Earticle

초록

영어

With global warming, the increasing forest fires have caused trips and outages frequently along transmission lines, which is a serious threat to the operation stability of power grids. Impact factors on transmission line fires are numerous and the current risk assessment methods could hardly handle the complex nonlinear relationship between risks and factors, therefore, a method based on BP neural network is presented to assess fire risk of transmission line in this paper. Firstly, risk assessment system would be established according to impact factors on transmission line fire. Then, based on neural network model, the complex nonlinear relationships between fire risk grade and evaluation factors could be built. Finally, combined with GIS technology, risk assessment on transmission line fire would be done. The applicability and accuracy of this method have been explored by a fire risk assessment of transmission line in Shanxi province. The result shows that the BP neural network based model has good recognition effect, credibility, and consistent with the survey result on transmission line fire risk in the region over the years.

목차

Abstract
 1. Introduction
 2. Modeling and Analysis
  2.1. Overview of the Studied Area
  2.2. Assessment System on Fire Risk of Transmission Lines
  2.3. Risk assessment Method on Forest Fire Disaster
  2.4. Case Study
  2.5. Assessment Result and Analysis in the Study Area
 3. Conclusion
 Acknowledgements
 References

키워드

저자

• Jing Zhou [ School of Control and Computer Engineering, North China Electric Power University, Beijing 102206, China ]
• Weiqing Ma [ Department of Information Technology, Shanxi Yangquan Electric Power Corporation, Yangquan 045000, China ]
• Jinya Miao [ Huada Tianyuan (Beijing) Electric Power Technology CO., LTD, Beijing 102206, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Smart Home

• 간기

  격월간

• pISSN

  1975-4094

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605