Stochastic hydrothermal unit commitment models via stabilized benders decomposition

Colonetti, Bruno; Finardi, Erlon Cristian

doi:10.1007/s00202-020-01206-0

Cited by 6 publications

(1 citation statement)

References 18 publications

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“…We refer to (Parvez et al, 2019;Kong et al, 2020;Thaeer Hammid et al, 2020) for more solution methods on the HUC problem. Recently, decomposition methods, including dual decomposition (Finardi and da Silva, 2006), Benders Decomposition (BD) (Benders, 2005;Moiseeva and Hesam zadeh, 2017;Colonetti and Finardi, 2021), and SDDP (Helseth et al, 2016;Hjelmeland et al, 2019) have gained more and more attention in the hydropower generation scheduling problems due to their good computational performance. SDDP is a state-of-the-art algorithm for longand medium-term hydropower scheduling problems (Hjelmeland et al, 2019).…”

Section: Frontiers In Energy Researchmentioning

confidence: 99%

Solving stochastic hydro unit commitment using benders decomposition and modified stochastic dual dynamic programming

Yang

et al. 2022

Front. Energy Res.

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This paper proposes a stochastic hydro unit commitment (SHUC) model for a price-taker hydropower producer in a liberalized market. The objective is to maximize the total revenue of the hydropower producer, including the immediate revenue, future revenue (i.e., opportunity cost), and startup and shutdown cost. The market price uncertainty is taken into account through the scenario tree. The solution of the model is a challenging task due to its non-convex and high-dimensional characteristics. A solution method based on the Benders Decomposition (BD) and Modified Stochastic Dual Dynamic Programming (MSDDP) is proposed to solve the problem efficiently. Firstly, the BD is applied to decompose the original problem into a Benders master problem representing the hydro unit commitment and a Benders subproblem representing the optimal operation of the hydropower plants. The Benders subproblem, which contains a large number of integer variables, is further decomposed by the period and solved by the MSDDP proposed in this paper. Finally, we verify the effectiveness of the SHUC model and the performance of the proposed solution method in case studies.

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Section: Frontiers In Energy Researchmentioning

confidence: 99%

Solving stochastic hydro unit commitment using benders decomposition and modified stochastic dual dynamic programming

Yang

et al. 2022

Front. Energy Res.

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Hydro Thermal Unit Commitment involving Demand Response resources: a MILP formulation

et al. 2022

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A Comparison of Cost and Emission Reduction Efficacy of Wind Energy in Hydrothermal Systems

Samal

2023

Iran J Sci Technol Trans Electr Eng

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Stochastic hydrothermal unit commitment models via stabilized benders decomposition

Cited by 6 publications

References 18 publications

Solving stochastic hydro unit commitment using benders decomposition and modified stochastic dual dynamic programming

Solving stochastic hydro unit commitment using benders decomposition and modified stochastic dual dynamic programming

Hydro Thermal Unit Commitment involving Demand Response resources: a MILP formulation

A Comparison of Cost and Emission Reduction Efficacy of Wind Energy in Hydrothermal Systems

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