Ahmad, Junaid and Malik, Aamir Saeed and Xia, Likun (2012) Vegetation encroachment monitoring for transmission lines right-of-ways:A survey. Electric Power Systems Research. (In Press)
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Abstract
With increasing blackouts owing to vegetation encroachments for transmission lines right-of-ways, it
has become imperative for electric utilities to review their vegetation management practices to avoid
incidents of un-intended encroachments. In this paper, advantages and limitations of existing techniques
for inspecting transmission lines is presented. Regarding the clearance of un-intended vegetation
for transmission lines right-of-ways, the surveillance of transmission lines is performed periodically
through visual inspection, or by airborne system. The geographical information system (GIS) containing
the geo-referenced data of assets, lands, wherefrom the transmission lines pass are essential tools for the
improvement of transmission lines maintenance. Air-borne LiDAR scanners, videography, and aerophotogranometry
are now available for surveillance applications. These tools, because of their accuracy in
spatial resolution, can be applied to track not only invasions, but also monitor the vegetation surrounding
the transmission lines right-of-ways. The paper discusses concept of utilizing multispectral satellite
stereo images to recover 3D-digital elevation model (DEM) of transmission lines right-of-ways to identify
dangerous vegetation that can strike the power lines to cause blackouts. Further, a new wireless multimedia
sensor networks (WMSNs) based method is proposed which is cost effective, less time consuming
and more accurate for the automated power line inspection against vegetation encroachments.
Item Type: | Article |
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Impact Factor: | 1.726 |
Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering |
Departments / MOR / COE: | Centre of Excellence > Center for Intelligent Signal and Imaging Research Departments > Electrical & Electronic Engineering Research Institutes > Energy Research Institutes > Institute for Health Analytics |
Depositing User: | Dr. L Xia |
Date Deposited: | 22 Nov 2012 02:56 |
Last Modified: | 20 Mar 2017 01:57 |
URI: | http://scholars.utp.edu.my/id/eprint/8440 |