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• W75430483 abstract "Occurrence of outages in overhead distribution systems isa significant factor in determining distribution systemreliability. Analysis of animal-related outages has practical valuesince animals cause a large number of outages in overheaddistribution systems. This dissertation presents several differentmethods to investigate the impact of weather and time of the yearon the animal-related outage rate. The animal-related outages fromyear 1998 to year 2007 for different cities in Kansas are providedby Westar Energy. From examinations of the historical data, twofactors which influence the animal-related outages, the month typeand the number of fair weather days are taken as inputs along withhistorical outage data for prediction models. Poisson regressionmodel, neural network model, wavelet based neural network model andBayesian model combined with Monte Carlo simulations are applied tothe weekly data of different cites. Even though Poisson regressionmodels, Bayesian models and neural network models are able torecognize the changing pattern of outage rates under differentweather conditions, they are limited in their ability to follow thehigh peaks in the time series of weekly animal-related outages. Theintroduction of wavelet transform techniques overcomes thisproblem. Simulation results indicate that the wavelet based neuralnetwork models are able to capture the pattern of fast fluctuationsin the weekly outages of different cities in Kansas of varioussizes. A hyperpermutation method inspired by artificial immunesystem algorithm is used to solve the overtraining problem in theapplication of neural networks. Finally, Monte Carlo simulationsbased on conditional probability tables from Bayesian models areused to find out the confidence intervals of the predictions. Weaggregate the weekly data and carry out the analysis on a monthlyand yearly basis too. Simulation results indicate that the modelsare able to capture the pattern as at least 90% of the observedvalues are within the upper limits of 95% confidence in thepredictions for weekly, monthly and yearly animal-related outagesof different cities in Kansas. The results obtained from MonteCarlo simulations are compared with the wavelet based neuralnetwork model to indentify years with more than expected level ofoutages." @default.
• W75430483 created "2016-06-24" @default.
• W75430483 creator A5014326046 @default.
• W75430483 date "2009-05-20" @default.
• W75430483 modified "2023-09-24" @default.
• W75430483 title "Advanced methods for prediction of animal-related outages in overhead distribution systems" @default.
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• W75430483 hasPublicationYear "2009" @default.
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