Research on Multi-level Cooperative Detection of Power Grid Dispatching Fault Based on Artificial Intelligence Technology

Authors

  • Jianzhong Dou Central China Branch Of State Grid Corporation Of China, Hubei Wuhan 430077, China
  • Zhicheng Liu Wuhan Fenghuo Putian Information Technology Co.,Ltd, Hubei Wuhan 430074, China
  • Wei Xiong Xiong Central China Branch Of State Grid Corporation Of China, Hubei Wuhan 430077, China
  • Zhongzhong Chen Central China Branch Of State Grid Corporation Of China, Hubei Wuhan 430077, China
  • Yifei Wu Wuhan Fenghuo Putian Information Technology Co.,Ltd, Hubei Wuhan 430074, China
  • Tao Sun Wuhan Fenghuo Putian Information Technology Co.,Ltd, Hubei Wuhan 430074, China

Keywords:

Artificial intelligence, power grid dispatch, scheduling fault, multilevel collaborative detection, neural network.

Abstract

The traditional power grid dispatching fault detection method has low detec-
tion efficiency and accuracy due to the lack of uncertainty in modeling.
Aiming at the above problems, a multi-level cooperative fault detection
method based on artificial intelligence technology is studied. After the pre-
liminary processing of the dispatching data, the multilevel fault detection
architecture is established. BP neural network is used to realize the multi-
level cooperative detection of scheduling faults in the multi-level detection
architecture. Through simulation experiment, it is proved that the failure rate
and false detection rate of the proposed method are far lower than those of
traditional methods, and the method has high stability and advantages.

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Author Biographies

Jianzhong Dou, Central China Branch Of State Grid Corporation Of China, Hubei Wuhan 430077, China

Jianzhong Dou (1988.10.06–), male, Han nationality, Qingyang, Gansu
Province, Central China Power Dispatching and Control center, master’s
degree, mainly engaged in big power grid operation and control technology,
artificial intelligence application research in the field of power grid dispatch-
ing an control.

Zhicheng Liu, Wuhan Fenghuo Putian Information Technology Co.,Ltd, Hubei Wuhan 430074, China

Zhicheng Liu (1981.09.08–), male, Han nationality, Wanan, Jiangxi
Province, Central China Power Dispatching and Control center, master’s
degree, mainly engaged in big power grid operation and control technology,
artificial intelligence application research in the field of power grid dispatch-
ing an control.

Wei Xiong Xiong, Central China Branch Of State Grid Corporation Of China, Hubei Wuhan 430077, China

Wei Xiong (1986.04.02–), male, Han nationality, Xishui, Hubei Province,
Central China Power Dispatching and Control center, master’s degree, mainly
engaged in big power grid operation and control technology, artificial intelli-
gence application research in the field of power grid dispatching an control.

Zhongzhong Chen, Central China Branch Of State Grid Corporation Of China, Hubei Wuhan 430077, China

Zhongzhong Chen (1992.02.19–), male, Han nationality, Anqing, Anhui
Province, Central China Power Dispatching and Control center, master’s
degree, mainly engaged in big power grid operation and control technology,
artificial intelligence application research in the field of power grid dispatch-
ing an control

Yifei Wu, Wuhan Fenghuo Putian Information Technology Co.,Ltd, Hubei Wuhan 430074, China

Yifei Wu (1991.02.22–), Female, Han nationality, Wuhan Hubei, Wuhan
Fenghuo Putian Information Technology Co., Ltd, mainly engaged in
machine learning and natural language understanding research.

Tao Sun, Wuhan Fenghuo Putian Information Technology Co.,Ltd, Hubei Wuhan 430074, China

Tao Sun (1984–), Male, Han nationality, Weifang Shandong, Wuhan
Fenghuo Putian Information Technology Co., Ltd, master’s degree, mainly
engaged in audio speech recognition and natural language processing
research.

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Published

2021-04-28

How to Cite

Dou, J. ., Liu, Z., Xiong, W. X., Chen, Z. ., Wu, Y. ., & Sun, T. . (2021). Research on Multi-level Cooperative Detection of Power Grid Dispatching Fault Based on Artificial Intelligence Technology. Distributed Generation &Amp; Alternative Energy Journal, 35(4), 331–344. Retrieved from https://journals.riverpublishers.com/index.php/DGAEJ/article/view/13629

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