Electric Power ›› 2022, Vol. 55 ›› Issue (3): 133-141.DOI: 10.11930/j.issn.1004-9649.202009003

• Transmission Line Emergency Response • Previous Articles     Next Articles

Calculation of Transmission Line Trip Probabilities under Forest Fire Condition

LIU Hui1, YANG Tao1, LIN Jikeng2, WANG Jingjing1, YAN Bo1, LIU Xiao3   

  1. 1. State Grid Anhui Electric Power Co., Ltd., Hefei 230022, China;
    2. College of Electronics and Information Engineering, Tongji University, Shanghai 200092, China;
    3. Anhui Jiyuan Software Co., Ltd., Hefei 230031, China
  • Received:2020-09-03 Revised:2021-07-28 Online:2022-03-28 Published:2022-03-29
  • Supported by:
    This work is supported by National Natural Science Foundation of China (Model and Optimization of Smart Grid Power Island Based on Graph Theory, No. 51177107) and Science & Technology Project of State Grid Anhui Electric Power Co., Ltd.(Research on Integrated Early Warning Technology of Power Grid Operation Risk Based on Meteorological Disaster Cloud Technology, No.52120018004Q)

Abstract: In recent years, line tripping incidents caused by forest fires occur frequently. How to accurately predict the line trip probability caused by forest fire has become one of the urgent issues that have attracted much attention. A new method for calculating transmission line trip probabilities is thus proposed in this paper using improved cellular automata forest fire spread model. Firstly some factors are introduced such as flame temperature, vegetation type, fire distance and precipitation, and the integrated impact of these factors on the line tripping is analyzed; then the improved cellular automata is used to predict the spread process of forest fires, and the accurate probability variation of line tripping caused by forest fire is thus obtained according to the spread situation. The effectiveness of the proposed method has been proved through case study, and it can provide a guide for the safe operation of power grid.

Key words: forest fire condition, transmission line trip probability, improved cellular automata, integrated influence, safety early-warning