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Power Load Prediction Based on Fractal Theory
Joint Authors
Wanqing, Song
Jian-Kai, Liang
Cattani, Carlo
Source
Advances in Mathematical Physics
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-6, 6 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-03-19
Country of Publication
Egypt
No. of Pages
6
Main Subjects
Abstract EN
The basic theories of load forecasting on the power system are summarized.
Fractal theory, which is a new algorithm applied to load forecasting, is introduced.
Based on the fractal dimension and fractal interpolation function theories, the correlation algorithms are applied to the model of short-term load forecasting.
According to the process of load forecasting, the steps of every process are designed, including load data preprocessing, similar day selecting, short-term load forecasting, and load curve drawing.
The attractor is obtained using an improved deterministic algorithm based on the fractal interpolation function, a day’s load is predicted by three days’ historical loads, the maximum relative error is within 3.7%, and the average relative error is within 1.6%.
The experimental result shows the accuracy of this prediction method, which has a certain application reference value in the field of short-term load prediction.
American Psychological Association (APA)
Jian-Kai, Liang& Cattani, Carlo& Wanqing, Song. 2015. Power Load Prediction Based on Fractal Theory. Advances in Mathematical Physics،Vol. 2015, no. 2015, pp.1-6.
https://search.emarefa.net/detail/BIM-1053032
Modern Language Association (MLA)
Jian-Kai, Liang…[et al.]. Power Load Prediction Based on Fractal Theory. Advances in Mathematical Physics No. 2015 (2015), pp.1-6.
https://search.emarefa.net/detail/BIM-1053032
American Medical Association (AMA)
Jian-Kai, Liang& Cattani, Carlo& Wanqing, Song. Power Load Prediction Based on Fractal Theory. Advances in Mathematical Physics. 2015. Vol. 2015, no. 2015, pp.1-6.
https://search.emarefa.net/detail/BIM-1053032
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1053032