Research and application of efficient risk analysis method for electric power grid multiple faults under widespread wildfire disasters. (2nd June 2019)

• Record Type: Journal Article
• Authors: Lu, Jiazheng; Guo, Jun; Jian, Zhou; Xu, Xunjian
• Is Part Of: International transactions on electrical energy systems. Volume 29:Number 9(2019)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2019-06-02
• Subjects: multiple faults -- power grid -- risk analysis -- transmission lines -- wildfire disaster; Electric power -- Periodicals; Electric power systems -- Periodicals; Electrical engineering -- Periodicals; 621.3
• DOI: 10.1002/2050-7038.12055
• Languages: English
• ISSNs: 2050-7038

Abstract

Summary: In recent years, wildfire disasters have occurred frequently in China, with currently more than 70 000 wildfires annually. During the high wildfire disaster period, multiple transmission lines readily trip simultaneously. This poses a serious threat to the safe operation of a large power grid. The probability that multiple transmission lines will trip is far greater than for only a single transmission line. The degree of risk to the power grid needs to be analyzed under multiple tripping combinations of transmission lines caused by wildfire disasters. However, when a large number of wildfire points is involved, the number of such transmission lines tripping combinations become huge, and rapid analysis of the risk to the power grid in these conditions is very difficult. In the present study, the probability distribution characteristics of power grid fault under wildfire disaster were analyzed using historical data on transmission line wildfires and wildfire tripping. A Markov chain Monte Carlo sampling method is proposed to match the probability distribution characteristics of transmission lines tripping under wildfire disasters. The precision of multi‐fault combination sampling is improved effectively. A quantitative power grid risk analysis method is put forward to estimate the sort of transmission lines risk under wildfire disasters efficiently. This gives scientifically based guidelines for reducing the risk to a power grid from widespread wildfire.