveness of the IFA. It shows that the IFA obtained better results in terms of operating costs compared to FA, Differential Evolution (DE), Particle Swarm Optimization (PSO) and Cuckoo Search Algorithm (CSA).
format	Thesis
qualification_name	Master of Philosophy (M.Phil.)
qualification_level	Master's degree
author	Saleh, Syukur
author_facet	Saleh, Syukur
author_sort	Saleh, Syukur
title	An improved firefly algorithm for optimal microgrid operation with renewable energy
title_short	An improved firefly algorithm for optimal microgrid operation with renewable energy
title_full	An improved firefly algorithm for optimal microgrid operation with renewable energy
title_fullStr	An improved firefly algorithm for optimal microgrid operation with renewable energy
title_full_unstemmed	An improved firefly algorithm for optimal microgrid operation with renewable energy
title_sort	improved firefly algorithm for optimal microgrid operation with renewable energy
granting_institution	Universiti Tun Hussein Onn Malaysia
granting_department	Fakulti Kejuruteraan Elektrik dan Elektronik
publishDate	2017
url	http://eprints.uthm.edu.my/870/1/24p%20SYUKUR%20SALEH.pdf http://eprints.uthm.edu.my/870/2/SYUKUR%20SALEH%20COPYRIGHT%20DECLARATION.pdf http://eprints.uthm.edu.my/870/3/SYUKUR%20SALEH%20WATERMARK.pdf
_version_	1747830698351263744

An improved firefly algorithm for optimal microgrid operation with renewable energy

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