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.
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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)
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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
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DOI: https://doi.org/10.1007/978-3-540-69162-4_72
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