DocumentCode :
3252936
Title :
Classification of input and output variables for a Bayesian model to analyze animal-related outages in overhead distribution systems
Author :
Gui, Min ; Pahwa, Anil ; Das, Sanjoy
Author_Institution :
Quanta Technol., LLC, Raleigh, NC, USA
fYear :
2010
fDate :
14-17 June 2010
Firstpage :
469
Lastpage :
474
Abstract :
Animals, such as squirrels, cause significant outages in overhead distribution systems. Models that would accurately estimate outages caused by animals would be very useful for utilities for year-end analysis of reliability performance of the distribution system. Large increase in outages caused by animals would require the utility to do further evaluation and take remedial actions. A two-layer Bayesian network model with Month-Type, Level of Fair Weather Days in the week, and Outage Level in the previous week as input and Outage Level in the week is presented in this paper for estimation of weekly animal-related outages. Results of different approaches for classification of inputs and output are presented, which are then compared to select the best classification of input and output variables for the model.
Keywords :
Bayes methods; power distribution reliability; Bayesian model; animal-related outages; distribution system reliability; overhead distribution systems; Animals; Bayesian methods; Distributed computing; Graphical models; Input variables; Neural networks; Performance analysis; Reliability engineering; Temperature; Wavelet analysis; Bayesian model; animal-related outage; distribution system; distribution system reliability;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Probabilistic Methods Applied to Power Systems (PMAPS), 2010 IEEE 11th International Conference on
Conference_Location :
Singapore
Print_ISBN :
978-1-4244-5720-5
Type :
conf
DOI :
10.1109/PMAPS.2010.5528968
Filename :
5528968
Link To Document :
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