A New Intelligent Method for Power Load Forecasting

Various factors that influence power load are more and more intricate. The traditional load forecasting methods can no longer adapt to the situation. Self-organizing method is a comparably new modeling method and so as to be easily used in the recognition and prediction of complex non-linear systems...

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Bibliographic Details
Main Authors: Wei Li, Renhui Huang, Jie Bai, Xiue Yuan, Dongxiao Niu
Format: Conference Proceeding
Language:English
Subjects:
Accuracy
Artificial intelligence
Artificial neural networks
Data handling
Intelligent networks
Load forecasting
Load modeling
Polynomials
Power system modeling
Predictive models
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Summary:Various factors that influence power load are more and more intricate. The traditional load forecasting methods can no longer adapt to the situation. Self-organizing method is a comparably new modeling method and so as to be easily used in the recognition and prediction of complex non-linear systems. Compared with traditional forecasting methods, it is of higher prediction accuracy. But common self-organizing methods don't realize the self-organizing function really and cannot show the advantages of self-organizing polynomial. Therefore, combing the artificial neural network with group method of data handling, a simply-improved self-organizing polynomial algorithm which is able to realize the real self-organizing function that is of intelligent characters, is put forward. At last, this kind of self-organizing polynomial algorithm is applied to predict the electric power load in order to prove the validity of this intelligent method as well as that of the improved load forecasting model
ISSN:2164-7143
2164-7151
DOI:10.1109/ISDA.2006.65