Keywords
artificial neural networks (ANNs)
harmonics
measurements
Abstract
The importance of the electric power quality (PQ) demands new methodologies and measurement tools in the power industry for the analysis and measurement of the basic electric magnitudes necessary. This paper presents a new measurement procedure based on neural networks for the estimation of harmonic amplitudes of current/voltage and respective harmonic powers. The measurement scheme is built with two neural network modules. The first module is an adaptive linear neuron (ADALINE) that is the kernel part of estimation of complex harmonic coefficients of the current/voltage. The second module is feedforward neural network that obtains the harmonic active/reactive powers. In order to perform digital simulation the Feedforward and Adaline neural network tools were developed in LabVIEW. This measurement algorithm was tested for the practical cases and found to be robust, computationally fast and efficient.
References
Arrillaga, J., Watson, N.R., and Chen, S. (2000), Power System Quality Assessment, Wiley, New York.
Steven Liu (1998), An adaptive kalman filter for dynamic estimation of harmonic signals, International Conference on Harmonics and Qualio of Power ICHQP '98, jointly organized by IEEEPES and NTUA,Athens, Greece, pp. 636-640. October 14-16.
Cichocki, A. and Lobos, T. (1994), Artificial neural networks for real-time estimation of basic waveforms of voltages and currents, IEEE Transaction on Power Systems, Vol. 9, No.2, pp. 612-618.
Dash, P.K., Panda, S.K., Mishra, B., and Swain, D.P. (1997), Fast Estimation of Voltage and Current Phasors In Powers Networks Using An Adaptive Neural Network, IEEE Transaction on Power System, Vol. 12, No. 4, pp. 1494-1499.
Lai, L.L., Tse, C.T., Chan, W.L., and So, A.T.P. (1999), Real-time frequency and harmonic evaluation using artificial neural networks, IEEE Transaction on Power Delivery, Vol. 14, No. 1, pp. 52-59.
Elmitwally, A., Abdelkader, S., and El-Kateb, M. (2000), Neural network controlled threephase four-wire shunt active power filter, Proceedings of Instrumention and Electctrical Engineering.-Generation, Transmission and Distribution, Vol. 147, No. 2, pp. 87-92.
Vazquez, J.R. and Salmeron, P.R. (2000), Three-phase active power filter control using neural networks, in Proc. IEEE Melecon, Vol. III, Chyprus, pp. 924-927.
Widrow, B. and Lehr, M. (1990), 30 years of Adaptive Neural Networks: Perceptron Madaline and Backpropagation, Proceedings IEEE, Vo1. 78, No. 9, pp. 1415-1442.