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Gold Medal for M.Tech studies awarded by Jagannath University Jaipur, India, in year 2013
Jagannath University Jaipur, India
Received from IIT Jodhpur, India for best PhD thesis
Indian Institute of Technology Jodhpur, India
Dr. Om Prakash Mahela has received the Ph.D. (C.V. Raman Gold Medal) degree in Power Systems from the Indian Institute of Technology Jodhpur (IITJ), India, in 2018. He received an M.Tech. (Gold Medalist) degree in 2013 from JNU Jaipur, India, and B.E. (University Rank Certificate) in 2002 from CTAE Udaipur, India, both in Electrical Engineering. Presently, he is an Assistant Engineer with the Power System Planning Division, RVPN, India. Research Interest: Power Quality, Power System Protection, Grid integration of RE.
The impact of fault circumstances on distribution grid parameters in the presence of wind power generation is explored in this research. A protection algorithm (PA) is also proposed for detecting faulty events by using the proposed wind fault index, which is computed by analysing current signals using the Wigner distribution function and the Stockwell transform (ST). The sort of fault is determined by the number of faulty phases found. The zero sequence currents introduced to identify the ground’s involvement in a fault event are analysed to calculate a wind ground fault index. Single phase to the ground, double phase to the ground, double phase, three-phases, and three phases to the ground faults are all investigated fault events. It has been determined that PA outperforms discrete Wavelet Transform and ST-based approaches in terms of fault estimation time and noise effect. The study was conducted on the IEEE-13 bus test feeder, which was connected to wind power plants (WPPs).
Om Prakash Mahela; Vikram Singh Bhati; Gulhasan Ahmad; Baseem Khan; P. Sanjeevikumar; Akhil Ranjan Garg; Rajendra Mahla. A protection scheme for distribution utility grid with wind energy penetration. Computers & Electrical Engineering 2021, 94, 107324 .
AMA StyleOm Prakash Mahela, Vikram Singh Bhati, Gulhasan Ahmad, Baseem Khan, P. Sanjeevikumar, Akhil Ranjan Garg, Rajendra Mahla. A protection scheme for distribution utility grid with wind energy penetration. Computers & Electrical Engineering. 2021; 94 ():107324.
Chicago/Turabian StyleOm Prakash Mahela; Vikram Singh Bhati; Gulhasan Ahmad; Baseem Khan; P. Sanjeevikumar; Akhil Ranjan Garg; Rajendra Mahla. 2021. "A protection scheme for distribution utility grid with wind energy penetration." Computers & Electrical Engineering 94, no. : 107324.
Renewable energy (RE) generation levels are increasing in modern power systems at a fast rate due to their advantages of clean and non-exhaustible nature of energy. However, this type of generation creates technical challenges in terms of operation and control due to uncertain and un-predictable nature of generation. Islanding is an operational scenario where there is a loss of grid and RE generators continue to feed power to the local load. This has harmful effects on the RE generators and operating personal. Hence, it is expected that islanding scenario is identified in minimum time and RE generators are disconnected within
Nagendra Kumar Swarnkar; Om Prakash Mahela; Baseem Khan; Mahendra Lalwani. Identification of Islanding Events in Utility Grid with Renewable Energy Penetration Using Current Based Passive Method. IEEE Access 2021, 9, 1 -1.
AMA StyleNagendra Kumar Swarnkar, Om Prakash Mahela, Baseem Khan, Mahendra Lalwani. Identification of Islanding Events in Utility Grid with Renewable Energy Penetration Using Current Based Passive Method. IEEE Access. 2021; 9 ():1-1.
Chicago/Turabian StyleNagendra Kumar Swarnkar; Om Prakash Mahela; Baseem Khan; Mahendra Lalwani. 2021. "Identification of Islanding Events in Utility Grid with Renewable Energy Penetration Using Current Based Passive Method." IEEE Access 9, no. : 1-1.
