Abstract
Load forecasting has become in recent years one of the major areas of research in electrical engineering. In a deregulated, competitive power market, utilities tend to maintain their generation reserve close to the minimum required by an independent system operator. This creates a need for an accurate instantaneous-load forecast for the next several minutes. An accurate forecast eases the problem of generation and load management to a great extent. This paper presents a novel artificial neural network (ANN) for very short-term load forecasting. The model with tapped delay line input is simple, fast, and accurate. Obtained results from extensive testing on Taipower System load data confirm the validity of the proposed approach.
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Chen, H., Huang, K., Chang, L. (2005). Application of Neural Networks for Very Short-Term Load Forecasting in Power Systems. In: Wang, J., Liao, XF., Yi, Z. (eds) Advances in Neural Networks – ISNN 2005. ISNN 2005. Lecture Notes in Computer Science, vol 3498. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11427469_100
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DOI: https://doi.org/10.1007/11427469_100
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-25914-5
Online ISBN: 978-3-540-32069-2
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