Title :
A holiday short term load forecasting considering weather information
Author :
Ding, Qia ; Zhang, Hui ; Huang, Tao ; Zhang, Junyi
Author_Institution :
NARI, Nanjing
fDate :
Nov. 29 2005-Dec. 2 2005
Abstract :
Load forecast for holidays is always hard to be processed, due to the dissimilar load behaviors compared with normal weekdays and to the insufficient samples for normal algorithm. The load during holiday is mainly influenced by the long time load increase and weather condition. The proposed method uses a hybrid method of similar days to obtain scaled load curve and fuzzy inference method to forecast the holiday load level. Weather information and load annual increase are considered in fuzzy inference to eliminate their influence. The proposed method is implemented in real-time EMS with actual load data. The test results show good accuracy especially in weather change days
Keywords :
energy management systems; inference mechanisms; load forecasting; dissimilar load behaviors; fuzzy inference method; holidays; real-time EMS; scaled load curve; short term load forecasting; weather information; Economic forecasting; Load forecasting; Medical services; Power generation economics; Power system modeling; Power system planning; Power system reliability; Predictive models; Testing; Weather forecasting; Fuzzy Inference; Short Term Load Forecast; Weather Information;
Conference_Titel :
Power Engineering Conference, 2005. IPEC 2005. The 7th International
Conference_Location :
Singapore
Print_ISBN :
981-05-5702-7
DOI :
10.1109/IPEC.2005.206879