Development of profit-based unit commitment solution using particle swarm optimization / Ida Syahirah Baderol Iskandar

This thesis presents the solution of profit-based unit commitment (PBUC) by using particle swarm optimization (PSO) technique. In this study, the on/off scheduling of generator units will be determined based on maximizing the profit while fulfilling the constraints. The proposed solution also helps...

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主要作者: Baderol Iskandar, Ida Syahirah
格式: Thesis
语言:English
出版: 2017
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在线阅读:https://ir.uitm.edu.my/id/eprint/67309/2/67309.pdf
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spelling my-uitm-ir.673092023-02-03T15:32:51Z Development of profit-based unit commitment solution using particle swarm optimization / Ida Syahirah Baderol Iskandar 2017 Baderol Iskandar, Ida Syahirah Production of electric energy or power. Powerplants. Central stations Electric power distribution. Electric power transmission This thesis presents the solution of profit-based unit commitment (PBUC) by using particle swarm optimization (PSO) technique. In this study, the on/off scheduling of generator units will be determined based on maximizing the profit while fulfilling the constraints. The proposed solution also helps to make decision on how much power and reserve is put up in the market sale while giving maximum profit based on the price behavior in the spot market. This optimization technique is performed on a test system consisting of three and ten generating units to study the effectiveness of this method to the PBUC problems. The results are compared to conventional unit commitment problem (UCP). 2017 Thesis https://ir.uitm.edu.my/id/eprint/67309/ https://ir.uitm.edu.my/id/eprint/67309/2/67309.pdf text en public degree Universiti Teknologi MARA (UiTM) Faculty of Electrical Engineering Sheikh Rahimullah, Bibi Norasiqin
institution Universiti Teknologi MARA
collection UiTM Institutional Repository
language English
advisor Sheikh Rahimullah, Bibi Norasiqin
topic Production of electric energy or power
Powerplants
Central stations
Production of electric energy or power
Powerplants
Central stations
spellingShingle Production of electric energy or power
Powerplants
Central stations
Production of electric energy or power
Powerplants
Central stations
Baderol Iskandar, Ida Syahirah
Development of profit-based unit commitment solution using particle swarm optimization / Ida Syahirah Baderol Iskandar
description This thesis presents the solution of profit-based unit commitment (PBUC) by using particle swarm optimization (PSO) technique. In this study, the on/off scheduling of generator units will be determined based on maximizing the profit while fulfilling the constraints. The proposed solution also helps to make decision on how much power and reserve is put up in the market sale while giving maximum profit based on the price behavior in the spot market. This optimization technique is performed on a test system consisting of three and ten generating units to study the effectiveness of this method to the PBUC problems. The results are compared to conventional unit commitment problem (UCP).
format Thesis
qualification_level Bachelor degree
author Baderol Iskandar, Ida Syahirah
author_facet Baderol Iskandar, Ida Syahirah
author_sort Baderol Iskandar, Ida Syahirah
title Development of profit-based unit commitment solution using particle swarm optimization / Ida Syahirah Baderol Iskandar
title_short Development of profit-based unit commitment solution using particle swarm optimization / Ida Syahirah Baderol Iskandar
title_full Development of profit-based unit commitment solution using particle swarm optimization / Ida Syahirah Baderol Iskandar
title_fullStr Development of profit-based unit commitment solution using particle swarm optimization / Ida Syahirah Baderol Iskandar
title_full_unstemmed Development of profit-based unit commitment solution using particle swarm optimization / Ida Syahirah Baderol Iskandar
title_sort development of profit-based unit commitment solution using particle swarm optimization / ida syahirah baderol iskandar
granting_institution Universiti Teknologi MARA (UiTM)
granting_department Faculty of Electrical Engineering
publishDate 2017
url https://ir.uitm.edu.my/id/eprint/67309/2/67309.pdf
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