IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v16y2024i3p1093-d1327680.html
   My bibliography  Save this article

Two-Stage Stochastic Scheduling of Cascaded Hydropower–Wind–Photovoltaic Hybrid Systems Considering Contract Decomposition and Spot Market

Author

Listed:
  • Yang Li

    (College of Energy and Electrical Engineering, Hohai University, Nanjing 211100, China)

  • Ni Fang

    (College of Energy and Electrical Engineering, Hohai University, Nanjing 211100, China)

  • Shengming He

    (Yalong River Hydropower Development Company Ltd., Chengdu 610051, China)

  • Feng Wu

    (College of Energy and Electrical Engineering, Hohai University, Nanjing 211100, China)

  • Outing Li

    (College of Energy and Electrical Engineering, Hohai University, Nanjing 211100, China)

  • Linjun Shi

    (College of Energy and Electrical Engineering, Hohai University, Nanjing 211100, China)

  • Renshan Ding

    (Yalong River Hydropower Development Company Ltd., Chengdu 610051, China)

Abstract

With the advancement of China’s electricity markets and the continuous development of renewable energy sources (RESs), it is of great importance to investigate the strategic behavior of RESs in electricity markets. In this paper, a two-stage stochastic optimization model is proposed for a hybrid energy system composed of cascade hydropower plants, wind farms, and photovoltaic stations. Firstly, typical scenarios are generated based on Latin hypercube sampling (LHS) and the K-means clustering algorithm to represent uncertainties of wind–photovoltaic power outputs. Then, with an analysis of China’s electricity market structure, a two-stage coordinated scheduling model of hydropower–wind–photovoltaic hybrid systems in electricity markets is established with the objective of maximizing total revenues considering bilateral contract decomposition, the day-ahead energy market, and the real-time balance market. In addition, the proposed model is transformed into a mixed-integer linear programming (MILP) problem for computational convenience. As shown in an analysis of case studies, cascade hydropower plants can compensate for the fluctuation in wind and photovoltaic power outputs to reduce financial risks caused by uncertainties of wind and photovoltaic power generation. Simulation results show that compared with uncoordinated operation, the coordinated operation of hydropower–wind–photovoltaic hybrid systems increases total revenue by 1.08% and reduces the imbalance penalty by 29.85%.

