IDEAS home Printed from https://ideas.repec.org/a/spr/waterr/v35y2021i11d10.1007_s11269-021-02917-0.html
   My bibliography  Save this article

Short-Term Hydro Generation Scheduling of the Three Gorges Hydropower Station Using Improver Binary-coded Whale Optimization Algorithm

Author

Listed:
  • Kun Yang

    (Hohai University)

  • Kan Yang

    (Hohai University)

Abstract

The short-term hydropower generation scheduling (STHGS) is a complicated problem in the utilization of hydropower and water resources. An improved binary-coded whale optimization algorithm (IBWOA) is proposed in this paper to solve the complex nonlinear problem. The STHGS problem is divided into unit combination (UC) subproblem and economic load distribution (ELD) subproblem. For the UC subproblem, we use the sigmoid function (SF) to generate a binary array representing the start/stop state of the unit. The whale algorithm's search mechanism is optimized, and the inertia weight and perturbation variation strategy are introduced to improve the algorithm's optimization ability. Each generation solution is optimized by repairing the minimum uptime/downtime constraint and the spinning reserve capacity constraint. For ELD subproblem, the optimal stable load distribution table (OSLDT) is used to distribute the load quickly. The Mutation mechanism and the Locally balanced dynamic search mechanism compensate for the non-convex problems caused by start-stop constraints and stable optimal table methods. Finally, the proposal is applied to solve the STHGS of the Three Gorges Hydropower Station. When the water head is 75 m,88 m, and 107 m, the minimum water consumption calculated by the IBWOA algorithm is 1,058,323,464 m3, 892,524,696 m3, and 745,272,216 m3, respectively. Compared with the traditional whale optimization algorithm, the water consumption of the IBOWA algorithm corresponding to 75 m, 88 m, and 107 m water heads is reduced by 0.76%, 0.26%, and 0.05%, respectively. The comparison between the IBWOA algorithm and other heuristic algorithms shows that the IBWOA has good feasibility and high optimization accuracy.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:waterr:v:35:y:2021:i:11:d:10.1007_s11269-021-02917-0
    DOI: 10.1007/s11269-021-02917-0
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11269-021-02917-0
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11269-021-02917-0?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. Zhe Yang & Kan Yang & Lyuwen Su & Hu Hu, 2020. "The Short-Term Economical Operation Problem for Hydropower Station Using Chaotic Normal Cloud Model Based Discrete Shuffled Frog Leaping Algorithm," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(3), pages 905-927, February.
    4. Hu Hu & Kan Yang & Lang Liu & Lyuwen Su & Zhe Yang, 2019. "Short-Term Hydropower Generation Scheduling Using an Improved Cloud Adaptive Quantum-Inspired Binary Social Spider Optimization Algorithm," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(7), pages 2357-2379, May.
    5. Periçaro, Gislaine A. & Karas, Elizabeth W. & Gonzaga, Clóvis C. & Marcílio, Débora C. & Oening, Ana Paula & Matioli, Luiz Carlos & Detzel, Daniel H.M. & de Geus, Klaus & Bessa, Marcelo R., 2020. "Optimal non-anticipative scenarios for nonlinear hydro-thermal power systems," Applied Mathematics and Computation, Elsevier, vol. 387(C).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    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. Yang, Zhe & Wang, Yufeng & Yang, Kan, 2022. "The stochastic short-term hydropower generation scheduling considering uncertainty in load output forecasts," Energy, Elsevier, vol. 241(C).
    3. Hong Pan & Chenyang Hang & Fang Feng & Yuan Zheng & Fang Li, 2022. "Improved Neural Network Algorithm Based Flow Characteristic Curve Fitting for Hydraulic Turbines," Sustainability, MDPI, vol. 14(17), pages 1-15, August.
    4. 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.
    5. 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.
    6. Shengli Liao & Yan Zhang & Jie Liu & Benxi Liu & Zhanwei Liu, 2021. "Short-Term Peak-Shaving Operation of Single-Reservoir and Multicascade Hydropower Plants Serving Multiple Power Grids," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(2), pages 689-705, January.
    7. José García & Paola Moraga & Matias Valenzuela & Hernan Pinto, 2020. "A db-Scan Hybrid Algorithm: An Application to the Multidimensional Knapsack Problem," Mathematics, MDPI, vol. 8(4), pages 1-22, April.
    8. Hong Pan & Jie Yang & Yang Yu & Yuan Zheng & Xiaonan Zheng & Chenyang Hang, 2024. "Intelligent Low-Consumption Optimization Strategies: Economic Operation of Hydropower Stations Based on Improved LSTM and Random Forest Machine Learning Algorithm," Mathematics, MDPI, vol. 12(9), pages 1-20, April.
    9. Tong Guo & Yajing Gao & Xiaojie Zhou & Yonggang Li & Jiaomin Liu, 2018. "Optimal Scheduling of Power System Incorporating the Flexibility of Thermal Units," Energies, MDPI, vol. 11(9), pages 1-17, August.
    10. Jia Chen, 2021. "Long-Term Joint Operation of Cascade Reservoirs Using Enhanced Progressive Optimality Algorithm and Dynamic Programming Hybrid Approach," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(7), pages 2265-2279, May.
    11. Huang, Jingwei & Qin, Hui & Shen, Keyan & Yang, Yuqi & Jia, Benjun, 2024. "Study on hierarchical model of hydroelectric unit commitment based on similarity schedule and quadratic optimization approach," Energy, Elsevier, vol. 305(C).
    12. Liao, Shengli & Liu, Zhanwei & Liu, Benxi & Cheng, Chuntian & Wu, Xinyu & Zhao, Zhipeng, 2021. "Daily peak shaving operation of cascade hydropower stations with sensitive hydraulic connections considering water delay time," Renewable Energy, Elsevier, vol. 169(C), pages 970-981.
    13. Sun, Lu & Xu, Qingshan & Song, Yun, 2022. "Game-theoretic genetic-priced optimization of multiple microgrids under uncertainties," Applied Mathematics and Computation, Elsevier, vol. 426(C).
    14. Wang, Yanling & Wen, Xin & Su, Huaying & Qin, Jisen & Kong, Linghui, 2023. "Real-time dispatch of hydro-photovoltaic (PV) hybrid system based on dynamic load reserve capacity," Energy, Elsevier, vol. 285(C).
    15. He, Mengjiao & Han, Shuo & Chen, Diyi & Zhao, Ziwen & Jurasz, Jakub & Mahmud, Md Apel & Liu, Pan & Deng, Mingjiang, 2024. "Optimizing cascade Hydropower-VRE hybrid systems: A novel approach addressing whole-process vibration to enhance operational safety," Energy, Elsevier, vol. 304(C).
    16. 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.
    17. Wang, Zizhao & Wu, Feng & Li, Yang & Shi, Linjun & Lee, Kwang Y. & Wu, Jiawei, 2023. "Itô-theory-based multi-time scale dispatch approach for cascade hydropower-photovoltaic complementary system," Renewable Energy, Elsevier, vol. 202(C), pages 127-142.
    18. José García & Gino Astorga & Víctor Yepes, 2021. "An Analysis of a KNN Perturbation Operator: An Application to the Binarization of Continuous Metaheuristics," Mathematics, MDPI, vol. 9(3), pages 1-20, January.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:waterr:v:35:y:2021:i:11:d:10.1007_s11269-021-02917-0. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.