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An MILP model based on a processing strategy of complex multisource constraints for the short-term peak shaving operation of large-scale cascaded hydropower plants

Author

Listed:
  • Fang, Zhou
  • Liao, Shengli
  • Zhao, Hongye
  • Cheng, Chuntian
  • Liu, Benxi
  • Wang, Huan
  • Li, Shushan

Abstract

Hydropower with flexible regulation plays an important role in short-term peak shaving operations. However, short-term peak shaving operation is a challenging problem due to the large scale, the nonconvex and nonlinear characteristics, and the complex multisource tasks. This study proposes a mixed integer linear programming (MILP) model, termed MILPoPSC, based on a processing strategy for complex multisource constraints, tailored for short-term peak shaving in large-scale cascaded hydropower plants. The MILP model, designed to incorporate multisource tasks by abstracting them into constraints, ensures that task requirements are met. A novel multisource constraint transformation method is introduced to derive constraint expressions related to power flow, facilitating the unification of constrained variables. Additionally, a classification and integration method based on restriction mode and set theory is proposed to improve solving efficiency by integrating constrains of the same type. The proposed method was applied to 7 hydropower cascade plants in the Wujiang River. The results showed that the linearization method and the processing strategy of complex multisource constraints can successfully reduce the complexity of the MILP model without affecting the solution quality. This indicates that MILPoPSC has good practical value for the short-term peak shaving operation of large-scale cascaded hydropower plants in China.

Suggested Citation

  • Fang, Zhou & Liao, Shengli & Zhao, Hongye & Cheng, Chuntian & Liu, Benxi & Wang, Huan & Li, Shushan, 2024. "An MILP model based on a processing strategy of complex multisource constraints for the short-term peak shaving operation of large-scale cascaded hydropower plants," Renewable Energy, Elsevier, vol. 231(C).
    • Handle: RePEc:eee:renene:v:231:y:2024:i:c:s0960148124010000
    DOI: 10.1016/j.renene.2024.120932
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    as
    1. Chaudhari, Vimal N. & Shah, Samip P., 2024. "Performance enhancement of savonius hydrokinetic turbine using split airfoil blade: A numerical investigation," Renewable Energy, Elsevier, vol. 224(C).
    2. Su, Chengguo & Wang, Peilin & Yuan, Wenlin & Wu, Yang & Jiang, Feng & Wu, Zening & Yan, Denghua, 2022. "Short-term optimal scheduling of cascade hydropower plants with reverse-regulating effects," Renewable Energy, Elsevier, vol. 199(C), pages 395-406.
    3. Sheng-li Liao & Ben-xi Liu & Chun-tian Cheng & Zhi-fu Li & Xin-yu Wu, 2017. "Long-Term Generation Scheduling of Hydropower System Using Multi-Core Parallelization of Particle Swarm Optimization," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(9), pages 2791-2807, July.
    4. Moura de Figueiredo, Nelio & Cavalcante Blanco, Claudio José & Pinheiro Campos Filho, Lúcio Carlos & Amarante Mesquita, André Luiz, 2023. "MUWOS - Multiple use water optimization system for the power generation and navigation trade-offs analysis," Renewable Energy, Elsevier, vol. 203(C), pages 205-218.
    5. Jose M. Gonzalez & Marcelo A. Olivares & Josué Medellín-Azuara & Rodrigo Moreno, 2020. "Multipurpose Reservoir Operation: a Multi-Scale Tradeoff Analysis between Hydropower Generation and Irrigated Agriculture," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(9), pages 2837-2849, July.
    6. Fang, Zhou & Liao, Shengli & Cheng, Chuntian & Zhao, Hongye & Liu, Benxi & Su, Huaying, 2023. "Parallel improved DPSA algorithm for medium-term optimal scheduling of large-scale cascade hydropower plants," Renewable Energy, Elsevier, vol. 210(C), pages 134-147.
    7. M. Afshar & R. Moeini, 2008. "Partially and Fully Constrained Ant Algorithms for the Optimal Solution of Large Scale Reservoir Operation Problems," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 22(12), pages 1835-1857, December.
    8. Rashid, Muhammad Usman & Abid, Irfan & Latif, Abid, 2022. "Optimization of hydropower and related benefits through Cascade Reservoirs for sustainable economic growth," Renewable Energy, Elsevier, vol. 185(C), pages 241-254.
    9. Liu, Benxi & Cheng, Chuntian & Wang, Sen & Liao, Shengli & Chau, Kwok-Wing & Wu, Xinyu & Li, Weidong, 2018. "Parallel chance-constrained dynamic programming for cascade hydropower system operation," Energy, Elsevier, vol. 165(PA), pages 752-767.
    10. Suiling Wang & Zhiqiang Jiang & Yi Liu, 2022. "Dimensionality Reduction Method of Dynamic Programming under Hourly Scale and Its Application in Optimal Scheduling of Reservoir Flood Control," Energies, MDPI, vol. 15(3), pages 1-17, January.
    11. Feng, Zhong-kai & Niu, Wen-jing & Cheng, Chun-tian, 2019. "China’s large-scale hydropower system: operation characteristics, modeling challenge and dimensionality reduction possibilities," Renewable Energy, Elsevier, vol. 136(C), pages 805-818.
    12. Bhatti, Bilal Ahmad & Hanif, Sarmad & Alam, Jan & Mitra, Bhaskar & Kini, Roshan & Wu, Di, 2023. "Using energy storage systems to extend the life of hydropower plants," Applied Energy, Elsevier, vol. 337(C).
    13. Zhao, Hongye & Liao, Shengli & Fang, Zhou & Liu, Benxi & Ma, Xiangyu & Lu, Jia, 2024. "Short-term peak-shaving operation of “N-reservoirs and multicascade” large-scale hydropower systems based on a decomposition-iteration strategy," Energy, Elsevier, vol. 288(C).
    14. Sebastian Sterl & Inne Vanderkelen & Celray James Chawanda & Daniel Russo & Robert J. Brecha & Ann Griensven & Nicole P. M. Lipzig & Wim Thiery, 2020. "Smart renewable electricity portfolios in West Africa," Nature Sustainability, Nature, vol. 3(9), pages 710-719, September.
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