Abstract
A new approach to nonparametric signal modelling techniques for tracking time-varying phasors of voltage and current in power systems is investigated. A first order polynomial is used to approximate these signals locally on a sliding window of fixed length. Non-quadratic methods to fit the linear function to the data, give superior performance over least squares methods in terms of accuracy. But these non-quadratic methods are iterative procedures and are much slower than the least squares method. A neural network is then used to model the non-quadratic methods. Once the neural network is trained, it is much faster than the least squares and the non-quadratic methods. The paper concludes with the presentation of the representative testing results.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Begovic, M., et al.: Frequency tracking in power networks in the presence of harmonics. IEEE Transactions on Power Delivery 8, 480–486 (1993)
Sachdev, M., Giray, M.: A least squares technique for determining power system frequency. IEEE Transactions on PAS (1985)
Terzija, V.V., Djurić, M.B., Kovac̆ević, B.D.: Voltage phasor and local system frequency estimation using Newton type algorithm. IEEE Transactions on Power Delivery 9, 1368–1374 (1994)
Terzija, V.V., Djurić, M.B., Kovac̆ević, B.D.: A new self-tuning algorithm for the frequency estimation of distorted signals. IEEE Transactions on Power Delivery 10, 1779–1785 (1995)
Sidhu, T.S., Sachdev, M.S.: An iterative technique for fast and accurate measurement of power system frequency. IEEE Transactions on Power Delivery 13, 109–115 (1998)
Hart, D., et al.: A new frequency tracking and phasor estimation algorithm for generator protection. IEEE Transactions on Power Delivery 12, 1064–1073 (1997)
Benmouyal, G.: An adaptive sampling interval generator for digital relaying. IEEE Transactions on Power Delivery 4, 1602–1609 (1989)
Akke, M.: Frequency estimation by demodulation of two complex signals. IEEE Transactions on Power Delivery 12, 157–163 (1997)
Jordaan, J.A., van Wyk, M.A.: Nonparametric Time-Varying Phasor Estimation using Non-Quadratic Criterium. In: The Sixth IASTED International Conference on Modelling, Simulation, and Optimization, Gaborone, Botswana (2006)
Gorry, P.A.: General Least-Squares Smoothing and Differentiation by the Convolution (Savitzky-Golay) Method. Analytical Chemistry 62, 570–573 (1990)
Bialkowski, S.E.: Generalized Digital Smoothing Filters Made Easy by Matrix Calculations. Analytical Chemistry 61, 1308–1310 (1989)
Pires, R.C., Costa, A.S., Mili, L.: Iteratively Reweighted Least-Squares State Estimation Through Givens Rotations. IEEE Transactions on Power Systems 14, 1499–1506 (1999)
Bishop, C.M.: Neural Networks for Pattern Recognition, 1st edn. Clarendon Press, Oxford (1997)
Multi-Layer Perceptron (MLP), Neural Networks Lectures 5+6 (2007), http://www.cogs.susx.ac.uk/users/andrewop/Courses/NN/NNs5_6_MLP.ppt
Mathworks: MATLAB Documentation - Neural Network Toolbox. Version 6.5.0.180913a Release 13 edn. Mathworks Inc., Natick, MA (2002)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Jordaan, J., van Wyk, A., van Wyk, B. (2008). Nonparametric Time-Varying Phasor Estimation Using Neural Networks. In: Ishikawa, M., Doya, K., Miyamoto, H., Yamakawa, T. (eds) Neural Information Processing. ICONIP 2007. Lecture Notes in Computer Science, vol 4985. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69162-4_72
Download citation
DOI: https://doi.org/10.1007/978-3-540-69162-4_72
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-69159-4
Online ISBN: 978-3-540-69162-4
eBook Packages: Computer ScienceComputer Science (R0)