Stochastic short-term hydropower planning with inflow scenario trees

DOI10.1016/j.ejor.2016.11.028zbMath1402.90224OpenAlexW3022975542MaRDI QIDQ1751942

Alois Pichler, Charles Audet, Sara Séguin, Stein-Erik Fleten, Pascal Côté

Publication date: 25 May 2018

Published in: European Journal of Operational Research (Search for Journal in Brave)

Full work available at URL: https://constellation.uqac.ca/4676/1/__sfserv_sbi%24_n2villen_Mes%20Documents_Services%20aux%20chercheurs_Sara%20S%C3%A9guin_Stochastic%20short-term%20hydropower%20planning%20with%20in.pdf

zbMATH Keywords

stochastic programmingnonlinear programmingscenariosOR in energylarge scale optimization

Mathematics Subject Classification ID

Applications of mathematical programming (90C90) Nonlinear programming (90C30) Stochastic programming (90C15) Case-oriented studies in operations research (90B90)

Related Items (9)

Finding multiple Nash equilibria via machine learning-supported Gröbner bases ⋮ Progressive hedging for stochastic programs with cross-scenario inequality constraints ⋮ Intraday power trading: toward an arms race in weather forecasting? ⋮ Distributionally robust optimization with multiple time scales: valuation of a thermal power plant ⋮ Large-scale unit commitment under uncertainty: an updated literature survey ⋮ Climate-aware generation and transmission expansion planning: a three-stage robust optimization approach ⋮ Accelerating Benders decomposition for short-term hydropower maintenance scheduling ⋮ Planning of cascade hydropower stations with the consideration of long-term operations under uncertainties ⋮ Optimized operating rules for short-term hydropower planning in a stochastic environment

Uses Software

• Matlab
• AMPL
• Ipopt
• XPRESS

Cites Work

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• Modeling with Stochastic Programming
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• Least squares quantization in PCM
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