Stochastic short-term hydropower planning with inflow scenario trees
Sara Séguin,
Stein-Erik Fleten,
Pascal Côté,
Alois Pichler and
Charles Audet
European Journal of Operational Research, 2017, vol. 259, issue 3, 1156-1168
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.
Keywords: Large scale optimization; Nonlinear programming; OR in energy; Scenarios; Stochastic programming (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (18)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:ejores:v:259:y:2017:i:3:p:1156-1168
DOI: 10.1016/j.ejor.2016.11.028
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