DocumentCode
531916
Title
Application of outlier mining in power load forecasting
Author
Donghui Shi
Author_Institution
Sch. of Electron. & Inf. Eng., Anhui Univ. of Archit., Hefei, China
Volume
5
fYear
2010
fDate
22-24 Oct. 2010
Abstract
According to the theory of power load forecasting, data mining based on historical data of power load is used in load predicting. During the practical application, there are some errors in the data collection, and a load forecasting curve often contains big jagged edges. This paper presents a new outlier data mining approach. It finds sharp angle points between two lines, which correspond to outliers of power load. We smooth the curve at same time outliers are handled. Experiments show that after the new outlier mining approach was applied, load forecast results were improved significantly.
Keywords
data mining; load forecasting; power engineering computing; big jagged edges; data collection errors; load prediction; outlier data mining approach; outlier mining application; power load data; power load forecasting theory; sharp angle points; Load modeling; outlier mining; power load forecastin; smooth; the sharp angle points between two lines;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Application and System Modeling (ICCASM), 2010 International Conference on
Conference_Location
Taiyuan
Print_ISBN
978-1-4244-7235-2
Electronic_ISBN
978-1-4244-7237-6
Type
conf
DOI
10.1109/ICCASM.2010.5619137
Filename
5619137
Link To Document