IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v17y2024i4p772-d1334270.html
   My bibliography  Save this article

Consideration of Multi-Objective Stochastic Optimization in Inter-Annual Optimization Scheduling of Cascade Hydropower Stations

Author

Listed:
  • Jun Jia

    (College of Transportation Engineering, Nanjing Tech University, Nanjing 211899, China)

  • Guangming Zhang

    (College of Electrical Engineering and Control Science, Nanjing Tech University, Nanjing 211899, China)

  • Xiaoxiong Zhou

    (College of Electrical Engineering and Control Science, Nanjing Tech University, Nanjing 211899, China)

  • Mingxiang Zhu

    (Taizhou College, Nanjing Normal University, Taizhou 225300, China)

  • Zhihan Shi

    (College of Electrical Engineering and Control Science, Nanjing Tech University, Nanjing 211899, China)

  • Xiaodong Lv

    (College of Electrical Engineering and Control Science, Nanjing Tech University, Nanjing 211899, China)

Abstract

There exists a temporal and spatial coupling effect among the hydropower units in cascade hydropower stations which constitutes a complex planning problem. Researching the multi-objective optimization scheduling of cascade hydropower stations under various spatiotemporal inflow impacts is of significant importance. Previous studies have typically only focused on the economic dispatch issues of cascade hydropower stations, with little attention given to their coupling mechanism models and the uncertainty impacts of inflows. Firstly, this paper establishes a coupled optimization scheduling model for cascade hydropower stations and elaborates on the operational mechanism of cascade hydropower stations. Secondly, according to the needs of actual scenarios, two types of optimization objectives are set, considering both the supply adequacy and peak-shaving capacity as indicators, with the total residual load and the peak-valley difference of the residual load as comprehensive optimization objectives. Subsequently, considering the uncertainty impact of the inflow side, a stochastic optimization model for inflow is established based on a normal distribution probability. Finally, case study analyses demonstrate that the proposed model not only effectively achieves supply stability but also reduces the peak-valley difference in load, and can achieve optimized scheduling under the uncertain environment of inflow.

Suggested Citation

  • Jun Jia & Guangming Zhang & Xiaoxiong Zhou & Mingxiang Zhu & Zhihan Shi & Xiaodong Lv, 2024. "Consideration of Multi-Objective Stochastic Optimization in Inter-Annual Optimization Scheduling of Cascade Hydropower Stations," Energies, MDPI, vol. 17(4), pages 1-18, February.
  • Handle: RePEc:gam:jeners:v:17:y:2024:i:4:p:772-:d:1334270
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/17/4/772/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/17/4/772/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ding, Huajie & Hu, Zechun & Song, Yonghua, 2012. "Stochastic optimization of the daily operation of wind farm and pumped-hydro-storage plant," Renewable Energy, Elsevier, vol. 48(C), pages 571-578.
    2. O., Yugeswar Reddy & J., Jithendranath & Chakraborty, Ajoy Kumar & Guerrero, Josep M., 2022. "Stochastic optimal power flow in islanded DC microgrids with correlated load and solar PV uncertainties," Applied Energy, Elsevier, vol. 307(C).
    3. Yao, Zhaosheng & Wang, Zhiyuan & Ran, Lun, 2023. "Smart charging and discharging of electric vehicles based on multi-objective robust optimization in smart cities," Applied Energy, Elsevier, vol. 343(C).
    4. Rahim, Sahar & Wang, Zhen & Ju, Ping, 2022. "Overview and applications of Robust optimization in the avant-garde energy grid infrastructure: A systematic review," Applied Energy, Elsevier, vol. 319(C).
    5. Rauf, Huzaifa & Gull, Muhammad Shuzub & Arshad, Naveed, 2020. "Complementing hydroelectric power with floating solar PV for daytime peak electricity demand," Renewable Energy, Elsevier, vol. 162(C), pages 1227-1242.
    Full references (including those not matched with items on IDEAS)

