Development of short-term load forecasting algorithm using hourly temperature

被引：0
作者：
机构：
[1] Song, Kyung-Bin
来源：
Song, K.-B. (kbsong@ssu.ac.kr) | 1600年 / Korean Institute of Electrical Engineers卷 / 63期
关键词：
Exponential smoothing method; Hourly temperature; Power system operation; Short-term load forecasting; Temperature-electric power demand sensitivity;
D O I：
10.5370/KIEE.2014.63.4.451
中图分类号：
学科分类号：
摘要：
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.
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页码：451 / 454
页数：3
相关论文
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