Voltage Harmonics and Transient Disturbances Detection and Classification using GoogLeNet Model of Deep Learning

Voltage harmonics and transients are most prominent disturbances affecting the power quality in modern power system. These are caused majorly due to significant penetration of electronic based machineries. Presently, an easy, precise and universal method to detect and classify the mentioned disturbances does not exist. Therefore, this paper employed a robust and efficient use of GoogLeNet deep learning model for classification of voltage harmonic and transient power quality disturbances. In this work, images of voltage harmonics and transient disturbances are synthesized MATLAB environment. These images are further used for training, validation and testing of GoogLeNet model. From the results, it can be observed that the mentioned approach is capable of classifying multiple disturbances affecting the power quality. Further, the robustness of mentioned approach is established by performing the classification in presence of distinct noise conditions.