4.7 Article

Stochastic short-term hydropower planning with inflow scenario trees

期刊

EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
卷 259, 期 3, 页码 1156-1168

出版社

ELSEVIER
DOI: 10.1016/j.ejor.2016.11.028

关键词

Large scale optimization; Nonlinear programming; OR in energy; Scenarios; Stochastic programming

资金

  1. NSERC
  2. FRQNT
  3. Rio Tinto
  4. FRQNT through GERAD allowed the research
  5. Research Council of Norway [243964/E20]

向作者/读者索取更多资源

This paper presents an optimization approach to solve the short-term hydropower unit commitment and loading problem with uncertain inflows. A scenario tree is built based on a forecasted fan of inflows, which is developed using the weather forecast and the historical weather realizations. The tree-building approach seeks to minimize the nested distance between the stochastic process of historical inflow data and the multistage stochastic process represented in the scenario tree. A two-phase multistage stochastic model is used to solve the problem. The proposed approach is tested on a 31 day rolling-horizon with daily forecasted inflows for three power plants situated in the province of Quebec, Canada, that belong to the company Rio Tinto. (C) 2016 Elsevier B.V. All rights reserved.

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