The Research of Optimal Power Dispatch

碩士 === 元智大學 === 資訊管理研究所 === 93 === In a power distribution system, all substations have their own equipment capacity to offer their power-supply area enough power. But sometimes the peak loads in their power-supply area are over than their equipment capacity. Therefore, the other substations in the...

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Main Authors: ChingYi Liu, 劉清億
Other Authors: ChaoChang Chiu
Format: Others
Language:zh-TW
Published: 2005
Online Access:http://ndltd.ncl.edu.tw/handle/34918277382316755881
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spelling ndltd-TW-093YZU003960462015-10-13T11:39:46Z http://ndltd.ncl.edu.tw/handle/34918277382316755881 The Research of Optimal Power Dispatch 電力負載移轉最佳化之研究 ChingYi Liu 劉清億 碩士 元智大學 資訊管理研究所 93 In a power distribution system, all substations have their own equipment capacity to offer their power-supply area enough power. But sometimes the peak loads in their power-supply area are over than their equipment capacity. Therefore, the other substations in the same power-supply area have to offer their power aid to the one who needs the power. However, it’s hard to determine which is the best substation to be the transferred to and power transmission path that leads the minimal power loss. We apply genetic algorithm for searching optimal power transfer order in this research. The substation can transfer electricity to each other under the condition that electricity-deficient substation can be minimized, so the goal in problem formulation is to minimize total deficient electricity in the power supply area to use electric resource fully and reach load balance. On the other hand, in order to improve the searching ability of genetic algorithm, we implement the power transfer programs by constraint-based genetic algorithm to resolve the power transfer problem in our research. Finally, we implement some experiments to compare the result of constraint-based genetic algorithm with that of genetic algorithm to show the advantages of constraint-based genetic algorithm in searching time and quality. Finally, we hope we can consider more factors in the future research. ChaoChang Chiu 邱昭彰 2005 學位論文 ; thesis 45 zh-TW
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description 碩士 === 元智大學 === 資訊管理研究所 === 93 === In a power distribution system, all substations have their own equipment capacity to offer their power-supply area enough power. But sometimes the peak loads in their power-supply area are over than their equipment capacity. Therefore, the other substations in the same power-supply area have to offer their power aid to the one who needs the power. However, it’s hard to determine which is the best substation to be the transferred to and power transmission path that leads the minimal power loss. We apply genetic algorithm for searching optimal power transfer order in this research. The substation can transfer electricity to each other under the condition that electricity-deficient substation can be minimized, so the goal in problem formulation is to minimize total deficient electricity in the power supply area to use electric resource fully and reach load balance. On the other hand, in order to improve the searching ability of genetic algorithm, we implement the power transfer programs by constraint-based genetic algorithm to resolve the power transfer problem in our research. Finally, we implement some experiments to compare the result of constraint-based genetic algorithm with that of genetic algorithm to show the advantages of constraint-based genetic algorithm in searching time and quality. Finally, we hope we can consider more factors in the future research.
author2 ChaoChang Chiu
author_facet ChaoChang Chiu
ChingYi Liu
劉清億
author ChingYi Liu
劉清億
spellingShingle ChingYi Liu
劉清億
The Research of Optimal Power Dispatch
author_sort ChingYi Liu
title The Research of Optimal Power Dispatch
title_short The Research of Optimal Power Dispatch
title_full The Research of Optimal Power Dispatch
title_fullStr The Research of Optimal Power Dispatch
title_full_unstemmed The Research of Optimal Power Dispatch
title_sort research of optimal power dispatch
publishDate 2005
url http://ndltd.ncl.edu.tw/handle/34918277382316755881
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