Power Quality Disturbance Classification Using Adaptive Linear Neural Network (ADALINE) and Feed Forward Neural Network (FFNN)
نویسندگان
چکیده
Abstract: This paper presents a dual neural network based technique for detecting and classifying the power quality disturbances. In the proposed method, Adaptive Linear Neural Network is used to extract the rms voltage for harmonics and Interharmonics estimations. With the help of these indices, PQ disturbances such as Sag, Swell, Outages are detected and classified, Harmonics and Interharmonics alongwith horizontal and vertical histograms for a specified voltage waveform and Feed Forward Neural Networks are used for pattern recognition in order to classify Spikes, Notches, Flicker and Oscillatory transients. Synthetic disturbance waveforms are generated using the MATLAB parametric equations.
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