Suggested Citation

  • Yang Li & Ni Fang & Shengming He & Feng Wu & Outing Li & Linjun Shi & Renshan Ding, 2024. "Two-Stage Stochastic Scheduling of Cascaded Hydropower–Wind–Photovoltaic Hybrid Systems Considering Contract Decomposition and Spot Market," Sustainability, MDPI, vol. 16(3), pages 1-19, January.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:3:p:1093-:d:1327680
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/16/3/1093/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/16/3/1093/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. Hans Ole Riddervold & Ellen Krohn Aasg{aa}rd & Lisa Haukaas & Magnus Korp{aa}s, 2021. "Internal hydro- and wind portfolio optimisation in real-time market operations," Papers 2102.10098, arXiv.org.
    3. Zhang, Yuquan & Zang, Wei & Zheng, Jinhai & Cappietti, Lorenzo & Zhang, Jisheng & Zheng, Yuan & Fernandez-Rodriguez, E., 2021. "The influence of waves propagating with the current on the wake of a tidal stream turbine," Applied Energy, Elsevier, vol. 290(C).
    4. Zhang, Hongxuan & Lu, Zongxiang & Hu, Wei & Wang, Yiting & Dong, Ling & Zhang, Jietan, 2019. "Coordinated optimal operation of hydro–wind–solar integrated systems," Applied Energy, Elsevier, vol. 242(C), pages 883-896.
    5. Wang, Xuebin & Chang, Jianxia & Meng, Xuejiao & Wang, Yimin, 2018. "Short-term hydro-thermal-wind-photovoltaic complementary operation of interconnected power systems," Applied Energy, Elsevier, vol. 229(C), pages 945-962.
    6. Li, Fang-Fang & Qiu, Jun, 2016. "Multi-objective optimization for integrated hydro–photovoltaic power system," Applied Energy, Elsevier, vol. 167(C), pages 377-384.
    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. Yang Li & Feng Wu & Xudong Song & Linjun Shi & Keman Lin & Feilong Hong, 2023. "Data-Driven Chance-Constrained Schedule Optimization of Cascaded Hydropower and Photovoltaic Complementary Generation Systems for Shaving Peak Loads," Sustainability, MDPI, vol. 15(24), pages 1-20, December.
    2. Guo, Yi & Ming, Bo & Huang, Qiang & Wang, Yimin & Zheng, Xudong & Zhang, Wei, 2022. "Risk-averse day-ahead generation scheduling of hydro–wind–photovoltaic complementary systems considering the steady requirement of power delivery," Applied Energy, Elsevier, vol. 309(C).
    3. Liu, Hailiang & Brown, Tom & Andresen, Gorm Bruun & Schlachtberger, David P. & Greiner, Martin, 2019. "The role of hydro power, storage and transmission in the decarbonization of the Chinese power system," Applied Energy, Elsevier, vol. 239(C), pages 1308-1321.
    4. 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).
    5. 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).
    6. Mahfoud, Rabea Jamil & Alkayem, Nizar Faisal & Zhang, Yuquan & Zheng, Yuan & Sun, Yonghui & Alhelou, Hassan Haes, 2023. "Optimal operation of pumped hydro storage-based energy systems: A compendium of current challenges and future perspectives," Renewable and Sustainable Energy Reviews, Elsevier, vol. 178(C).
    7. Jin, Xiaoyu & Liu, Benxi & Liao, Shengli & Cheng, Chuntian & Yan, Zhiyu, 2022. "A Wasserstein metric-based distributionally robust optimization approach for reliable-economic equilibrium operation of hydro-wind-solar energy systems," Renewable Energy, Elsevier, vol. 196(C), pages 204-219.
    8. Wang, Fengjuan & Xie, Yachen & Xu, Jiuping, 2019. "Reliable-economical equilibrium based short-term scheduling towards hybrid hydro-photovoltaic generation systems: Case study from China," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    9. Zhang, Juntao & Cheng, Chuntian & Yu, Shen & Wu, Huijun & Gao, Mengping, 2021. "Sharing hydropower flexibility in interconnected power systems: A case study for the China Southern power grid," Applied Energy, Elsevier, vol. 288(C).
    10. Nasir, Jehanzeb & Javed, Adeel & Ali, Majid & Ullah, Kafait & Kazmi, Syed Ali Abbas, 2022. "Capacity optimization of pumped storage hydropower and its impact on an integrated conventional hydropower plant operation," Applied Energy, Elsevier, vol. 323(C).
    11. Ming, Bo & Liu, Pan & Guo, Shenglian & Cheng, Lei & Zhang, Jingwen, 2019. "Hydropower reservoir reoperation to adapt to large-scale photovoltaic power generation," Energy, Elsevier, vol. 179(C), pages 268-279.
    12. Xu, Jiuping & Liu, Liying & Wang, Fengjuan, 2022. "Equilibrium strategy-based economic-reliable approach for day-ahead scheduling towards solar-wind-gas hybrid power generation system: A case study from China," Energy, Elsevier, vol. 240(C).
    13. Feng, Zhong-kai & Huang, Qing-qing & Niu, Wen-jing & Su, Hua-ying & Li, Shu-shan & Wu, Hui-jun & Wang, Jia-yang, 2024. "Peak operation optimization of cascade hydropower reservoirs and solar power plants considering output forecasting uncertainty," Applied Energy, Elsevier, vol. 358(C).
    14. Wang, Zhenni & Wen, Xin & Tan, Qiaofeng & Fang, Guohua & Lei, Xiaohui & Wang, Hao & Yan, Jinyue, 2021. "Potential assessment of large-scale hydro-photovoltaic-wind hybrid systems on a global scale," Renewable and Sustainable Energy Reviews, Elsevier, vol. 146(C).
    15. Xu, Bin & Zhu, Feilin & Zhong, Ping-an & Chen, Juan & Liu, Weifeng & Ma, Yufei & Guo, Le & Deng, Xiaoliang, 2019. "Identifying long-term effects of using hydropower to complement wind power uncertainty through stochastic programming," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    16. Fu, Yiwei & Lu, Zongxiang & Hu, Wei & Wu, Shuang & Wang, Yiting & Dong, Ling & Zhang, Jietan, 2019. "Research on joint optimal dispatching method for hybrid power system considering system security," Applied Energy, Elsevier, vol. 238(C), pages 147-163.
    17. Feng, Zhong-kai & Niu, Wen-jing & Wang, Wen-chuan & Zhou, Jian-zhong & Cheng, Chun-tian, 2019. "A mixed integer linear programming model for unit commitment of thermal plants with peak shaving operation aspect in regional power grid lack of flexible hydropower energy," Energy, Elsevier, vol. 175(C), pages 618-629.
    18. Liu, Benxi & Liu, Tengyuan & Liao, Shengli & Lu, Jia & Cheng, Chuntian, 2023. "Short-term coordinated hybrid hydro-wind-solar optimal scheduling model considering multistage section restrictions," Renewable Energy, Elsevier, vol. 217(C).
    19. Zhang, Zhi & Zhang, Yuquan & Zheng, Yuan & Zhang, Jisheng & Fernandez-Rodriguez, Emmanuel & Zang, Wei & Ji, Renwei, 2023. "Power fluctuation and wake characteristics of tidal stream turbine subjected to wave and current interaction," Energy, Elsevier, vol. 264(C).
    20. Shabani, Masoume & Mahmoudimehr, Javad, 2019. "Influence of climatological data records on design of a standalone hybrid PV-hydroelectric power system," Renewable Energy, Elsevier, vol. 141(C), pages 181-194.

    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:jsusta:v:16:y:2024:i:3:p:1093-:d:1327680. 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.