A Solution Method of Unit Commitment Problem by Means of Neural Network
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- Sasaki Hiroshi
- Hiroshima University
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- Fujii Yuhji
- Hiroshima University
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- Watanabe Masahiro
- Hiroshima University
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- Kubokawa Junji
- Hiroshima University
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- Yorino Naoto
- Hiroshima University
Bibliographic Information
- Other Title
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- ニューラルネットワークによる発電機起動停止計画問題の一解法
- ニューラル ネットワーク ニ ヨル ハツデンキ キドウ テイシ ケイカク モン
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Abstract
This paper studies the feasibility of applying the Hopfield type neural network to unit commitment problems of a large power system. The unit commitment problem is to determine an optimal schedule of what thermal units must be started or shut off to meet the anticipated demand; it can be formulated as a complicated mixed integer programming problem with a number of equality and inequality constraints. In our approach, the neural network gives the on/off states of thermal units at each period and then the output power of each unit is adjusted to meet the total demand. Another feature of our approach is that an adhoc neural network is installed to satisfy inequality constraints which take into account spinning reserve constraints and minimum up/down time constraints. The proposed neural network approach has been applied to solve a unit commitment problem of 30 units over 24 periods; results obtained were close to those by the Lagrangian relaxation method.
Journal
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- IEEJ Transactions on Power and Energy
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IEEJ Transactions on Power and Energy 111 (7), 729-734, 1991
The Institute of Electrical Engineers of Japan
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Keywords
Details 詳細情報について
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- CRID
- 1390282679580886400
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- NII Article ID
- 130006840745
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- NII Book ID
- AN10136334
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- ISSN
- 13488147
- 03854213
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- NDL BIB ID
- 3730236
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- Data Source
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- JaLC
- NDL
- Crossref
- CiNii Articles
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- Abstract License Flag
- Disallowed