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Hydropower unit commitment with nonlinearity decoupled from mixed integer nonlinear problem

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  • Wang, Jinwen
  • Guo, Min
  • Liu, Yong

Abstract

This paper formulates a nonlinear and discrete hydropower unit commitment (UC) problem, which is particular useful to coordinate with the higher level operation of cascaded hydropower reservoirs. Given the outflow process, this UC problem maximizes energy production during a planning horizon, to determine the unit operating zones and allocate the release among units in one hydroplant. This work shows how the constraints on the start-up number and up/down hours can be transformed into linear equations. The objective is equivalently interpreted to sequentially minimize spillages, maximize generation efficiency, and maximize energy production, which makes it possible to handle the nonlinearity in a low-dimensional space due to the lowest priority of the third sub-objective where the nonlinearity comes. The UC problem is skillfully decomposed into a zone commitment (ZC) that determines the optimal operating zones using the mixed integer linear programming, and one-stage sub-problems that allocate the outflow among units using the hill-climbing method. The case studies that deal with quarter-hourly hydropower unit commitments during a day show that the present model and procedure turn out to be efficient for a UC problem with up to four units, becoming volatile then on, but still acceptable for up to nine units.

Suggested Citation

  • Wang, Jinwen & Guo, Min & Liu, Yong, 2018. "Hydropower unit commitment with nonlinearity decoupled from mixed integer nonlinear problem," Energy, Elsevier, vol. 150(C), pages 839-846.
    • Handle: RePEc:eee:energy:v:150:y:2018:i:c:p:839-846
    DOI: 10.1016/j.energy.2018.02.128
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    Cited by:

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    2. 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.
    3. de Oliveira, Glauber Cardoso & Bertone, Edoardo & Stewart, Rodney A., 2022. "Challenges, opportunities, and strategies for undertaking integrated precinct-scale energy–water system planning," Renewable and Sustainable Energy Reviews, Elsevier, vol. 161(C).
    4. Cheng, Xianliang & Feng, Suzhen & Zheng, Hao & Wang, Jinwen & Liu, Shuangquan, 2022. "A hierarchical model in short-term hydro scheduling with unit commitment and head-dependency," Energy, Elsevier, vol. 251(C).
    5. Harun Or Rashid Howlader & Oludamilare Bode Adewuyi & Ying-Yi Hong & Paras Mandal & Ashraf Mohamed Hemeida & Tomonobu Senjyu, 2019. "Energy Storage System Analysis Review for Optimal Unit Commitment," Energies, MDPI, vol. 13(1), pages 1-21, December.
    6. Pan, Jeng-Shyang & Hu, Pei & Chu, Shu-Chuan, 2021. "Binary fish migration optimization for solving unit commitment," Energy, Elsevier, vol. 226(C).
    7. Razavi, Seyed-Ehsan & Esmaeel Nezhad, Ali & Mavalizadeh, Hani & Raeisi, Fatima & Ahmadi, Abdollah, 2018. "Robust hydrothermal unit commitment: A mixed-integer linear framework," Energy, Elsevier, vol. 165(PB), pages 593-602.
    8. Hassan Shokouhandeh & Mehrdad Ahmadi Kamarposhti & Ilhami Colak & Kei Eguchi, 2021. "Unit Commitment for Power Generation Systems Based on Prices in Smart Grid Environment Considering Uncertainty," Sustainability, MDPI, vol. 13(18), pages 1-13, September.
    9. Iram Parvez & Jianjian Shen & Ishitaq Hassan & Nannan Zhang, 2021. "Generation of Hydro Energy by Using Data Mining Algorithm for Cascaded Hydropower Plant," Energies, MDPI, vol. 14(2), pages 1-28, January.

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