IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v17y2024i11p2515-d1400294.html
   My bibliography  Save this article

A Long-Term Power Supply Risk Evaluation Method for China Regional Power System Based on Probabilistic Production Simulation

Author

Listed:
  • Jianzu Hu

    (China Renewable Energy Engineering Institute, Power Construction Corporation of China, Beijing 100048, China)

  • Yuefeng Wang

    (China Renewable Energy Engineering Institute, Power Construction Corporation of China, Beijing 100048, China)

  • Fan Cheng

    (Center for Strategic Studies, Chinese Academy of Engineering, Beijing 100088, China
    Department of Electrical Engineering, Tsinghua University, Beijing 100084, China)

  • Hanqing Shi

    (Center for Strategic Studies, Chinese Academy of Engineering, Beijing 100088, China)

Abstract

To qualify the risk of extreme weather events for power supply security during the long-term power system transformation process, this paper proposes a risk probability evaluation method based on probabilistic production simulation. Firstly, the internal relationship of extreme weather intensity and duration is depicted using the copula function, and the influences of extreme weather on power security are described using the guaranteed power output ability coefficient, which can provide the extreme scenario basis for probabilistic production simulation. Then, a probabilistic production simulation method is proposed, which includes a typical-year scenario and extreme weather events. Meanwhile, an index system is proposed to qualify the power security level, which applies the loss of load expectation (LOLE) and time of loss of load expectation (TOLE) under different scenarios and other indices to reveal the long-term power security trend. Finally, the long-term power supply risks for the Yunnan provincial power system are analyzed using the proposed method, validating that the proposed method is capable of characterizing the influences of extreme weather on power security. The security level of different long-term power transformation schemes is evaluated.