This paper introduced an advanced algorithm making hybrid use of Stockwell transform (ST), Hilbert transform (HT) and Alienation coefficient (ACF) for identification, classification and to locate faulty events on transmission line. Signals of Current are processed by application of ST, HT and ACF for computing S-index, H-index and A-index, respectively. These indices are multiplied element by element to compute proposed fault index (FI). A threshold magnitude is decided after testing the algorithm during different fault scenarios and faulty events are recognized when FI exceeds this threshold magnitude. Faults are categorized by identifying the number of phases which are faulty in nature and a ground fault index (GFI). GFI is designed by processing the zero sequence current using ST and used to identify involvement of ground during fault event. A mathematical formulation is framed to estimate location of faults on transmission line. Fault location has been estimated with a mean error less than 1%. Investigated faults include phase to ground (PGF), double phase (PPF), double phase to ground (PPGF) and three phase to ground (TPGF). Algorithm is found effective for faulty scenario such as fault impedance variations, fault incidence angle (FIA) variations, reverse power flow, effect of line loading, effect of noise, transient faults, off-nominal frequency, and presence of harmonic components. Algorithm is also effective for discriminating switching transients from faulty conditions. Effective performance of the algorithm is established by comparing with fault detection and classification approach based on alienation coefficients, discrete Fourier transform (DFT) and time-frequency approach. Study is performed on a two terminal transmission line in MATLAB/Simulink environment. Effectiveness of the algorithm is also established on a real time transmission grid of Rajasthan state of India.
Abhishek Gupta; Ramesh Kumar Pachar; Baseem Khan; Om Prakash Mahela; Sanjeevikumar Padmanaban; Fellow Iet. A multivariable transmission line protection scheme using signal processing techniques. IET Generation, Transmission & Distribution 2021, 1 .
AMA StyleAbhishek Gupta, Ramesh Kumar Pachar, Baseem Khan, Om Prakash Mahela, Sanjeevikumar Padmanaban, Fellow Iet. A multivariable transmission line protection scheme using signal processing techniques. IET Generation, Transmission & Distribution. 2021; ():1.
Chicago/Turabian StyleAbhishek Gupta; Ramesh Kumar Pachar; Baseem Khan; Om Prakash Mahela; Sanjeevikumar Padmanaban; Fellow Iet. 2021. "A multivariable transmission line protection scheme using signal processing techniques." IET Generation, Transmission & Distribution , no. : 1.
The presented work in this paper deals with various step sizes used in incremental conductance (INC) related to the maximum power point tracking (MPPT) technique. In the solar photovoltaic system, the variable step size selection method for INC is proposed and compared. The MATLAB/Simulink and hardware setup are used for assessing and analyzing step size methods. The variable step size (DVS), fixed step size (DFS) are comprehensively studied and compared. This DVS method is having a lower ON delay time
Ankur Kumar Gupta; Rupendra Kumar Pachauri; Tanmoy Maity; Yogesh K. Chauhan; Om Prakash Mahela; Baseem Khan; Pankaj Kumar Gupta. Effect of Various Incremental Conductance MPPT Methods on the Charging of Battery Load Feed by Solar Panel. IEEE Access 2021, 9, 1 -1.
AMA StyleAnkur Kumar Gupta, Rupendra Kumar Pachauri, Tanmoy Maity, Yogesh K. Chauhan, Om Prakash Mahela, Baseem Khan, Pankaj Kumar Gupta. Effect of Various Incremental Conductance MPPT Methods on the Charging of Battery Load Feed by Solar Panel. IEEE Access. 2021; 9 ():1-1.
Chicago/Turabian StyleAnkur Kumar Gupta; Rupendra Kumar Pachauri; Tanmoy Maity; Yogesh K. Chauhan; Om Prakash Mahela; Baseem Khan; Pankaj Kumar Gupta. 2021. "Effect of Various Incremental Conductance MPPT Methods on the Charging of Battery Load Feed by Solar Panel." IEEE Access 9, no. : 1-1.
