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Permanent link (DOI): https://doi.org/10.7939/R3D912

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Intelligent Methods for Evaluating the Impact of Weather on Power Transmission Infrastructure Open Access

Descriptions

Other title
Subject/Keyword
weather impact on power transmission lines
precipitation cooling thermal model
ice accretion model optimization
Type of item
Thesis
Degree grantor
University of Alberta
Author or creator
Pytlak, Pawel Maksymilian
Supervisor and department
Musilek, Petr (Electrical and Computer Engineering)
Lozowski, Edward (Earth and Atmospheric Sciences)
Examining committee member and department
Robinson Fayek, Aminah (Civil and Environmental Engineering)
Stull, Roland (Earth, Ocean and Atmospheric Sciences)
Knight, Andy (Electrical and Computer Engineering)
Reformat, Marek (Electrical and Computer Engineering)
Department
Department of Electrical and Computer Engineering
Specialization
Software Engineering and Intelligent Systems
Date accepted
2012-08-15T10:53:43Z
Graduation date
2012-11
Degree
Doctor of Philosophy
Degree level
Doctoral
Abstract
Weather has a significant impact on human society, both in driving the life-giving physical processes that allow humans to meet their most basic needs, and as an adversarial force, often causing significant losses to property and life. The electrical power industry is particularly subject to significant weather influence due to the wide-scale exposure of its infrastructure to nature's elements. Severe storms can cause damage in the millions of dollars, and even directly or indirectly cause fatalities. Weather patterns and their impact on the industry are hard to predict using simple statistical measures, and thus more complex methodologies must be used to provide accurate forecasts and impact assessment. The increasing global awareness of climate change is driving the power industry to adopt more green energy sources. Unfortunately, these sources cannot be constructed at will; they must be harnessed where they are available. Consequently, the power industry is not always ready to incorporate these sources into the existing grid without costly infrastructure upgrades and/or expansion projects. To help alleviate these concerns, this thesis presents intelligent methodologies that can use either modern Numerical Weather Prediction (NWP) models or direct weather observations to solve some of the challenges faced by the power industry. It describes the optimization and verification of an ice accretion forecast system that is tuned to increase its predictive accuracy using computational intelligence techniques. The performance of the system is also evaluated in a true forecast simulation. This thesis also describes the enhancement of an industry standard line rating model that is expanded to include the cooling impact of precipitation. Studies are presented that discover the optimal configuration of weather-based dynamic thermal rating systems, evaluate the accuracy and risk of forecasting line ampacity ratings using NWP models, and assess the reduction in emissions by using dynamic ratings to incorporate more green energy into the transmission grid. Finally, this thesis describes intelligent systems aimed at assisting and supporting planning decisions in transmission infrastructure construction and expansion projects.
Language
English
DOI
doi:10.7939/R3D912
Rights
Permission is hereby granted to the University of Alberta Libraries to reproduce single copies of this thesis and to lend or sell such copies for private, scholarly or scientific research purposes only. Where the thesis is converted to, or otherwise made available in digital form, the University of Alberta will advise potential users of the thesis of these terms. The author reserves all other publication and other rights in association with the copyright in the thesis and, except as herein before provided, neither the thesis nor any substantial portion thereof may be printed or otherwise reproduced in any material form whatsoever without the author's prior written permission.
Citation for previous publication
P. Pytlak, P. Musilek, E. Lozowski, and D. Arnold, “Evolutionary optimization of an ice accretion forecasting system,” Mon. Wea. Rev., vol. 138, no. 7, pp. 2913–2929, Jul. 2010.J. Hosek, P. Musilek, E. Lozowski, and P. Pytlak, “Forecasting severe ice storms using numerical weather prediction: the March 2010 Newfoundland event,” Natural Hazards and Earth System Science, vol. 11, no. 2, pp. 587–595, 2011.P. Pytlak, P. Musilek, E. Lozowski, and J. Toth, “Modelling precipitation cooling of overhead conductors,” Electric Power Systems Research, vol. 81, no. 12, 2011.J. Hosek, P. Musilek, E. Lozowski, and P. Pytlak, “Effect of time resolution of meteorological inputs on dynamic thermal rating calculations,” IET Generation, Transmission Distribution, vol. 5, pp. 941–947, Sept. 2011.P. Pytlak and P. Musilek, “An intelligent weather-based system to support optimal routing of power transmission lines,” in 10th Electrical Power and Energy Conference (EPEC 2010), pp. 1–6, IEEE, 2010.P. Pytlak and P. Musilek, “Selective upgrading of transmission lines using DTCR,” in IEEE 25th Canadian Conference on Electrical and Computer Engineering (CCECE 2012), pp. 1–4, Jun 2012.P. Pytlak, P. Musilek, and J. Doucet, “Using dynamic thermal rating systems to reduce power generation emissions,” in IEEE Power and Energy Society General Meeting, pp. 1–7, Jul 2011.

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File title: Intelligent Methods for Evaluating the Impact of Weather on Power Transmission Infrastructure
File author: Pawel Maksymilian Pytlak, University of Alberta, Faculty of Engineering
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