Karthik Thirumala | National Institute of Technology, Tiruchirappalli (original) (raw)

Conference Presentations by Karthik Thirumala

Generator is an important component of power system which plays a vital role in the whole system ... more Generator is an important component of power system which plays a vital role in the whole system for security and stability. The conventional protection systems will not detect inter turn faults. Longitudinal differential protection detects only inter phase and ground faults. Some large capacity generators are provided with split phase windings to enable transverse differential relay to detect inter turn faults. But this system cannot be retrofit to existing generators. The inter-turn fault protection for stator windings of generators is an important and effective measure to ensure the safe operation of the generator because the inter turn fault may finally lead to ground fault. Therefore, early detection of inter-turn faults would eliminate subsequent damage to adjacent coils and stator core, reducing repair cost and generator outage time. The new Criterion discussed in this paper for detection of inter turn fault is based on the fact that the inter turn fault causes unbalance in t...

2016 National Power Systems Conference (NPSC)

2016 IEEE International Conference on Power System Technology (POWERCON)

This paper proposes a generalized empirical wavelet transform (GEWT) for the recognition of singl... more This paper proposes a generalized empirical wavelet transform (GEWT) for the recognition of single and combined power quality (PQ) disturbances. The FFT-based frequency estimation is adaptive, requires no prior information and is also capable to diagnose all the PQ disturbances. The improved spectral segmentation followed by an adaptive filter design accurately extracts the fundamental frequency component, thereby enabling the extraction of informative features. Thus, the proposed approach combines the GEWT and a simple rule-based decision tree (DT) for accurate recognition of most significant PQ disturbances. The DT classifier with five features extracted from the GEWT is refined and finally tested on 1200 simulated as well as three real disturbance signals. The proposed scheme is found to be computationally efficient and performs satisfactorily with a good classification accuracy.

This paper proposes a new tunable-Q wavelet transform (TQWT) based feature extraction for classif... more This paper proposes a new tunable-Q wavelet transform (TQWT) based feature extraction for classification of power quality (PQ) disturbances. The filters are designed to extract the fundamental frequency component from the complete voltage/current signal. This is achieved by tuning the Q-factor (Q) and redundancy (r) of the wavelet by primarily investigating the presence of interharmonics near the fundamental frequency. To test the effectiveness of the proposed scheme, the system is verified with noise-added disturbance signals generated in MATLAB and finally on some practical signals. The proposed methodology is computationally efficient as the traditional PQ analyzers.

This paper presents an application of Empirical Wavelet Transform (EWT) to the power signals for ... more This paper presents an application of Empirical Wavelet Transform (EWT) to the power signals for estimation of Power quality Indices (PQIs). This technique first estimates the frequency components present in the distorted signal, computes the boundaries and extracts mono components based on the boundaries computed. Several stationary and non-stationary signals have been analyzed to show the effectiveness of this technique. The PQIs obtained with the proposed technique has been compared with Discrete Wavelet Technique (DWT) and the proposed technique is found to be effective and superior over DWT. The results confirm that the EWT efficiently extracts the mono-component signals from the time varying distorted signal and hence this technique would be suitable for real time PQ indices estimation.

Papers by Karthik Thirumala

Electric Power Systems Research, Feb 1, 2017

Tracking of instantaneous power quality (PQ) indices is very essential for better characterizatio... more Tracking of instantaneous power quality (PQ) indices is very essential for better characterization of the time-varying voltage and current signals. This paper presents the estimation of time-varying PQ indices for accurate interpretation of disturbances using a generalized empirical wavelet transform (GEWT). This approach is based on adaptive segmentation of Fourier spectrum and followed by an appropriate filter design to extract the individual frequency components. The main emphasis of this work is to estimate the actual frequencies present in the signal by overcoming the problem of spectral leakage. A preliminary investigation of time domain amplitude variation of the signal helps in realizing the presence of low-frequency interharmonics and thereby permitting to extract the fundamental frequency component perfectly. Hence, the GEWT is employed to assess successfully all sorts of power signals having disturbances such as voltage fluctuation, sag, swell, interruption, transients, harmonics, and interharmonics. The robustness and applicability of the GEWT for PQ analysis have been verified by analyzing several distorted signals generated using PSCAD, recorded waveforms available in IEEE database and a few real signals. Finally, the estimated GEWT-based time-varying single phase PQ indices are compared with the indices obtained from IEC defined fast Fourier transform (FFT) and fast S-transform (FST).

2022 IEEE International Conference on Power Electronics, Smart Grid, and Renewable Energy (PESGRE), Jan 2, 2022

The impedance source inverter has features of single-stage conversion, boosting capability, and s... more The impedance source inverter has features of single-stage conversion, boosting capability, and shoot-through (ST) immunity. Hence, they are widely used and outperform the conventional voltage and current source inverters. It is a known fact that a leakage current flows in the network due to a common ground issue. This poses an electrical safety risk in solar photovoltaic systems. This paper proposes a common ground-based high gain basic switched boost inverter (SBI) topology. The topology includes a common ground from the source to the load that leads to leakage current elimination. It can buck/boost the input voltage to the desired voltage level. The detailed functioning of the proposed configuration and steady-state analysis are presented. The MATLAB Simulink software is used to assess the proposed SBI operation and analyze results. To validate the performance of the proposed SBI, the simulation results are compared with the values derived from the mathematical formulation. The results elucidate that the proposed inverter configuration has higher gain, Modulation index (MI), and less switching stress across switches as compared to a basic SBI.

