Conference Papers

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Author: search.filters.author.Krishnan, G.Has files: No

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    Intentional islanding operations of distributed generation systems with a load shedding algorithm
    (2012) Krishnan, G.; Gaonkar, D.N.
    Intentional islanding is a condition in which a distributed generation source continues to supply power to the local loads during a catastrophic utility failure. With a properly coordinated and sophisticated control scheme, islanding can be a possible solution, to ensure reliable power to the critical loads. This paper analyzes a control scheme for intentional islanding operation of an inverter based DG system. In grid connected mode, the interface control is designed to provide constant active and reactive power to the load. When grid is disconnected, an islanding detection algorithm will transfer the inverter into voltage control mode. The mismatch between load and generation is removed by implementing a load shedding algorithm. This paper also investigates the performance and the Non Detection Zones of the islanding detection scheme with different interface controllers. © 2012 IEEE.
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    Control of grid connected and islanding operations of distributed generation systems with seamless transfer between modes
    (Institute of Electrical and Electronics Engineers Inc., 2013) Krishnan, G.; Gaonkar, D.N.
    Intentional islanding of distributed generation systems requires seamless transition of power between grid connected and islanding modes, ensuring little or no disruption to the local loads. This paper conducts a detail study regarding the factors affecting seamless transition. A control scheme for grid connected and islanding mode of operation with a passive islanding detection algorithm, synchronization algorithm and recloser algorithm is developed. Simulation studies are carried out to evaluate the performance of the controller in grid connected and islanding modes and the possibility of seamless transition between both modes is verified. © 2013 IEEE.
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    Performance evaluation of a new hybrid islanding detection method for a wind based DG system
    (IEEE Computer Society, 2013) Krishnan, G.; Gaonkar, D.N.
    In this paper the performance of a new hybrid islanding detection method is studied considering a synchronous generator based wind power system. The proposed hybrid islanding detection algorithm combines an adaptive reactive power perturbation based active method with a novel passive algorithm. The passive algorithm considered in this study relies on some special transient response characteristics of the islanded system for providing an islanding suspicion signal. On receiving the suspicion signal the active counterpart injects minimum reactive power based on the resonant frequency to detect the islanding condition. The performance of the developed method is analyzed with various case studies conducted in MATLAB/SIMPOWERSYSTEMS environment. © 2013 IEEE.
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    Voice activity detection from the breathing pattern of the speaker
    (Institute of Electrical and Electronics Engineers Inc., 2018) Ramakrishnan, A.G.; Krishnan, G.; Srivathsan, S.
    In this paper, we propose a method to perform voice activity detection using only the breathing signal of a speaker. Human breathing and speech production go hand in hand. Normal respiration and respiration during speech have a different profile. The former is generally symmetric as compared to an asymmetric profile in the case of respiration during speech. Impedance pneumography provides a mechanism to capture chest expansions and compressions due to breathing. We have recorded the breathing signal along with the speech audio for 44 subjects while they were speaking and quiet. We have classified cycles of breathing into two classes, namely during speech and normal, using the cycle-synchronous discrete cosine transform coefficients of the breathing signal with different classifiers. The best accuracy of 96.4% is obtained using the k-nearest neighbor classifier. From the classified breathing cycles, we determine the intervals when a subject is quiet and when he is speaking. We use the corresponding timeframes on the simultaneously recorded audio and achieve a good accuracy in voice activity detection. Compared to the earlier reported time resolution of 30 sec, we obtain a decision for every breathing cycle, which works out to an average resolution of about 3 sec. © 2017 IEEE.