|Synchrophasor Data Event Detection using Unsupervised Wavelet Convolutional Autoencoders
Timely and accurate detection of events affecting the stability and reliability of power transmission systems is crucial for safe grid operation. This paper presents an efficient unsupervised machine-learning algorithm for event detection using a combination of discrete wavelet transform (DWT) and convolutional autoencoders (CAE) with synchrophasor phasor measurements. These measurements are collected from a hardware-in-the-loop testbed setup equipped with a digital real-time simulator. Using DWT, the detail coefficients of measurements are obtained.
|Year of Publication
2023 IEEE International Conference on Smart Computing (SMARTCOMP),
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