The purchasing policy based on robust optimization in the electric power supply chain under cost uncertainty

Jian Wang, Huixia Liu, Kuijun Yu, Qunzhi Wang, Hiroaki Matsukawa

研究成果: Conference contribution

抄録

With the national policy reforming, how to decide the power purchasing policy under the uncertain fuel cost becomes the important question for the power grid enterprises in the Chinese electric power supply chain. Usually, the stochastic programming models are often used for the solution. A new robust optimization model was built and the numerical experiment results were compared with the results from the stochastic programming model. The results show that the robust optimization model is more flexible than the stochastic programming model in the worst situation. Comparing the result from the stochastic programming with the small uncertainty range, the robust optimization's objective function may have higher value. The solution based on the application of both the robust model and the stochastic model was suggested in response to the required robustness and uncertainty level.

本文言語English
ホスト出版物のタイトルICLEM 2014
ホスト出版物のサブタイトルSystem Planning, Supply Chain Management, and Safety - Proceedings of the 2014 International Conference of Logistics Engineering and Management
編集者Jin Zhang, Xiaoqiang Zhang, Ping Yi, Kun Wang
出版社American Society of Civil Engineers (ASCE)
ページ7-13
ページ数7
ISBN(電子版)9780784413753
DOI
出版ステータスPublished - 2014
イベント2014 4th International Conference of Logistics Engineering and Management: System Planning, Supply Chain Management, and Safety, ICLEM 2014 - Shanghai, China
継続期間: 2014 10 92014 10 11

出版物シリーズ

名前ICLEM 2014: System Planning, Supply Chain Management, and Safety - Proceedings of the 2014 International Conference of Logistics Engineering and Management

Other

Other2014 4th International Conference of Logistics Engineering and Management: System Planning, Supply Chain Management, and Safety, ICLEM 2014
CountryChina
CityShanghai
Period14/10/914/10/11

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Industrial and Manufacturing Engineering

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