Title :
Research on Analytical Methods of Electric Load Based on Data Mining
Author :
Lu, Yun ; Huang, Yinuo
Author_Institution :
Sch. of Electr. Eng., Shenyang Univ. of Technol., Shenyang, China
Abstract :
In the thesis, an analytical method of electric load based on data mining is presented. To know the regularity of load changes, periodicity of load is discussed by analyzing historic load data. Data mining principle is adopted to analyze electric load data by clustering, and load is classified effectively. This paper supplies strong theoretical basis for production plan and load forecasting in electric power system. Examples prove that the method presented has exactitude and validity.
Keywords :
data mining; load forecasting; pattern clustering; power engineering computing; data clustering; data mining; electric load data; electric power system; load forecasting; Clustering algorithms; Data analysis; Data mining; Economic forecasting; Equations; Load forecasting; Power generation economics; Power system economics; Production systems; Temperature sensors; clustering; data mining; electric power system; load analysis;
Conference_Titel :
Intelligent Computation Technology and Automation (ICICTA), 2010 International Conference on
Conference_Location :
Changsha
Print_ISBN :
978-1-4244-7279-6
Electronic_ISBN :
978-1-4244-7280-2
DOI :
10.1109/ICICTA.2010.592
