Title :
Short-term load forecasting system using data mining
Author :
Jin, Liu ; Jilai, Yu
Author_Institution :
Dept. of Electr. Eng., Harbin Inst. of Technol., Harbin, China
Abstract :
In this paper, by means of data mining techniques, a platform of data warehouse is designed after preprocessing the huge amounts original data of power system, and a system for short term load forecasting (STLF) is developed, in which there is the synthetic technology of both fuzzy clustering and robust regression model in the platform. The useful data excavated from large amounts of data can offer the effective and accurate load forecasting information for reliable and economic operation of power systems. The validity of the designed system for STLF is shown by the simulation results of an actual power system in China.
Keywords :
data mining; data warehouses; fuzzy set theory; load forecasting; pattern clustering; power systems; STLF; data mining techniques; data warehouse; fuzzy clustering; power system; robust regression model; short-term load forecasting system; Data mining; Data warehouses; Load forecasting; Load modeling; Meteorology; Robustness; data mining; data warehouse; fuzzy clustering; load forecasting; robust regression;
Conference_Titel :
Automation and Computing (ICAC), 2011 17th International Conference on
Conference_Location :
Huddersfield
Print_ISBN :
978-1-4673-0000-1
