A flame combustion model-based wildfire-induced tripping risk assessment approach of transmission lines

被引:0
|
作者
Zhou, Enze [1 ]
Wang, Lei [1 ]
Wei, Ruizeng [1 ]
Liu, Shuqing [1 ]
Zhou, You [2 ]
机构
[1] Elect Power Res Inst Guangdong Power Grid Co Ltd, Key Lab Power Equipment Reliabil Enterprise, Guangzhou, Guangdong, Peoples R China
[2] Changsha Univ Sci & Technol, Sch Elect & Informat Engn, Changsha, Hunan, Peoples R China
基金
中国国家自然科学基金;
关键词
wildfire occurrence probability; flame height; insulation breakdown risk; risk level; risk distribution; LEADER INCEPTION; FIRE; SPREAD;
D O I
10.3389/fenrg.2024.1330782
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
With the intensification of global climate change, the frequency of wildfires has markedly increased, presenting an urgent challenge in assessing tripping failures for power systems. This paper proposes an innovative method to evaluate the spatial wildfire-induced tripping risk of transmission lines based on a flame combustion model. Firstly, Bayes theory is employed to assess the spatial probability of wildfire occurrence. Subsequently, Wang Zhengfei's flame combustion model is utilized to estimate the potential flame height of wildfires along the transmission corridor. Thirdly, the insulation breakdown risk of the transmission line is calculated based on the relative height difference between the flame and the transmission line. Finally, the spatial wildfire-induced tripping risk of the transmission line is then determined by combining the wildfire occurrence probability and the insulation breakdown risk. A case study conducted in Guizhou province, China validates the accuracy of the proposed model. Utilizing ArcGIS, the wildfire occurrence probability distribution in Guizhou is visualized to enhance the efficiency of operation and maintenance. The results indicate that over 80% of wildfire incidents occurred in areas with occurrence probabilities exceeding 50%.
引用
收藏
页数:13
相关论文
共 50 条
  • [1] Risk Distribution Assessment of Wildfire-induced Trips in Transmission Line Based on Flame Combustion Model
    Zhou E.
    Fan L.
    Huang Y.
    Zhou Y.
    Zhou W.
    Chen W.
    Dianwang Jishu/Power System Technology, 2022, 46 (07): : 2778 - 2785
  • [2] Wildfire-Induced Risk Assessment to Enable Resilient and Sustainable Electric Power Grid
    Kovvuri, Srikar
    Chatterjee, Paroma
    Basumallik, Sagnik
    Srivastava, Anurag
    ENERGIES, 2024, 17 (02)
  • [3] An approach for model-based risk assessment
    Gran, BA
    Fredriksen, R
    Thunem, APJ
    COMPUTER SAFETY, RELIABILITY, AND SECURITY, PROCEEDINGS, 2004, 3219 : 311 - 324
  • [4] A Model-Based Approach for Aviation Cyber Security Risk Assessment
    Kiesling, Tobias
    Niederl, Josef
    Ziegler, Juergen
    Krempel, Matias
    PROCEEDINGS OF 2016 11TH INTERNATIONAL CONFERENCE ON AVAILABILITY, RELIABILITY AND SECURITY, (ARES 2016), 2016, : 517 - 525
  • [5] Addressing dependability by applying an approach for model-based risk assessment
    Gran, Bjorn Axel
    Fredriksen, Rune
    Thunem, Atoosa P. -J.
    RELIABILITY ENGINEERING & SYSTEM SAFETY, 2007, 92 (11) : 1492 - 1502
  • [6] Model-based risk assessment of dengue fever transmission in Xiamen City, China
    Guo, Zhinan
    Liu, Weikang
    Liu, Xingchun
    Abudunaibi, Buasiyamu
    Luo, Li
    Wu, Sihan
    Deng, Bin
    Yang, Tianlong
    Huang, Jiefeng
    Wu, Shenggen
    Lei, Lei
    Zhao, Zeyu
    Li, Zhuoyang
    Li, Peihua
    Liu, Chan
    Zhan, Meirong
    Chen, Tianmu
    FRONTIERS IN PUBLIC HEALTH, 2023, 11
  • [7] A deep learning model-based approach to financial risk assessment and prediction
    Li X.
    Li L.
    Applied Mathematics and Nonlinear Sciences, 2024, 9 (01)
  • [8] A Model-based Approach for Assessment and Motivation
    Spector, J. Michael
    Kim, ChanMin
    COMPUTER SCIENCE AND INFORMATION SYSTEMS, 2012, 9 (02) : 893 - 915
  • [9] Model-based risk assessment evaluation
    Germanos, Vasileios
    Zeng, Wen
    SECURITY AND PRIVACY, 2022, 5 (05)
  • [10] A Spatial Assessment of Wildfire Risk for Transmission-Line Corridor Based on a Weighted Naive Bayes Model
    Xiang, Kunxuan
    Zhou, You
    Zhou, Enze
    Lu, Junhan
    Liu, Hui
    Huang, Yu
    FRONTIERS IN ENERGY RESEARCH, 2022, 10