This paper proposes a security algorithm based on thewavelet-alienation-neural technique for detecting, classifying, and locating faults on Thyristor-Controlled Series compensator (TCSC) compensated lines. A fault index has been calculated using wavelet transform and alienation coefficients with post-fault current signals measured/ sampled for quarter cycle time at both near and far end buses for fault detection and classification. The location of the fault is predicted using an Artificial Neural Network (ANN) after the fault has been diagnosed. Approximate coefficients (quarter cycle time) of both voltage and current signals, from both buses, were provided as input to ANN. Various case studies, such as variations in TCSC position, fault location, sampling frequency, power flow path, incipient angle of fault, TCSC control strategy, fault resistance, and load switching conditions, have verified the robustness of the proposed safety system.
Bhuvnesh Rathore; Amit Gangwar; Om Prakash Mahela; Baseem Khan; Sanjeevikumar padmanaban. A Fast Protection Scheme for TCSC Compensated Transmission Line Using Wavelet-Alienation-Neural Technique. 2021, 1 .
AMA StyleBhuvnesh Rathore, Amit Gangwar, Om Prakash Mahela, Baseem Khan, Sanjeevikumar padmanaban. A Fast Protection Scheme for TCSC Compensated Transmission Line Using Wavelet-Alienation-Neural Technique. . 2021; ():1.
Chicago/Turabian StyleBhuvnesh Rathore; Amit Gangwar; Om Prakash Mahela; Baseem Khan; Sanjeevikumar padmanaban. 2021. "A Fast Protection Scheme for TCSC Compensated Transmission Line Using Wavelet-Alienation-Neural Technique." , no. : 1.
This research work has designed an algorithm to identify islanding events using the current signals in a distribution grid interfaced with renewable energy (RE) sources situated in remote areas. A median-based islanding recognition factor (MIRF) is designed by processing the current signal using Stockwell transform (ST). A current rate of change of islanding recognition factor (CRCIRF) is computed by differentiating the root mean square (RMS) current concerning time. The MIRF and CRCIRF are multiplied element by element to calculate the current-based islanding recognition factor (IRFC) used to recognize islanding events and non-islanding events. Simple decision rules are used to discriminate Islanding events from the faulty and the operational events by comparing peak magnitude of IRFC with pre-set threshold values. This IDM effectively recognizes islanding events in the presence of noise with 10 dB signal-to-noise ratio (SNR) level. The performance of IDM is established on a practical distribution feeder. Developed work is executed in MATLAB/Simulink.
Om Prakash Mahela; Yagya Sharma; Shoyab Ali; Baseem Khan; Sanjeevikumar Padmanaban. Estimation of Islanding Events in Utility Distribution Grid With Renewable Energy Using Current Variations and Stockwell Transform. IEEE Access 2021, 9, 69798 -69813.
AMA StyleOm Prakash Mahela, Yagya Sharma, Shoyab Ali, Baseem Khan, Sanjeevikumar Padmanaban. Estimation of Islanding Events in Utility Distribution Grid With Renewable Energy Using Current Variations and Stockwell Transform. IEEE Access. 2021; 9 ():69798-69813.
Chicago/Turabian StyleOm Prakash Mahela; Yagya Sharma; Shoyab Ali; Baseem Khan; Sanjeevikumar Padmanaban. 2021. "Estimation of Islanding Events in Utility Distribution Grid With Renewable Energy Using Current Variations and Stockwell Transform." IEEE Access 9, no. : 69798-69813.
This paper has introduced an algorithm for the identification of islanding events in the remotely located distribution grid with renewable energy (RE) sources using the voltage signals. Voltage signal is processed using Stockwell transform (ST) to compute the median-based islanding recognition factor (MIRF). The rate of change in the root mean square (RMS) voltage is computed by differentiating the RMS voltage with respect to time to compute the voltage rate of change in islanding recognition factor (VRCIRF). The proposed voltage-based islanding recognition factor (IRFV) is computed by multiplying the MIRF and VRCIRF element to element. The islanding event is discriminated from the faulty and operational events using the simple decision rules using the peak magnitude of IRFV by comparing peak magnitude of IRFV with pre-set threshold values. The proposed islanding detection method (IDM) effectively identified the islanding events in the presence of solar energy, wind energy and simultaneous presence of both wind and solar energy at a fast rate in a time period of less than 0.05 cycles compared to the voltage change rate (ROCOV) and frequency change rate (ROCOF) IDM that detects the islanding event in a time period of 0.25 to 0.5 cycles. This IDM provides a minimum non-detection zone (NDZ). This IDM efficiently discriminated the islanding events from the faulty and switching events. The proposed study is performed on an IEEE-13 bus test system interfaced with renewable energy (RE) generators in a MATLAB/Simulink environment. The performance of the proposed IDM is better compared to methods based on the use of ROCOV, ROCOF and discrete wavelet transform (DWT).
