IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v13y2020i10p2477-d358030.html
   My bibliography  Save this article

Short-Term Scheduling of Expected Output-Sensitive Cascaded Hydro Systems Considering the Provision of Reserve Services

Author

Listed:
  • Ruhong Zhong

    (Institute of Hydropower System & Hydroinformatics, Dalian University of Technology, Dalian 116024, China)

  • Chuntian Cheng

    (Institute of Hydropower System & Hydroinformatics, Dalian University of Technology, Dalian 116024, China
    Key Laboratory of Ocean Energy Utilization and Energy Conservation of Ministry of Education, Dalian University of Technology, Dalian 116024, China)

  • Shengli Liao

    (Institute of Hydropower System & Hydroinformatics, Dalian University of Technology, Dalian 116024, China
    Key Laboratory of Ocean Energy Utilization and Energy Conservation of Ministry of Education, Dalian University of Technology, Dalian 116024, China)

  • Zhipeng Zhao

    (Institute of Hydropower System & Hydroinformatics, Dalian University of Technology, Dalian 116024, China)

Abstract

The integration of large-scale wind and solar power into the power grid brings new challenges to the security and stability of power systems because of the uncertainty and intermittence of wind and solar power. This sensitive expected output has real implications for short-term hydro scheduling (STHS), which provides reserve services to alleviate electrical perturbations from wind and solar power. This paper places an emphasis on the sensitive expected output characteristics of hydro plants and their effect on reserve services. The multi-step progressive optimality algorithm (MSPOA) is used for the STHS problem. An iterative approximation method is proposed to determine the forebay level and output under the condition of the sensitive expected output. Cascaded hydro plants in the Wujiang River are selected as an example. The results illustrate that the method can achieve good performance for peak shaving and reserve services. The proposed approach is both accurate and computationally acceptable so that the obtained hydropower schedules are in accordance with practical circumstances and the reserve can cope with renewable power fluctuations effectively.

Suggested Citation

  • Ruhong Zhong & Chuntian Cheng & Shengli Liao & Zhipeng Zhao, 2020. "Short-Term Scheduling of Expected Output-Sensitive Cascaded Hydro Systems Considering the Provision of Reserve Services," Energies, MDPI, vol. 13(10), pages 1-15, May.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:10:p:2477-:d:358030
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/13/10/2477/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/13/10/2477/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Sedghi, Mahdi & Ahmadian, Ali & Aliakbar-Golkar, Masoud, 2016. "Assessment of optimization algorithms capability in distribution network planning: Review, comparison and modification techniques," Renewable and Sustainable Energy Reviews, Elsevier, vol. 66(C), pages 415-434.
    2. Wang, Xianxun & Mei, Yadong & Kong, Yanjun & Lin, Yuru & Wang, Hao, 2017. "Improved multi-objective model and analysis of the coordinated operation of a hydro-wind-photovoltaic system," Energy, Elsevier, vol. 134(C), pages 813-839.
    3. Yong-Gi Park & Jong-Bae Park & Namsu Kim & Kwang Y. Lee, 2017. "Linear Formulation for Short-Term Operational Scheduling of Energy Storage Systems in Power Grids," Energies, MDPI, vol. 10(2), pages 1-16, February.
    4. Hamid Bashiri-Atrabi & Kourosh Qaderi & David Rheinheimer & Erfaneh Sharifi, 2015. "Application of Harmony Search Algorithm to Reservoir Operation Optimization," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(15), pages 5729-5748, December.
    5. Nazari-Heris, M. & Mohammadi-Ivatloo, B. & Haghrah, A., 2017. "Optimal short-term generation scheduling of hydrothermal systems by implementation of real-coded genetic algorithm based on improved Mühlenbein mutation," Energy, Elsevier, vol. 128(C), pages 77-85.
    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. 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).

