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http://dx.doi.org/10.5351/KJAS.2014.27.5.843

Electricity Demand Forecasting for Daily Peak Load with Seasonality and Temperature Effects  

Jung, Sang-Wook (Department of Applied Statistics, Chung-Ang University)
Kim, Sahm (Department of Applied Statistics, Chung-Ang University)
Publication Information
The Korean Journal of Applied Statistics / v.27, no.5, 2014 , pp. 843-853 More about this Journal
Abstract
Accurate electricity demand forecasting for daily peak load is essential for management and planning at electrical facilities. In this paper, we rst, introduce the several time series models that forecast daily peak load and compare the forecasting performance of the models based on Mean Absolute Percentage Error(MAPE). The results show that the Reg-AR-GARCH model outperforms other competing models that consider Cooling Degree Day(CDD) and Heating Degree Day(HDD) as well as seasonal components.
Keywords
Time Series models; daily peak load; CDD; HDD; seasonality; MAPE;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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