DocumentCode
1185880
Title
Optimal Vegetation Maintenance Scheduling of Overhead Electric Power Distribution Systems
Author
Kuntz, P. A. ; Christie, R. D. ; Venkata, S. S.
Author_Institution
University of Washington, Seattle, WA; Iowa State University, Ames, IA
Volume
22
Issue
7
fYear
2002
fDate
7/1/2002 12:00:00 AM
Firstpage
64
Lastpage
64
Abstract
Vegetation maintenance involves trimming or removing trees and brush near the overhead conductors to reduce the number of tree related outages and maintain system reliability. This paper reports a maintenance scheduling algorithm that determines the optimal location and time for performing vegetation maintenance on overhead distribution feeders. A vegetation failure rate model is developed that quantifies the impact of the maintenance schedule on the reliability of a distribution system. Using this reliability model and a predictive reliability assessment algorithm, the maintenance scheduling algorithm is formulated as a combinatorial optimization problem that considers different objective functions and constraints. After experimentation with several heuristic search techniques, a hybrid genetic algorithm-hill climbing technique consistently found the highest quality maintenance schedules. The results from applying the maintenance scheduling algorithm to a real distribution system are also presented. It is shown that the new maintenance scheduling algorithm can find lower cost and more reliable schedules as compared to standard fixed interval schedules.
Keywords
Brushes; Conductors; Constraint optimization; Genetics; Maintenance; Prediction algorithms; Predictive models; Reliability; Scheduling algorithm; Vegetation; Distribution systems; Tabu search; genetic algorithms; reliability assessment; reliability centered maintenance; simulated annealing; tree trimming; vegetation maintenance; vegetation maintenance scheduling;
fLanguage
English
Journal_Title
Power Engineering Review, IEEE
Publisher
ieee
ISSN
0272-1724
Type
jour
DOI
10.1109/MPER.2002.4312439
Filename
4312439
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