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:
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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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