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Artificial neural networks applied to long-term electricity demand forecasting

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2 Author(s)
Mamun, M.A. ; Dept. of Electr; & Electron. Eng., Tokyo Univ. of Agric. & Technol., Japan ; Nagasaka, K.

The electric power demand in Japan has steadily increased and the load factor of total power system has decreased. It is therefore very important to the utilities to have advance knowledge of their electrical load. One of the important points for forecasting the long-term load in Japan is to take into account the past and present economic situations and power demand. These points were considered in this study. The proposed artificial neural network (ANN) that is radial basis function network (RBFN) has also showed that the changes in loads are a reflection of economy. Here, prediction of peak loads in Japan up to year 2015 is discussed using the RBFN and the maximum demands for 2001 through 2015 are predicted to be elevated from 179.42 GW to 209.18 GW. The annual average rate of load growth seen per ten years until 2015 is about 1.39%.

Published in:

Hybrid Intelligent Systems, 2004. HIS '04. Fourth International Conference on

Date of Conference:

5-8 Dec. 2004