基于流行病模型的电力系统级联故障检测方法

IF 6.9 2区 工程技术 Q2 ENERGY & FUELS
Jian Xu;Zhonghao He;Siyang Liao;Yuanzhang Sun;Liangzhong Yao;Deping Ke;Jun Yang
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引用次数: 0

摘要

在可再生能源渗透率较高的情况下,早期发现级联故障对电力系统的安全稳定运行具有重要作用。本文提出了一种基于流行病模型的故障传播动态模型,并进一步提出了一种检测级联故障发展的方法。通过对 IEEE 39 总线和 118 总线系统的仿真,证明该模型是有效的,能够为可再生能源高渗透率电力系统中级联故障的预防提供实用的技术支持。本文还提供了在级联故障各阶段选择不同保护和控制措施的分析方法,具有关键意义和后续价值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Detection Method for Cascading Failure of Power Systems Based on Epidemic Model
The early detection of cascading failure plays an important role in the safe and stable operation of the power system with high penetration of renewable energy. This paper proposes a fault propagation dynamic model based on the epidemic model, and further puts forward a method to detect the development of cascading failures. Through the simulation of the IEEE 39-bus and 118-bus systems, this model is proven to be valid and capable of providing practical technical support for the prevention of cascading failures in power systems with high penetration of renewable energy. This paper also provides an analysis method for the choice of different protection and control measures at each stage of cascading failure, which has critical significance and follow-up value.
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来源期刊
CiteScore
11.80
自引率
12.70%
发文量
389
审稿时长
26 weeks
期刊介绍: The CSEE Journal of Power and Energy Systems (JPES) is an international bimonthly journal published by the Chinese Society for Electrical Engineering (CSEE) in collaboration with CEPRI (China Electric Power Research Institute) and IEEE (The Institute of Electrical and Electronics Engineers) Inc. Indexed by SCI, Scopus, INSPEC, CSAD (Chinese Science Abstracts Database), DOAJ, and ProQuest, it serves as a platform for reporting cutting-edge theories, methods, technologies, and applications shaping the development of power systems in energy transition. The journal offers authors an international platform to enhance the reach and impact of their contributions.
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