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Sharing hydropower flexibility in interconnected power systems: A case study for the China Southern power grid

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  • Zhang, Juntao
  • Cheng, Chuntian
  • Yu, Shen
  • Wu, Huijun
  • Gao, Mengping

Abstract

In 2020, China pledged to become carbon neutral before 2060, which implies the acceleration of China’s low-carbon energy transition and development of new energy (wind and solar). As a result, the demand for flexibility in China’s power system has never been so urgent. Because China has the greatest installed hydropower capacity in the world, sharing hydropower flexibility in its interconnected power systems is of great practical significance to China. This paper reports the necessity and feasibility of sharing the hydropower flexibility of Yunnan’s large hydropower bases in the China Southern Power Grid (CSG) through direct-current (DC) tie-lines. In addition, an effective solution to this problem is presented. First, several quantitative methods of flexibility are proposed. Second, a decentralized and coordinated scheduling model that taps and shares the power flexibility of large hydropower bases in interconnected power systems is constructed. The model considers the complex nonlinear constraints of hydropower and DC tie-lines. Third, new linearization modeling methods are proposed to transform the model to a mixed integer linear programming (MILP) model, reducing the computational complexity. The MILP model is applied to the CSG to determine the hourly generation schedules for power plants in Yunnan’s large hydropower bases and the power transmission plans for DC tie-lines. The cases studies demonstrate that the proposed model can fully tap hydropower flexibility and ensure that large hydropower bases simultaneously respond to the flexibility demands of sending-end and receiving-end power grids. The study provides a valuable technical approach for alleviating the lack of power flexibility in other countries with large hydropower bases.

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  • 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).
    • Handle: RePEc:eee:appene:v:288:y:2021:i:c:s0306261921001781
    DOI: 10.1016/j.apenergy.2021.116645
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    as
    1. He, Feifei & Zhou, Jianzhong & Mo, Li & Feng, Kuaile & Liu, Guangbiao & He, Zhongzheng, 2020. "Day-ahead short-term load probability density forecasting method with a decomposition-based quantile regression forest," Applied Energy, Elsevier, vol. 262(C).
    2. English, Jeffrey & Niet, Taco & Lyseng, Benjamin & Keller, Victor & Palmer-Wilson, Kevin & Robertson, Bryson & Wild, Peter & Rowe, Andrew, 2020. "Flexibility requirements and electricity system planning: Assessing inter-regional coordination with large penetrations of variable renewable supplies," Renewable Energy, Elsevier, vol. 145(C), pages 2770-2782.
    3. Xie, Min & Ji, Xiang & Hu, Xintong & Cheng, Peijun & Du, Yuxin & Liu, Mingbo, 2018. "Autonomous optimized economic dispatch of active distribution system with multi-microgrids," Energy, Elsevier, vol. 153(C), pages 479-489.
    4. Yang, Yandong & Li, Shufang & Li, Wenqi & Qu, Meijun, 2018. "Power load probability density forecasting using Gaussian process quantile regression," Applied Energy, Elsevier, vol. 213(C), pages 499-509.
    5. Uddin, Moslem & Romlie, Mohd Fakhizan & Abdullah, Mohd Faris & Abd Halim, Syahirah & Abu Bakar, Ab Halim & Chia Kwang, Tan, 2018. "A review on peak load shaving strategies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 3323-3332.
    6. Liu, Laibao & Wang, Zheng & Wang, Yang & Wang, Jun & Chang, Rui & He, Gang & Tang, Wenjun & Gao, Ziqi & Li, Jiangtao & Liu, Changyi & Zhao, Lin & Qin, Dahe & Li, Shuangcheng, 2020. "Optimizing wind/solar combinations at finer scales to mitigate renewable energy variability in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 132(C).
    7. Gebretsadik, Yohannes & Fant, Charles & Strzepek, Kenneth & Arndt, Channing, 2016. "Optimized reservoir operation model of regional wind and hydro power integration case study: Zambezi basin and South Africa," Applied Energy, Elsevier, vol. 161(C), pages 574-582.
    8. Qiu, Haifeng & You, Fengqi, 2020. "Decentralized-distributed robust electric power scheduling for multi-microgrid systems," Applied Energy, Elsevier, vol. 269(C).
    9. Feng, Zhong-kai & Niu, Wen-jing & Cheng, Chun-tian & Zhou, Jian-zhong, 2017. "Peak shaving operation of hydro-thermal-nuclear plants serving multiple power grids by linear programming," Energy, Elsevier, vol. 135(C), pages 210-219.
    10. Segurado, R. & Madeira, J.F.A. & Costa, M. & Duić, N. & Carvalho, M.G., 2016. "Optimization of a wind powered desalination and pumped hydro storage system," Applied Energy, Elsevier, vol. 177(C), pages 487-499.
    11. Askeland, Kristine & Bozhkova, Kristina N. & Sorknæs, Peter, 2019. "Balancing Europe: Can district heating affect the flexibility potential of Norwegian hydropower resources?," Renewable Energy, Elsevier, vol. 141(C), pages 646-656.
    12. 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.
    13. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
    14. Shen, Jianjian & Cheng, Chuntian & Cheng, Xiong & Lund, Jay R., 2016. "Coordinated operations of large-scale UHVDC hydropower and conventional hydro energies about regional power grid," Energy, Elsevier, vol. 95(C), pages 433-446.
    15. Ji, Qiang & Zhang, Dayong, 2019. "How much does financial development contribute to renewable energy growth and upgrading of energy structure in China?," Energy Policy, Elsevier, vol. 128(C), pages 114-124.
    16. Zhu, Yongnan & Ke, Jing & Wang, Jianhua & Liu, He & Jiang, Shan & Blum, Helcio & Zhao, Yong & He, Guohua & Meng, Yuan & Su, Jian, 2020. "Water transfer and losses embodied in the West–East electricity transmission project in China," Applied Energy, Elsevier, vol. 275(C).
    17. Shen, Jianjian & Cheng, Chuntian & Wu, Xinyu & Cheng, Xiong & Li, Weidong & Lu, Jianyu, 2014. "Optimization of peak loads among multiple provincial power grids under a central dispatching authority," Energy, Elsevier, vol. 74(C), pages 494-505.
    18. 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.
    19. Cheng, Chuntian & Su, Chengguo & Wang, Peilin & Shen, Jianjian & Lu, Jianyu & Wu, Xinyu, 2018. "An MILP-based model for short-term peak shaving operation of pumped-storage hydropower plants serving multiple power grids," Energy, Elsevier, vol. 163(C), pages 722-733.
    20. 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.
    21. Juan M. Morales & Antonio J. Conejo & Henrik Madsen & Pierre Pinson & Marco Zugno, 2014. "Integrating Renewables in Electricity Markets," International Series in Operations Research and Management Science, Springer, edition 127, number 978-1-4614-9411-9, September.
    22. Lund, Peter D. & Lindgren, Juuso & Mikkola, Jani & Salpakari, Jyri, 2015. "Review of energy system flexibility measures to enable high levels of variable renewable electricity," Renewable and Sustainable Energy Reviews, Elsevier, vol. 45(C), pages 785-807.
    23. 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.
    24. Alassi, Abdulrahman & Bañales, Santiago & Ellabban, Omar & Adam, Grain & MacIver, Callum, 2019. "HVDC Transmission: Technology Review, Market Trends and Future Outlook," Renewable and Sustainable Energy Reviews, Elsevier, vol. 112(C), pages 530-554.
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