A neuro wavelet-based approach for short-term load forecasting in integrated generation systems

A neuro wavelet-based approach for short-term load forecasting in integrated generation systems

In the paper is proposed a new neuro-wavelet based approach for the problem of short term load forecasting. The implemented neuro-wavelet based algorithm combines the potential of two soft computing techniques. The strength over other approaches appeared in literature is that firstly the hourly powe...

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Bibliographic Details
Published in:2013 International Conference on Clean Electrical Power (ICCEP) pp. 772 - 776
Main Authors: Bonanno, F., Capizzi, G., Sciuto, G. Lo
Format: Conference Proceeding
Language:English
Published: IEEE 01-06-2013
Subjects:
Computational modeling
Forecasting
Load forecasting
Load modeling
neural networks
neuro wavelet approach
Neurons
power load demand
Power system stability
Recurrent neural networks
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Summary:In the paper is proposed a new neuro-wavelet based approach for the problem of short term load forecasting. The implemented neuro-wavelet based algorithm combines the potential of two soft computing techniques. The strength over other approaches appeared in literature is that firstly the hourly power load data are wavelet processed and then provided as input to an RNN. The obtained simulation results confirm the improved forecasting model over conventional techniques.
ISBN:146734429X
9781467344296
DOI:10.1109/ICCEP.2013.6586946