    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. Ardizzon, G. & Cavazzini, G. & Pavesi, G., 2014. "A new generation of small hydro and pumped-hydro power plants: Advances and future challenges," Renewable and Sustainable Energy Reviews, Elsevier, vol. 31(C), pages 746-761.
    2. Yıldıran, Uğur & Kayahan, İsmail, 2018. "Risk-averse stochastic model predictive control-based real-time operation method for a wind energy generation system supported by a pumped hydro storage unit," Applied Energy, Elsevier, vol. 226(C), pages 631-643.
    3. Ma, Chao & Liu, Zhao, 2022. "Water-surface photovoltaics: Performance, utilization, and interactions with water eco-environment," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).
    4. Kenfack, Joseph & Nzotcha, Urbain & Voufo, Joseph & Ngohe-Ekam, Paul Salomon & Nsangou, Jean Calvin & Bignom, Blaise, 2021. "Cameroon's hydropower potential and development under the vision of Central Africa power pool (CAPP): A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 151(C).
    5. Shaohua Hu & Xinlong Zhou & Yi Luo & Guang Zhang, 2019. "Numerical Simulation Three-Dimensional Nonlinear Seepage in a Pumped-Storage Power Station: Case Study," Energies, MDPI, vol. 12(1), pages 1-15, January.
    6. Ming, Zeng & Junjie, Feng & Song, Xue & Zhijie, Wang & Xiaoli, Zhu & Yuejin, Wang, 2013. "Development of China's pumped storage plant and related policy analysis," Energy Policy, Elsevier, vol. 61(C), pages 104-113.
    7. Thomas, Dimitrios & Deblecker, Olivier & Ioakimidis, Christos S., 2016. "Optimal design and techno-economic analysis of an autonomous small isolated microgrid aiming at high RES penetration," Energy, Elsevier, vol. 116(P1), pages 364-379.
    8. Su, Chengguo & Cheng, Chuntian & Wang, Peilin & Shen, Jianjian & Wu, Xinyu, 2019. "Optimization model for long-distance integrated transmission of wind farms and pumped-storage hydropower plants," Applied Energy, Elsevier, vol. 242(C), pages 285-293.
    9. Helge Bormann & Inge Andersen Martinez, 2014. "Towards an Indicator Based Framework Analysing the Suitability of Existing Dams for Energy Storage," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(6), pages 1613-1630, April.
    10. Hilario J. Torres-Herrera & Alexis Lozano-Medina, 2021. "Methodological Proposal for the Assessment Potential of Pumped Hydropower Energy Storage: Case of Gran Canaria Island," Energies, MDPI, vol. 14(12), pages 1-27, June.
    11. Cozzolino, R. & Tribioli, L. & Bella, G., 2016. "Power management of a hybrid renewable system for artificial islands: A case study," Energy, Elsevier, vol. 106(C), pages 774-789.
    12. Wadim Strielkowski & Lubomír Civín & Elena Tarkhanova & Manuela Tvaronavičienė & Yelena Petrenko, 2021. "Renewable Energy in the Sustainable Development of Electrical Power Sector: A Review," Energies, MDPI, vol. 14(24), pages 1-24, December.
    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. Jakub Jurasz & Jerzy Mikulik & Paweł B. Dąbek & Mohammed Guezgouz & Bartosz Kaźmierczak, 2021. "Complementarity and ‘Resource Droughts’ of Solar and Wind Energy in Poland: An ERA5-Based Analysis," Energies, MDPI, vol. 14(4), pages 1-24, February.
    15. Katsaprakakis, Dimitris Al. & Dakanali, Irini & Condaxakis, Constantinos & Christakis, Dimitris G., 2019. "Comparing electricity storage technologies for small insular grids," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    16. Mohamed A. M. Shaheen & Hany M. Hasanien & Said F. Mekhamer & Mohammed H. Qais & Saad Alghuwainem & Zia Ullah & Marcos Tostado-Véliz & Rania A. Turky & Francisco Jurado & Mohamed R. Elkadeem, 2022. "Probabilistic Optimal Power Flow Solution Using a Novel Hybrid Metaheuristic and Machine Learning Algorithm," Mathematics, MDPI, vol. 10(17), pages 1-23, August.
    17. Mohamed S. Hashish & Hany M. Hasanien & Haoran Ji & Abdulaziz Alkuhayli & Mohammed Alharbi & Tlenshiyeva Akmaral & Rania A. Turky & Francisco Jurado & Ahmed O. Badr, 2023. "Monte Carlo Simulation and a Clustering Technique for Solving the Probabilistic Optimal Power Flow Problem for Hybrid Renewable Energy Systems," Sustainability, MDPI, vol. 15(1), pages 1-25, January.
    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. Shayan, Mostafa Esmaeili & Najafi, Gholamhassan & Ghobadian, Barat & Gorjian, Shiva & Mamat, Rizalman & Ghazali, Mohd Fairusham, 2022. "Multi-microgrid optimization and energy management under boost voltage converter with Markov prediction chain and dynamic decision algorithm," Renewable Energy, Elsevier, vol. 201(P2), pages 179-189.
    20. Jianzhong Zhou & Yanhe Xu & Yang Zheng & Yuncheng Zhang, 2017. "Optimization of Guide Vane Closing Schemes of Pumped Storage Hydro Unit Using an Enhanced Multi-Objective Gravitational Search Algorithm," Energies, MDPI, vol. 10(7), pages 1-23, July.

    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:17:y:2024:i:4:p:772-:d:1334270. 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.