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• W3022975542 abstract "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." @default.
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• W3022975542 date "2017-06-01" @default.
• W3022975542 modified "2023-10-18" @default.
• W3022975542 title "Stochastic short-term hydropower planning with inflow scenario trees" @default.
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• W3022975542 doi "https://doi.org/10.1016/j.ejor.2016.11.028" @default.
• W3022975542 hasPublicationYear "2017" @default.
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