Om Mahela; Yagya Sharma; Shoyab Ali; Baseem Khan; Akhil Garg. Voltage-Based Hybrid Algorithm Using Parameter Variations and Stockwell Transform for Islanding Detection in Utility Grids. Informatics 2021, 8, 21 .
AMA StyleOm Mahela, Yagya Sharma, Shoyab Ali, Baseem Khan, Akhil Garg. Voltage-Based Hybrid Algorithm Using Parameter Variations and Stockwell Transform for Islanding Detection in Utility Grids. Informatics. 2021; 8 (2):21.
Chicago/Turabian StyleOm Mahela; Yagya Sharma; Shoyab Ali; Baseem Khan; Akhil Garg. 2021. "Voltage-Based Hybrid Algorithm Using Parameter Variations and Stockwell Transform for Islanding Detection in Utility Grids." Informatics 8, no. 2: 21.
This paper introduces an algorithm based on wavelet packet supported fast Kurtogram and decision rules for the identification and classification of complex power quality (PQ) disturbances. Features are extracted from the signals using fast Kurtogram, envelope of filtered voltage signal and amplitude spectrum of squared envelop. Proposed algorithm can be implemented for the recognition of the complex PQ disturbances, which include the combination of voltage sag and harmonics, voltage momentary interruption (MI) and oscillatory transient (OT), voltage MI and harmonics, voltage sag and impulsive transient (IT), voltage sag, OT, IT and harmonics. Proposed work has been performed using the MATLAB software. Performance of the algorithm is compared with performance of algorithm supported by discrete wavelet transform (DWT) and fuzzy C-means clustering (FCM).
Rajendra Mahla; Baseem Khan; Om Prakash Mahela; Anup Singh. Recognition of complex and multiple power quality disturbances using wavelet packet-based fast kurtogram and ruled decision tree algorithm. International Journal of Modeling, Simulation, and Scientific Computing 2021, 1 .
AMA StyleRajendra Mahla, Baseem Khan, Om Prakash Mahela, Anup Singh. Recognition of complex and multiple power quality disturbances using wavelet packet-based fast kurtogram and ruled decision tree algorithm. International Journal of Modeling, Simulation, and Scientific Computing. 2021; ():1.
Chicago/Turabian StyleRajendra Mahla; Baseem Khan; Om Prakash Mahela; Anup Singh. 2021. "Recognition of complex and multiple power quality disturbances using wavelet packet-based fast kurtogram and ruled decision tree algorithm." International Journal of Modeling, Simulation, and Scientific Computing , no. : 1.
Fault analysis (detection, classification and location) of transmission network is of great importance in power system. A Wavelet-Alienation-Neural (WAN) technique has been developed for the fault analysis of Unified Power Flow Controller (UPFC) compensated transmission network. The detection and classification of various outages are accomplished by alienation of wavelet based approximate coefficients computed from current signals. The precise location of faults is carried out by an Artificial Neural Network fed from estimated approximate coefficients computed from voltage and current signals of the same quarter cycle. The robustness of the algorithm is proved with the case studies of varying fault locations, sampling frequency, system parameters, effects of noise, fault incipient angle, different control strategies and fault path impedances.
Bhuvnesh Rathore; Om Prakash Mahela; Baseem Khan; Sanjeevikumar Padmanaban. Protection Scheme using Wavelet-Alienation-Neural Technique for UPFC Compensated Transmission Line. IEEE Access 2021, 9, 13737 -13753.
