International Journal of Communications, Network and System Sciences

Volume 3, Issue 3 (March 2010)

ISSN Print: 1913-3715   ISSN Online: 1913-3723

Google-based Impact Factor: 0.66  Citations  h5-index & Ranking

Short-Term Load Forecasting Using Soft Computing Techniques

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DOI: 10.4236/ijcns.2010.33035    6,604 Downloads   13,745 Views  Citations

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ABSTRACT

Electric load forecasting is essential for developing a power supply strategy to improve the reliability of the ac power line data network and provide optimal load scheduling for developing countries where the demand is increased with high growth rate. In this paper, a short-term load forecasting realized by a generalized neuron–wavelet method is proposed. The proposed method consists of wavelet transform and soft computing technique. The wavelet transform splits up load time series into coarse and detail components to be the features for soft computing techniques using Generalized Neurons Network (GNN). The soft computing techniques forecast each component separately. The modified GNN performs better than the traditional GNN. At the end all forecasted components is summed up to produce final forecasting load.

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D. Chaturvedi, S. Premdayal and A. Chandiok, "Short-Term Load Forecasting Using Soft Computing Techniques," International Journal of Communications, Network and System Sciences, Vol. 3 No. 3, 2010, pp. 273-279. doi: 10.4236/ijcns.2010.33035.

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