Power quality assessment using an adaptive neural network
- Regional Engineering Coll., Rourkela (India). Dept. of Electrical Engineering
- Virginia Polytechnic Inst. and State Univ., Blacksburg, VA (United States)
The paper presents an adaptive neural network approach for the estimation of harmonic components of a power system and the power quality. The neural estimator is based on the use of an adaptive perceptron consisting of a linear adaptive neuron called Adaline. The learning parameters in the proposed algorithm are adjusted to force the error between the actual and desired outputs to satisfy a stable difference error equation. The estimator tracks the Fourier coefficients of the signal data corrupted with noise and decaying dc components very accurately. Adaptive tracking of harmonic components of a power system can easily be done using this algorithm. Several numerical tests have been conducted for the adaptive estimation of harmonic components, total harmonic distortion and power quality of power system signals mixed with noise and decaying dc components.
- OSTI ID:
- 474552
- Report Number(s):
- CONF-9601119--; ISBN 0-7803-2795-0
- Country of Publication:
- United States
- Language:
- English
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