Conference Papers

Permanent URI for this collectionhttps://idr.nitk.ac.in/handle/123456789/28506

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Author: search.filters.author.Gaonkar, D.N.Subject: search.filters.subject.Transfer Learning

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    A Novel Islanding Detection Method Based on Transfer Learning Technique Using VGG16 Network
    (Institute of Electrical and Electronics Engineers Inc., 2019) Manikonda, S.K.G.; Gaonkar, D.N.
    The escalating need for energy in the recent times is unprecedented, which is driving the penetration of renewable energy sources in distribution system in a big way. The growing number of renewable sources in a system has made the control, operation and protection of the system very complex. Among others, one of the key issues in seamless interconnection of renewable energy sources to a system is islanding. This paper proposes a new and efficient islanding detection method that employs transfer learning based technique. The results show that the proposed method can successfully classify islanding events with a good accuracy. © 2019 IEEE.
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    Power Quality Event Classification Using Transfer Learning on Images
    (Institute of Electrical and Electronics Engineers Inc., 2019) Manikonda, S.K.G.; Santhosh, J.; Sreckala, S.P.K.; Gangwani, S.; Gaonkar, D.N.
    Given the ever-increasing complexity of the electrical grid system, power quality events have been surging in frequency with each passing day. Due to their potential to cause massive losses for a wide variety of customers, it is crucial that such events are detected and classified immediately for appropriate response. in this paper, a novel approach has been developed wherein Transfer Learning techniques have been employed to classify power quality events using image classification. More specifically, the VGG16 model has been utilized to classify five distinct power quality issues by using scalograms as input images. 489 scalograms were generated via feature extraction using wavelet transforms. The VGG16 model has then been trained and tested using the same. Thereafter, the model performance has been evaluated, and the results have been discussed. © 2019 IEEE.