Title :
Short-term load forecasting based on weather information
Author :
Feng, Wang ; Keng, Yu Er ; Qi, Liu Yong ; Jun, Liu ; Shan, Yan Chen
Author_Institution :
Electr. Power Res. Inst., Beijing, China
Abstract :
This paper addresses electric power short-term load forecasting (the next day 24 or 96 time point load) based on weather forecasting information. It describes a load forecasting system that is running in North China Electric Power Network. The system can consider the effect of temperature. Relative humidity and weather condition on the load. The forecasting result is improved. The ANN´s techniques and a simplified pattern recognition are adopted to deal with the complex relation between the load and weather variables
Keywords :
load forecasting; neural nets; pattern recognition; power system analysis computing; ANN techniques; North China Electric Power Network; pattern recognition; relative humidity; short-term load forecasting; temperature effect; weather condition; weather information; weather variables; Artificial neural networks; Erbium; Humidity; Load forecasting; Load modeling; Predictive models; Rain; Snow; Temperature; Weather forecasting;
Conference_Titel :
Power System Technology, 1998. Proceedings. POWERCON '98. 1998 International Conference on
Conference_Location :
Beijing
Print_ISBN :
0-7803-4754-4
DOI :
10.1109/ICPST.1998.729029
