Monitoring of Transmission Line Wildfires Using Satellite Remote Sensing

DOI

10.2991/eeeis-17.2017.38How to use a DOI?

Keywords

Satellite Remote Sensing, Wildfire of Transmission Line, Wildfire Monitoring, Fire Spot Screening, Fuzzy Synthetic Evaluation Method.

Abstract

Wildfires can cause transmission lines to trip, which can prove difficult to reclose successfully. Using satellite remote sensing technology to monitor wildfires can alert the power sector to potential damage. However, wildfires along transmission lines may have a small burned area and may spread rapidly. In addition, false alarms and missing alarms often happen in real-world situations. Monitoring, therefore, needs high spatial and temporal resolution satellite data. To address this problem, this paper identifies the monitoring index requirements for satellite data based on the characteristics of transmission line wildfires. Using historical fault information from wildfires for transmission lines in Guangdong province, China, this paper considered the influence of each impact factor, combining a fuzzy synthetic evaluation method and trapezoidal method to establish a model for wildfire screening. The proposed method can distinguish true and false fire spots. The accuracy of the model was verified by using examples, and the model was able to meet the accuracy requirements for engineering applications. Finally, this paper suggested a three-level wildfire alarm system for transmission lines according to operating experience, providing guidance for on site management.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Xiao-Ran YI
AU  - En-Zhe ZHOU
AU  - Li YE
AU  - Shuang-Yu DU
AU  - Zhan-Qing YU
PY  - 2017/09
DA  - 2017/09
TI  - Monitoring of Transmission Line Wildfires Using Satellite Remote Sensing
BT  - Proceedings of the 3rd Annual International Conference on Electronics, Electrical Engineering and Information Science (EEEIS 2017)
PB  - Atlantis Press
SP  - 277
EP  - 284
SN  - 2352-5401
UR  - https://doi.org/10.2991/eeeis-17.2017.38
DO  - 10.2991/eeeis-17.2017.38
ID  - YI2017/09
ER  -