Suggested Citation

  • Jianzu Hu & Yuefeng Wang & Fan Cheng & Hanqing Shi, 2024. "A Long-Term Power Supply Risk Evaluation Method for China Regional Power System Based on Probabilistic Production Simulation," Energies, MDPI, vol. 17(11), pages 1-23, May.
  • Handle: RePEc:gam:jeners:v:17:y:2024:i:11:p:2515-:d:1400294
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/17/11/2515/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/17/11/2515/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Yang, Yesen & Li, Zhengmao & Mandapaka, Pradeep V. & Lo, Edmond Y.M., 2023. "Risk-averse restoration of coupled power and water systems with small pumped-hydro storage and stochastic rooftop renewables," Applied Energy, Elsevier, vol. 339(C).
    2. Zhenyu Zhuo & Ershun Du & Ning Zhang & Chris P. Nielsen & Xi Lu & Jinyu Xiao & Jiawei Wu & Chongqing Kang, 2022. "Cost increase in the electricity supply to achieve carbon neutrality in China," Nature Communications, Nature, vol. 13(1), pages 1-13, December.
    3. Stover, Oliver & Karve, Pranav & Mahadevan, Sankaran, 2023. "Reliability and risk metrics to assess operational adequacy and flexibility of power grids," Reliability Engineering and System Safety, Elsevier, vol. 231(C).
    4. Wu, Xinyu & Wu, Yiyang & Cheng, Xilong & Cheng, Chuntian & Li, Zehong & Wu, Yongqi, 2023. "A mixed-integer linear programming model for hydro unit commitment considering operation constraint priorities," Renewable Energy, Elsevier, vol. 204(C), pages 507-520.
    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. Wang, Yadong & Wang, Delu & Shi, Xunpeng, 2023. "Sustainable development pathways of China's wind power industry under uncertainties: Perspective from economic benefits and technical potential," Energy Policy, Elsevier, vol. 182(C).
    2. Jing-Li Fan & Zezheng Li & Xi Huang & Kai Li & Xian Zhang & Xi Lu & Jianzhong Wu & Klaus Hubacek & Bo Shen, 2023. "A net-zero emissions strategy for China’s power sector using carbon-capture utilization and storage," Nature Communications, Nature, vol. 14(1), pages 1-16, December.
    3. Jiang, Hou & Yao, Ling & Lu, Ning & Qin, Jun & Zhang, Xiaotong & Liu, Tang & Zhang, Xingxing & Zhou, Chenghu, 2024. "Exploring the optimization of rooftop photovoltaic scale and spatial layout under curtailment constraints," Energy, Elsevier, vol. 293(C).
    4. Zengkai Zhang & Jiaoyan Li & Dabo Guan, 2023. "Value chain carbon footprints of Chinese listed companies," Nature Communications, Nature, vol. 14(1), pages 1-9, December.
    5. Tianyu Lu & Hongyu Li, 2024. "Can China’s Regional Industrial Chain Innovation and Reform Policy Make the Impossible Triangle of Energy Attainable? A Causal Inference Study on the Effect of Improving Industrial Chain Resilience," Energies, MDPI, vol. 17(10), pages 1-33, May.
    6. Li, Zepeng & Wu, Qiuwei & Li, Hui & Nie, Chengkai & Tan, Jin, 2024. "Distributed low-carbon economic dispatch of integrated power and transportation system," Applied Energy, Elsevier, vol. 353(PA).
    7. Bo, Yimin & Bao, Minglei & Ding, Yi & Hu, Yishuang, 2024. "A DNN-based reliability evaluation method for multi-state series-parallel systems considering semi-Markov process," Reliability Engineering and System Safety, Elsevier, vol. 242(C).
    8. Pan, Xunzhang & Ma, Xueqing & Zhang, Yanru & Shao, Tianming & Peng, Tianduo & Li, Xiang & Wang, Lining & Chen, Wenying, 2023. "Implications of carbon neutrality for power sector investments and stranded coal assets in China," Energy Economics, Elsevier, vol. 121(C).
    9. Zhang, Hongji & Ding, Tao & Sun, Yuge & Huang, Yuhan & He, Yuankang & Huang, Can & Li, Fangxing & Xue, Chen & Sun, Xiaoqiang, 2023. "How does load-side re-electrification help carbon neutrality in energy systems: Cost competitiveness analysis and life-cycle deduction," Renewable and Sustainable Energy Reviews, Elsevier, vol. 187(C).
    10. Guo, Zhi & Mao, Xianqiang & Lu, Jianhong & Gao, Yubing & Chen, Xing & Zhang, Shining & Ma, Zhiyuan, 2024. "Can a new power system create more employment in China?," Energy, Elsevier, vol. 295(C).
    11. Peng, Tianduo & Ren, Lei & Ou, Xunmin, 2023. "Development and application of life-cycle energy consumption and carbon footprint analysis model for passenger vehicles in China," Energy, Elsevier, vol. 282(C).
    12. He, Zhenglei & Liu, Chang & Wang, Yutao & Wang, Xu & Man, Yi, 2023. "Optimal operation of wind-solar-thermal collaborative power system considering carbon trading and energy storage," Applied Energy, Elsevier, vol. 352(C).
    13. Yang, Mao & Han, Chao & Zhang, Wei & Wang, Bo, 2024. "A short-term power prediction method for wind farm cluster based on the fusion of multi-source spatiotemporal feature information," Energy, Elsevier, vol. 294(C).
    14. Karol Sidor & Piotr Miller & Robert Małkowski & Michał Izdebski, 2024. "Optimization of Division and Reconfiguration Locations of the Medium-Voltage Power Grid Based on Forecasting the Level of Load and Generation from Renewable Energy Sources," Energies, MDPI, vol. 17(19), pages 1-21, October.
    15. Onodera, Hiroaki & Delage, Rémi & Nakata, Toshihiko, 2024. "The role of regional renewable energy integration in electricity decarbonization—A case study of Japan," Applied Energy, Elsevier, vol. 363(C).
    16. Xizhe Yan & Dan Tong & Yixuan Zheng & Yang Liu & Shaoqing Chen & Xinying Qin & Chuchu Chen & Ruochong Xu & Jing Cheng & Qinren Shi & Dongsheng Zheng & Kebin He & Qiang Zhang & Yu Lei, 2024. "Cost-effectiveness uncertainty may bias the decision of coal power transitions in China," Nature Communications, Nature, vol. 15(1), pages 1-12, December.
    17. Jiang, Haiyang & Du, Ershun & He, Boyu & Zhang, Ning & Wang, Peng & Li, Fuqiang & Ji, Jie, 2023. "Analysis and modeling of seasonal characteristics of renewable energy generation," Renewable Energy, Elsevier, vol. 219(P1).
    18. Jain, Tanmay & Verma, Kusum, 2024. "Reliability based computational model for stochastic unit commitment of a bulk power system integrated with volatile wind power," Reliability Engineering and System Safety, Elsevier, vol. 244(C).
    19. Zhou, Siyu & Han, Yang & Zalhaf, Amr S. & Lehtonen, Matti & Darwish, Mohamed M.F. & Mahmoud, Karar, 2024. "Risk-averse bi-level planning model for maximizing renewable energy hosting capacity via empowering seasonal hydrogen storage," Applied Energy, Elsevier, vol. 361(C).
    20. Stover, Oliver & Nath, Paromita & Karve, Pranav & Mahadevan, Sankaran & Baroud, Hiba, 2024. "Dependence structure learning and joint probabilistic forecasting of stochastic power grid variables," Applied Energy, Elsevier, vol. 357(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:17:y:2024:i:11:p:2515-:d:1400294. 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.