Abstract
A back-propagation neural network method is proposed for accurate frequencies, amplitudes and phases estimation from periodic signals in power systems, and the convergence theorem shows that the proposed algorithm can be convergent asymptotically to its global minimum. The method is aimed at the system in which the sampling frequency cannot be locked on the actual fundamental frequency. Some simulating examples are given and the results show that the accuracy of the estimates provided by the proposed approach in the asynchronous case is relatively better than that of the estimates obtained with the conventional harmonic analysis methods.
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© 2007 Springer Berlin Heidelberg
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Wang, X., He, Y., Long, Y. (2007). Neural Network Based High Accuracy Frequency Harmonic Analysis in Power System. In: Liu, D., Fei, S., Hou, Z., Zhang, H., Sun, C. (eds) Advances in Neural Networks – ISNN 2007. ISNN 2007. Lecture Notes in Computer Science, vol 4493. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72395-0_123
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DOI: https://doi.org/10.1007/978-3-540-72395-0_123
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