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http://dx.doi.org/10.5370/KIEE.2014.63.4.451

Development of Short-Term Load Forecasting Algorithm Using Hourly Temperature  

Song, Kyung-Bin (Dept. of Electrical Engineering at Soongsil University)
Publication Information
The Transactions of The Korean Institute of Electrical Engineers / v.63, no.4, 2014 , pp. 451-454 More about this Journal
Abstract
Short-term load forecasting(STLF) for electric power demand is essential for stable power system operation and efficient power market operation. We improved STLF method by using hourly temperature as an input data. In order to using hourly temperature to STLF algorithm, we calculated temperature-electric power demand sensitivity through past actual data and combined this sensitivity to exponential smoothing method which is one of the STLF method. The proposed method is verified by case study for a week. The result of case study shows that the average percentage errors of the proposed load forecasting method are improved comparing with errors of the previous methods.
Keywords
Short-term load forecasting; Hourly temperature; Temperature-electric power demand sensitivity; Exponential smoothing method; Power system operation;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
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