Development of short-term load forecasting algorithm using hourly temperature
- Authors
- Song, K.-B.
- Issue Date
- 2014
- Publisher
- Korean Institute of Electrical Engineers
- Keywords
- Exponential smoothing method; Hourly temperature; Power system operation; Short-term load forecasting; Temperature-electric power demand sensitivity
- Citation
- Transactions of the Korean Institute of Electrical Engineers, v.63, no.4, pp.451 - 454
- Journal Title
- Transactions of the Korean Institute of Electrical Engineers
- Volume
- 63
- Number
- 4
- Start Page
- 451
- End Page
- 454
- URI
- http://scholarworks.bwise.kr/ssu/handle/2018.sw.ssu/10966
- DOI
- 10.5370/KIEE.2014.63.4.451
- ISSN
- 1975-8359
- 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.
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Collections - College of Engineering > School of Electrical Engineering > 1. Journal Articles
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