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Research on New Electric Power System Risk Assessment Based on Cloud Model

Author

Listed:
  • Mingrun Tang

    (School of Economics and Management, North China Electric Power University, Beijing 102206, China)

  • Ruoyang Li

    (State Grid Beijing Electric Power Company, Beijing 100054, China)

  • Rujia Zhang

    (School of Economics and Management, North China Electric Power University, Beijing 102206, China)

  • Shuxia Yang

    (School of Economics and Management, North China Electric Power University, Beijing 102206, China)

Abstract

A large number of new energy power electronic equipment is connected to the new power system, and the high proportion of new energy brings huge volatility and randomness, so it is necessary to establish a systematic risk assessment system to adapt to the new power system. This paper has improved the neglect of environmental benefits and supply and demand balance in the existing indicator system and established an indicator system for the risk of the new power system from the five perspectives of safety, supply and demand, sufficiency, cleanliness, and flexibility through the analysis of the evaluation indicator system of the large power grid and the influencing factors of the new power system. The index weight of a new power system is established by means of the entropy weight–critic combination weighting method, and the comprehensive evaluation is carried out by combining it with the cloud model. Finally, the specific data of the new power system in Fujian Province from 2020 to 2022 are taken as an example to verify the feasibility of combining the combined weighting method and the cloud model, and it is concluded that the new power system in Fujian Province has been in a “low risk” operation state for the recent three years.

Suggested Citation

  • Mingrun Tang & Ruoyang Li & Rujia Zhang & Shuxia Yang, 2024. "Research on New Electric Power System Risk Assessment Based on Cloud Model," Sustainability, MDPI, vol. 16(5), pages 1-19, February.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:5:p:2014-:d:1348577
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