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  • School of Engineering, Computer and Mathematical Sciences - Te Kura Mātai Pūhanga, Rorohiko, Pāngarau
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Application of Dynamic Thermal Rating: Overhead Line Critical Spans Identification Under Weather Dependent Optimized Sensor Placement

Talpur, S; Lie, TT; Zamora, R
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http://hdl.handle.net/10292/13212
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Abstract
Dynamic thermal rating (DTR) for an overhead transmission line is a viable and cost-effective technique based on real weather conditions to mitigate congestion and avoid load shedding for reliable transfer of the required electricity. Spans of overhead lines passing through multiple geographical regions face diverse weather conditions and varying terrain, and thus need to be monitored to obtain reliable estimates of line loadability. Spans facing the worst weather and with the longest length determine the absolute minimum line loadability and are therefore known as critical spans. Identifying critical spans is important in allowing utility providers to monitor their overhead transmission networks spanning large geographical regions. This paper focuses on identifying critical spans using the proposed technique to find the bottleneck to the overhead transmission network for optimum power transfer. It determines the optimal number and placement of sensors across the entire test line, dividing the line into non-uniform segments, each carrying multiple length spans passing through flat and non-flat terrains. The resulting critical spans determine the line loadability that can effectively relieve transmission line congestion, based on the allowable vertical clearance to the ground. The outcome of the proposed technique is validated against the conventional technique for critical span identification.
Keywords
Dynamic thermal rating; Critical line spans; Optimal sensor placement; Non-uniform line segmentation; Weather conditions and span topography; Line congestion and load shed management
Date
November 28, 2019
Source
Electric Power Systems Research, 180, 106125.
Item Type
Journal Article
Publisher
Elsevier
DOI
10.1016/j.epsr.2019.106125
Publisher's Version
https://www.sciencedirect.com/science/article/pii/S0378779619304444?via%3Dihub
Rights Statement
Copyright © 2020 Elsevier Ltd. All rights reserved. This is the author’s version of a work that was accepted for publication in (see Citation). Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. The definitive version was published in (see Citation). The original publication is available at (see Publisher's Version).

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