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A Study on Forecasting Method for a Short-Term Demand Forecasting of Customer's Electric Demand  

Ko, Jong-Min (한전 전력연구원)
Yang, Il-Kwon (한전 전력연구원)
Song, Jae-Ju (한전 전력연구원)
Publication Information
The Transactions of The Korean Institute of Electrical Engineers / v.58, no.1, 2009 , pp. 1-6 More about this Journal
Abstract
The traditional demand prediction was based on the technique wherein electric power corporations made monthly or seasonal estimation of electric power consumption for each area and subscription type for the next one or two years to consider both seasonally generated and local consumed amounts. Note, however, that techniques such as pricing, power generation plan, or sales strategy establishment were used by corporations without considering the production, comparison, and analysis techniques of the predicted consumption to enable efficient power consumption on the actual demand side. In this paper, to calculate the predicted value of electric power consumption on a short-term basis (15 minutes) according to the amount of electric power actually consumed for 15 minutes on the demand side, we performed comparison and analysis by applying a 15-minute interval prediction technique to the average and that to the time series analysis to show how they were made and what we obtained from the simulations.
Keywords
Incentive-Based Demand Response; Regular Load Reduction; Customer Baseline Load; Moving Average; Exponential Smoothing Method; ARMA; Load Profile;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
Times Cited By SCOPUS : 0
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