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Design of short term load forecasting model based on BP neural network and Fuzzy rule

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2 Author(s)
Zeng yanfei ; Automatization Dept., Guangdong Polytech. Normal Univ., Guangzhou, China ; Wu Yinbo

By way of analyzing the more common advantages and disadvantages of short-term load forecasting, the short-term load forecasting model based on BP neural network and Fuzzy rule has been proposed. In the model, the load forecasting has been divided into two parts: the basic load component and the temperature and holiday load component. The former completed by the BP neural network, the latter completed by the fuzzy logic. Since introduction the smooth coefficient, forgetting factor, uneven membership into the model, the learning speed of BP neural network has been improved and the sensitivity of the load to temperature has been enhanced.

Published in:

Electric Information and Control Engineering (ICEICE), 2011 International Conference on

Date of Conference:

15-17 April 2011