Electrical Engineering, Jun 17, 2022

International Journal of Emerging Electric Power Systems, Mar 25, 2021

In active distribution networks, it is a challenging task for the utility and system operators to... more In active distribution networks, it is a challenging task for the utility and system operators to identify and analyze the power quality (PQ) disturbance and its cause. Likewise, the consumers are curious about the quality of power supply being provided and the economic impacts of low PQ. Thus, continuous monitoring of the overall quality of the power at the consumer end has become a significant concern in distribution networks. This paper presents a new composite power quality index (CPQI) for low-voltage distribution networks. The CPQI is formulated as a weighted average of five basic parameters, namely voltage level, current harmonic quality, voltage harmonic quality, power factor, and system frequency. The main emphasis is on quantifying the overall quality of the power supply under different PQ disturbance conditions. The CPQI estimate helps in a preliminary investigation of tracking the low PQ location and its source. The proposed CPQI is evaluated on a variety of simulated signals obtained from a CIGRE low-voltage microgrid network. Furthermore, the formulated CPQI is investigated on a LabVIEW-based virtual instrumentation platform with LED loads. It is interpreted from the results that the proposed CPQI is able to evaluate the overall PQ at a load terminal with diverse load conditions subjected to different power quality disturbances.

Energies, Sep 27, 2021

This article is an open access article distributed under the terms and conditions of the Creative... more This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY

Energy conversion and economics, Mar 31, 2023

Renewable energy sources (RES) and electric vehicles (EVs) pose ‘energy‐risk’ in peer energy comm... more Renewable energy sources (RES) and electric vehicles (EVs) pose ‘energy‐risk’ in peer energy commitments due to their temporal and spatial uncertainties. Thus, optimistic commitments in the peer‐to‐peer transactive energy market (P2P TEM) are improbable. This paper proposes a two‐stage master–slave portfolio optimization approach for combining energy‐risk of RES and EVs, and welfare‐risk of peers, in building clean energy portfolios. The master portfolio (MP) refers to the shares of renewable and EVs in P2P market settlement, whereas the slave portfolio (SP) gives the wind‐solar mix within renewables. Here, Rachev Ratio (RR), an index used in financial portfolio selection for tail‐risk management, is adapted and combined with Markowitz Efficient Frontier (EF) to find the optimal slave portfolio. Both the extreme tails are optimized, encouraging energy outputs far above forecast and discouraging those far below forecast. The master portfolio is obtained by maximizing the sum of the average welfare of the peers at the best (right) and worst (left) tails of the welfare distribution curve using Stochastic Weight Trade‐off Particle Swarm Optimization (SWT‐PSO). The proposed portfolio selection approach is better in terms of increased expected energy output, improved utilization of RES and EVs, and better collective peer welfare.

2022 IEEE 19th India Council International Conference (INDICON), Nov 24, 2022

Energy Economics, Oct 1, 2022

IEEE Transactions on Power Delivery, Feb 1, 2015

ABSTRACT Application of an empirical wavelet transform (EWT)-based time-frequency technique is pr... more ABSTRACT Application of an empirical wavelet transform (EWT)-based time-frequency technique is proposed in this paper for the estimation of power-quality indices (PQIs). This technique first estimates the frequency components present in the distorted signal, computes the boundaries, and then filtering is done based on the boundaries computed. This technique is effective and offers many advantages over other techniques because the scaling function and wavelets adapt themselves according to the information contained in the signal and no prior information regarding the signal is required. Besides this, the advantages of the discrete wavelet transform (DWT), wavelet packet transform (WPT), short-time Fourier transform (STFT), windowing techniques, and filter bank techniques also hold. Simulated and experimental test signals with power-quality disturbances have been analyzed and the effectiveness of this technique has been shown by comparing the PQIs estimated by using the proposed method with those obtained using the DWT and WPT. The results confirm that the EWT efficiently extracts the mono component signals from the actual distorted signal and thereby accurately estimates the PQIs.

IEEE Transactions on Smart Grid, Jul 1, 2018

A new automated recognition approach based on tunable-Q wavelet transform (TQWT) and a dual multi... more A new automated recognition approach based on tunable-Q wavelet transform (TQWT) and a dual multiclass support vector machines (MSVM) has been proposed for detection of power quality disturbances. The proposed approach first investigates the presence of low-frequency interharmonics and then tunes the wavelet for decomposition of signal into fundamental and harmonic components. The tuning of Q-factor and redundancy makes the filter design to accurately extract the fundamental frequency component from a distorted input signal. Then, a unique set of features, which clearly reveal the characteristics of disturbances, are extracted. The power quality disturbances are broadly categorized into two groups based on the pre-obtained information of low-frequency interharmonics. Therefore, multiple disturbances are recognized by employing a dual MSVM, one for each group. Results demonstrate the applicability, strength, and accuracy of the proposed approach for classification of single and combined disturbances under different noisy conditions. Moreover, to illustrate the prominence of the features extracted from TQWT, two more classifiers based on decision tree and feedforward neural network have been employed for classification of power quality disturbances.

