Title :
Application of outlier mining in power load forecasting
Author_Institution :
Sch. of Electron. & Inf. Eng., Anhui Univ. of Archit., Hefei, China
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;
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
DOI :
10.1109/ICCASM.2010.5619137
