Short-term load forecasting using neural network with principal component analysis
Xin-Chen Guo; Zhou-Yi Chen; Hong-Wei Ge; Yan-Chun Liang
Machine Learning and Cybernetics, 2004. Proceedings of 2004 International Conference on
Volume 6, Issue , 26-29 Aug. 2004 Page(s): 3365 - 3369 vol.6
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Summary: A neural-network-based (NN-based) approach for short-term load forecasting of electrical power is proposed. The principal component analysis (PCA) technique is used to reduce the original electric load variables to several characteristic variables. A single parameter dynamic search algorithm (SPDS) is employed to train the NN. Since the training sample sets can be chosen before forecasting, the interference of the non-correlative samples for the forecasting can be avoided. The effectiveness and the feasibility of on line forecasting of the proposed method are examined using simulated experiments.

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