DocumentCode :
3045234
Title :
ANN-based short-term load forecasting in electricity markets
Author :
Chen, Hong ; Cañizares, Claudio A. ; Singh, Ajit
Author_Institution :
Dept. of Electr. & Comput. Eng., Waterloo Univ., Ont., Canada
Volume :
2
fYear :
2001
fDate :
2001
Firstpage :
411
Abstract :
This paper proposes an artificial neural network (ANN)-based short-term load forecasting technique that considers electricity price as one of the main characteristics of the system load, demonstrating the importance of considering pricing when predicting loading in today´s electricity markets. Historical load data from the Ontario Hydro system as well as pricing information from the neighboring system are used for testing, showing the good performance of the proposed method
Keywords :
electricity supply industry; load forecasting; neural nets; power system analysis computing; power system economics; tariffs; Canada; artificial neural network; electricity markets; electricity price; pricing; short-term load forecasting; Artificial neural networks; Economic forecasting; Electricity supply industry; Feedforward systems; Job shop scheduling; Load forecasting; Power markets; Pricing; System testing; Weather forecasting;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Power Engineering Society Winter Meeting, 2001. IEEE
Conference_Location :
Columbus, OH
Print_ISBN :
0-7803-6672-7
Type :
conf
DOI :
10.1109/PESW.2001.916876
Filename :
916876
Link To Document :
بازگشت