Title :
A novel ultra-short term load forecasting method based on load trend and fuzzy c-means clustering algorihm
Author :
Zhang Yi ; Zhang Feng ; Zhu Bingquan
Author_Institution :
Zhejiang Univ. of Water Resources & Electr. Power, Hangzhou, China
Abstract :
According to the requirement of ultra-short term load forecasting in a certain provincial power grid and on the basis of fully analyzing the load characteristics, a novel ultra-short term load forecasting method based on the trend of power load fluctuation and fuzzy C-means clustering algorithm is proposed. In this method the identification and correction of pseudo data are integrated into the load forecasting process. This method is accurate and practicable; the practical application of this method shows that its error analysis index is much better than that from other ultra-short load forecasting method being used in the certain provincial power grid.
Keywords :
error analysis; fuzzy set theory; load forecasting; pattern clustering; power grids; error analysis index; fuzzy c-means clustering algorithm; load trend; provincial power grid; ultrashort term load forecasting method; Equations; Forecasting; Load forecasting; Market research; Mathematical model; Power grids; Energy management system (EMS); Fuzzy C-means clustering algorithm; Load trend; Power system dispatching; Ultra-short term load forecasting;
Conference_Titel :
Power System Technology (POWERCON), 2014 International Conference on
Conference_Location :
Chengdu
DOI :
10.1109/POWERCON.2014.6993488