IET Energy Systems Integration

In this article, the stability of a synchronous motor generator pair (SMGP) used for improving th... more In this article, the stability of a synchronous motor generator pair (SMGP) used for improving the inertia of grid‐connected renewable energy systems is investigated. The useful operational regime for different sets of system parameters is identified, such as electromagnetic torque, damping co‐efficient, and inertia by employing bifurcation analysis to detect stability boundaries. For the first time, the existence of bi‐stable regimes for the SMGP with non‐linear stability analysis is revealed. The authors' analysis unravels the possibility of the system getting transited to unsafe operation even when the system is in the linearly stable region. The existence of the bistable regime indicates the possibility of the system becoming unstable even when the eigenvalues are in the left half plane. The authors also identify globally stable and globally unstable regimes in the parameter space. The safe operating range of inertia and damping co‐efficient values helps in the design of a s...

Energy Conversion and Economics

2022 IEEE 19th India Council International Conference (INDICON)

2016 National Power Systems Conference (NPSC)

2016 IEEE International Conference on Power System Technology (POWERCON)

Electric Power Systems Research, Feb 1, 2017

2022 IEEE International Conference on Power Electronics, Smart Grid, and Renewable Energy (PESGRE), Jan 2, 2022

Electrical Engineering, Jun 17, 2022

International Journal of Emerging Electric Power Systems, Mar 25, 2021

Energies, Sep 27, 2021

Energy conversion and economics, Mar 31, 2023

2022 IEEE 19th India Council International Conference (INDICON), Nov 24, 2022

Energy Economics, Oct 1, 2022

IEEE Transactions on Power Delivery, Feb 1, 2015

IEEE Transactions on Smart Grid, Jul 1, 2018

IET Energy Systems Integration

Energy Conversion and Economics

2022 IEEE 19th India Council International Conference (INDICON)

2022 IEEE International Conference on Power Electronics, Smart Grid, and Renewable Energy (PESGRE), 2022

2021 IEEE 8th Uttar Pradesh Section International Conference on Electrical, Electronics and Computer Engineering (UPCON)

2020 19th International Conference on Harmonics and Quality of Power (ICHQP), 2020

This paper develops a knowledge-based neural network (KBNN) for the classification of power quali... more This paper develops a knowledge-based neural network (KBNN) for the classification of power quality (PQ) disturbances. Initially, the tunable-q wavelet transform (TQWT) is employed for the extraction of the 50 Hz component from a voltage signal with any sort of disturbance. This is achieved by varying the quality factor of wavelet according to the signal information. The KBNN is a combined model of neural network and rule-based approach. This paper explores the potential of the KBNN for classification of the most common power quality disturbances. The efficacy of the KBNN approach is evaluated on a wide range of time-varying signals with noise, fundamental frequency deviation, and variation in signal parameters. The performance analysis elucidates the efficiency and robustness of the proposed approach using KBNN classifier for classification of the normal and eight PQ disturbances.

2019 National Power Electronics Conference (NPEC), 2019

This paper develops a LabVIEW based instrumentation for the classification of power quality (PQ) ... more This paper develops a LabVIEW based instrumentation for the classification of power quality (PQ) disturbances. Initially, the wavelet packet transform (WPT) is employed for the extraction of the 50 Hz component and decomposition of a distorted voltage signal into uniform bands. Then seven essential features are extracted from the decomposed signal coefficients. The knowledge-based neural network (KBNN) is a combined model of neural network and rule-based approach. This paper explores the potential of the KBNN for the classification of the most common power quality disturbances. The efficacy of the KBNN approach is evaluated on a wide range of time-varying signals with noise, fundamental frequency deviation, and variation in signal parameters. The implementation in LabVIEW and experimental results elucidate the efficiency and robustness of the proposed PQ disturbance classifier using KBNN.

Current drawn by a Personal Computer measured using a Hall effect based Current sensor. The signa... more Current drawn by a Personal Computer measured using a Hall effect based Current sensor. The signal is recorded by a Data acquisition system at a sampling rate of 10 kHz. The sensitivity of the sensor is 0.1V/1A, so the amplitude (in volts) should be multiplied by 10 to attain the exact current amplitude.

Current drawn by a Laptop measured using a Hall effect based Current sensor. The signal is record... more Current drawn by a Laptop measured using a Hall effect based Current sensor. The signal is recorded by a Data acquisition system at a sampling rate of 10 kHz. The sensitivity of the sensor is 0.1V/1A, so the amplitude (in volts) should be multiplied by 10 to attain the exact current.