Faculty Publications
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Item A New Islanding Detection Method Using Transfer Learning Technique(IEEE Computer Society help@computer.org, 2018) Manikonda, S.K.G.; Gaonkar, D.N.The increasing need for energy in the recent times is unprecedented, which is driving the penetration of renewable sources in distribution system in a big way. The increasing number of renewable sources in a system has made the operation, control and protection of the system very complex. One of the key issues in seamless interconnection of renewable energy sources to a system is islanding. This paper proposes a new method to detect islanding in an efficient way by employing transfer learning based technique for image classification. The results show that the proposed method can successfully classify islanding events with a good accuracy. © 2018 IEEE.Item 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.Item STFT Filter Bank Based Islanding Detection Technique(Institute of Electrical and Electronics Engineers Inc., 2023) Pinto, J.A.; Vittal, K.P.Depleting coal reserves and increasing carbon emissions have propelled the use of renewable energy sources to generate electricity. Microgrids have been recognised as one of the solutions to provide continuity of power to critical loads even during natural disasters, as they can connect or disconnect from the main grid. The presence or absence of the grid is critical to the operation of the various inverter-based resources and load management in the Microgrid. Various active and passive methods have been proposed by researchers to detect islanding. This paper focuses on detecting the islanding condition based on the filter bank approach of Short Time Fourier Transform. The voltage at the interface of distributed generation was sensed and the amplitude of a particular frequency component was estimated using the filter bank approach. The estimated amplitude was then checked against a set threshold to detect islanding. The proposed islanding detection technique was tested and was found effective on a sample Microgrid for conditions like normal operation, operation during faults and operation during turning ON and OFF loads and sources. © 2023 IEEE.