Re-Scheduling of Unit Commitment Based on Customers' Fuzzy Requirements for Power Reliability
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- WANG Bo
- Department of Production, Graduate School of IPS, Waseda University
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- LI You
- Department of Production, Graduate School of IPS, Waseda University
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- WATADA Junzo
- Department of Production, Graduate School of IPS, Waseda University
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The development of the electricity market enables us to provide electricity of varied quality and price in order to fulfill power consumers' needs. Such customers choices should influence the process of adjusting power generation and spinning reserve, and, as a result, change the structure of a unit commitment optimization problem (UCP). To build a unit commitment model that considers customer choices, we employ fuzzy variables in this study to better characterize customer requirements and forecasted future power loads. To measure system reliability and determine the schedule of real power generation and spinning reserve, fuzzy Value-at-Risk (VaR) is utilized in building the model, which evaluates the peak values of power demands under given confidence levels. Based on the information obtained using fuzzy VaR, we proposed a heuristic algorithm called local convergence-averse binary particle swarm optimization (LCA-PSO) to solve the UCP. The proposed model and algorithm are used to analyze several test systems. Comparisons between the proposed algorithm and the conventional approaches show that the LCA-PSO performs better in finding the optimal solutions.
収録刊行物
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- IEICE Transactions on Information and Systems
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IEICE Transactions on Information and Systems E94-D (7), 1378-1385, 2011
一般社団法人 電子情報通信学会
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詳細情報 詳細情報について
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- CRID
- 1390282679354095360
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- NII論文ID
- 10029805420
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- NII書誌ID
- AA10826272
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- ISSN
- 17451361
- 09168532
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- 本文言語コード
- en
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- データソース種別
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- JaLC
- Crossref
- CiNii Articles
- KAKEN
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