    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. Thibaut Cuvelier & Pierre Archambeau & Benjamin Dewals & Quentin Louveaux, 2018. "Comparison Between Robust and Stochastic Optimisation for Long-term Reservoir Management Under Uncertainty," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(5), pages 1599-1614, March.
    2. Yin, Yue & Liu, Tianqi & He, Chuan, 2019. "Day-ahead stochastic coordinated scheduling for thermal-hydro-wind-photovoltaic systems," Energy, Elsevier, vol. 187(C).
    3. Wang, Jin & Zhao, Zhipeng & Zhou, Jinglin & Cheng, Chuntian & Su, Huaying, 2024. "Developing operating rules for a hydro–wind–solar hybrid system considering peak-shaving demands," Applied Energy, Elsevier, vol. 360(C).
    4. Mojtaba Moravej & Seyed-Mohammad Hosseini-Moghari, 2016. "Large Scale Reservoirs System Operation Optimization: the Interior Search Algorithm (ISA) Approach," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(10), pages 3389-3407, August.
    5. Lei, Kaixuan & Chang, Jianxia & Long, Ruihao & Wang, Yimin & Zhang, Hongxue, 2022. "Cascade hydropower station risk operation under the condition of inflow uncertainty," Energy, Elsevier, vol. 244(PA).
    6. Ting Wang & Qiya Wang & Caiqing Zhang, 2021. "Research on the Optimal Operation of a Novel Renewable Multi-Energy Complementary System in Rural Areas," Sustainability, MDPI, vol. 13(4), pages 1-16, February.
    7. Yang, Yuqi & Zhou, Jianzhong & Liu, Guangbiao & Mo, Li & Wang, Yongqiang & Jia, Benjun & He, Feifei, 2020. "Multi-plan formulation of hydropower generation considering uncertainty of wind power," Applied Energy, Elsevier, vol. 260(C).
    8. Wei, Hu & Hongxuan, Zhang & Yu, Dong & Yiting, Wang & Ling, Dong & Ming, Xiao, 2019. "Short-term optimal operation of hydro-wind-solar hybrid system with improved generative adversarial networks," Applied Energy, Elsevier, vol. 250(C), pages 389-403.
    9. Panda, Debashish & Ramteke, Manojkumar, 2019. "Preventive crude oil scheduling under demand uncertainty using structure adapted genetic algorithm," Applied Energy, Elsevier, vol. 235(C), pages 68-82.
    10. Li, He & Liu, Pan & Guo, Shenglian & Cheng, Lei & Huang, Kangdi & Feng, Maoyuan & He, Shaokun & Ming, Bo, 2021. "Deriving adaptive long-term complementary operating rules for a large-scale hydro-photovoltaic hybrid power plant using ensemble Kalman filter," Applied Energy, Elsevier, vol. 301(C).
    11. Vartika Paliwal & Aniruddha D. Ghare & Ashwini B. Mirajkar & Neeraj Dhanraj Bokde & Andrés Elías Feijóo Lorenzo, 2019. "Computer Modeling for the Operation Optimization of Mula Reservoir, Upper Godavari Basin, India, Using the Jaya Algorithm," Sustainability, MDPI, vol. 12(1), pages 1-21, December.
    12. Gokmen Tayfur, 2017. "Modern Optimization Methods in Water Resources Planning, Engineering and Management," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(10), pages 3205-3233, August.
    13. Yuan, Wenlin & Wang, Xinqi & Su, Chengguo & Cheng, Chuntian & Liu, Zhe & Wu, Zening, 2021. "Stochastic optimization model for the short-term joint operation of photovoltaic power and hydropower plants based on chance-constrained programming," Energy, Elsevier, vol. 222(C).
    14. Candas, Soner & Reveron Baecker, Beneharo & Mohapatra, Anurag & Hamacher, Thomas, 2023. "Optimization-based framework for low-voltage grid reinforcement assessment under various levels of flexibility and coordination," Applied Energy, Elsevier, vol. 343(C).
    15. Liu, Yi & Zhang, Jian & Liu, Zhe & Chen, Long & Yu, Xiaodong, 2022. "Surge wave characteristics for hydropower plant with upstream double surge tanks connected in series under small load disturbance," Renewable Energy, Elsevier, vol. 186(C), pages 667-676.
    16. Geng, Xinmin & Zhou, Ye & Zhao, Weiqiang & Shi, Li & Chen, Diyi & Bi, Xiaojian & Xu, Beibei, 2024. "Pricing ancillary service of a Francis hydroelectric generating system to promote renewable energy integration in a clean energy base: Tariff compensation of deep peak regulation," Renewable Energy, Elsevier, vol. 226(C).
    17. Zhang, Yusheng & Ma, Chao & Yang, Yang & Pang, Xiulan & Liu, Lu & Lian, Jijian, 2021. "Study on short-term optimal operation of cascade hydro-photovoltaic hybrid systems," Applied Energy, Elsevier, vol. 291(C).
    18. Ming, Bo & Liu, Pan & Guo, Shenglian & Cheng, Lei & Zhou, Yanlai & Gao, Shida & Li, He, 2018. "Robust hydroelectric unit commitment considering integration of large-scale photovoltaic power: A case study in China," Applied Energy, Elsevier, vol. 228(C), pages 1341-1352.
    19. Zhang, Xinshuo & Huang, Weibin & Chen, Shijun & Xie, Diya & Liu, Dexu & Ma, Guangwen, 2020. "Grid–source coordinated dispatching based on heterogeneous energy hybrid power generation," Energy, Elsevier, vol. 205(C).
    20. Papadimitrakis, M. & Giamarelos, N. & Stogiannos, M. & Zois, E.N. & Livanos, N.A.-I. & Alexandridis, A., 2021. "Metaheuristic search in smart grid: A review with emphasis on planning, scheduling and power flow optimization applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 145(C).

    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:gam:jeners:v:13:y:2020:i:10:p:2477-:d:358030. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.