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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2017
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Online Access: | https://ir.uitm.edu.my/id/eprint/67309/2/67309.pdf |
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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 |
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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 |
_version_ |
1783735677615079424 |