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Solving Hydropower Unit Commitment Problem Using a Novel Sequential Mixed Integer Linear Programming Approach

Author

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  • Alireza Amani

    (Université de Sherbrooke
    Iran University of Science and Technology)

  • Hosein Alizadeh

    (Iran University of Science and Technology)

Abstract

Hydro Unit Commitment (HUC) is an important problem of power systems and when it is dealt with via a mathematical programming approach and optimization, it leads to the complicated class of mixed-integer nonlinear programming (MINLP). Many attempts have been made to solve the problem efficiently, while there is still ongoing research to come up with better solution schemes in terms of runtime and optimality. Highly nonlinear nature of the relationships and constraints in the optimization problem have forced the researchers to deal with the HUC problem in simplified manners which may result in impractical and unreliable solutions, i.e. schedules. Here in this paper we proposed a new method based on sequential mixed-integer linear programming (MILP) for solving a more realistic version of the HUC problem efficiently. We applied the proposed method to a cascade of two hydropower plants, Karun-3 and Karun-4, located in the Southwest of Iran. The sequential MILP approach was compared with several MINLP solvers of the GAMS optimization package. The results indicated that the proposed methodology outperformed the MINLP solvers in terms of efficiency, with solution time of less than 30 s, compared to 10 min that were given to the solvers, and in terms of optimality with more than 20 thousand cubic meters per day in water release. Additionally, we have explored the effect of penalizing the total number of startups on the total release, convergence of the algorithm, and the computation time. In all of the cases the total number of startups was reduced more than three times.

Suggested Citation

  • Alireza Amani & Hosein Alizadeh, 2021. "Solving Hydropower Unit Commitment Problem Using a Novel Sequential Mixed Integer Linear Programming Approach," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(6), pages 1711-1729, April.
    • Handle: RePEc:spr:waterr:v:35:y:2021:i:6:d:10.1007_s11269-021-02806-6
    DOI: 10.1007/s11269-021-02806-6
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    References listed on IDEAS

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    1. Zhiwei Li & Tianran Jin & Shuqiang Zhao & Jinshan Liu, 2018. "Power System Day-Ahead Unit Commitment Based on Chance-Constrained Dependent Chance Goal Programming," Energies, MDPI, vol. 11(7), pages 1-20, July.
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    Cited by:

    1. Shuangquan Liu & Pengcheng Wang & Zifan Xu & Zhipeng Feng & Congtong Zhang & Jinwen Wang & Cheng Chen, 2023. "Hydropower Unit Commitment Using a Genetic Algorithm with Dynamic Programming," Energies, MDPI, vol. 16(15), pages 1-13, August.
    2. Kun Yang & Kan Yang, 2021. "Short-Term Hydro Generation Scheduling of the Three Gorges Hydropower Station Using Improver Binary-coded Whale Optimization Algorithm," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(11), pages 3771-3790, September.
    3. Kun Yang & Kan Yang, 2022. "Improved Whale Algorithm for Economic Load Dispatch Problem in Hydropower Plants and Comprehensive Performance Evaluation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(15), pages 5823-5838, December.

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