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Utilizing time series analysis to forecast long-term electrical consumption

UNCW Author/Contributor (non-UNCW co-authors, if there are any, appear on document)
Danny Robert Modlin (Creator)
The University of North Carolina Wilmington (UNCW )
Web Site:
James Blum

Abstract: Developing an accurate forecast model for the amount of power consumed will include such factors as time of day, day of the year, the weather, among many others. Based upon these given factors, current models use a neural network approach to forecast in the very near future. For the purpose of business operations, this model should be accurate for predicting power usage at least six months into the future. Using regression with time series analysis, the goal is to build a model that re°ects systematic movements in the data and predict them so errors would be more or less random and minimized.

Additional Information

A Thesis Submitted to the University of North Carolina at Wilmington in Partial Fulfillment of the Requirement for the Degree of Masters of Science
Language: English
Date: 2009
Electric power consumption--Forecasting, Electric power consumption--Southern States--Statistics, Progress Energy, Time-series analysis--Mathematical models
Time-series analysis -- Mathematical models
Electric power consumption -- Southern States -- Statistics
Progress Energy
Electric power consumption -- Forecasting