AMA StyleBhuvnesh Rathore, Om Prakash Mahela, Baseem Khan, Sanjeevikumar Padmanaban. Protection Scheme using Wavelet-Alienation-Neural Technique for UPFC Compensated Transmission Line. IEEE Access. 2021; 9 ():13737-13753.
Chicago/Turabian StyleBhuvnesh Rathore; Om Prakash Mahela; Baseem Khan; Sanjeevikumar Padmanaban. 2021. "Protection Scheme using Wavelet-Alienation-Neural Technique for UPFC Compensated Transmission Line." IEEE Access 9, no. : 13737-13753.
Distribution static compensator is based on power electronic devices technology which is utilized to supply rapid changes in active power as well as reactive power of utility grids. This is useful to achieve corrections in power factor, balancing of load, compensation of current and filtering of harmonics. Therefore, proposed work investigates the improvement of the power quality by utilizing the distribution static compensator, which is equipped by battery energy storage system and interfaced to distribution network with solar photo voltaic (PV) energy integration. In the present study, distribution static compensator is controlled using a control strategy based on the synchronous reference frame theory. Customised IEEE‐13 nodes test system incorporating solar PV generation and distribution static compensator, is utilized to perform the harmonic mitigation and power quality analysis. Disturbances of power quality and harmonics have been investigated due to abrupt changes in the insolation of solar radiation, outage of PV plant from grid and synchronization of PV plant to grid. MATLAB/Simulink environment is utilized to perform the study. Effectiveness of a developed approach is validated by comparing results of simulation with results extracted in real time using real time digital simulator. Results indicate that the developed method is more effective for harmonic mitigation and improving power quality of electrical power in distribution network integrated with solar PV generation. Performance of the approach is compared with the performance of methods reported in the literature to establish the suitability of the method for harmonics mitigation and power quality improvement in grid with solar energy.
Om Prakash Mahela; Baseem Khan; H. H. Alhelou; Sudeep Tanwar; Sanjeevikumar Padmanaban. Harmonic mitigation and power quality improvement in utility grid with solar energy penetration using distribution static compensator. IET Power Electronics 2021, 14, 912 -922.
AMA StyleOm Prakash Mahela, Baseem Khan, H. H. Alhelou, Sudeep Tanwar, Sanjeevikumar Padmanaban. Harmonic mitigation and power quality improvement in utility grid with solar energy penetration using distribution static compensator. IET Power Electronics. 2021; 14 (5):912-922.
Chicago/Turabian StyleOm Prakash Mahela; Baseem Khan; H. H. Alhelou; Sudeep Tanwar; Sanjeevikumar Padmanaban. 2021. "Harmonic mitigation and power quality improvement in utility grid with solar energy penetration using distribution static compensator." IET Power Electronics 14, no. 5: 912-922.
An algorithm making use of hybrid features of Hilbert transform (HT) and Stockwell transform (ST) to identify the single-stage and multiple (multi-stage) power quality disturbances (PQDs) is introduced in this manuscript. A power quality index (PI) and time location index (TLI), based on the features computed from the voltage signal by the use of HT and ST are proposed for recognition of the PQDs. Four features extracted from the PI and TLI are considered for classification of the PQDs achieved using decision tree driven by rules. The algorithm is tested on the PQDs generated with the help of mathematical models (in conformity with standard IEEE-1159). Performance is evaluated on 100 data set of every disturbance computed by varying various parameters, and efficiency is found to be greater than 99%. It is established that an algorithm is effective for recognition of PQ events with an efficiency greater than 98% even in the presence of high-level noise. Algorithm is faster compared to many reported techniques and scalable for application to voltages of all range. Results are validated through comparison with the results of the algorithms reported in the literature. Performance of the algorithm is effectively validated on the practical utility network. This algorithm can be effectively implemented for designing the power quality (PQ) monitoring devices for the utility grids.
Rajkumar Kaushik; Om Prakash Mahela; Pramod Kumar Bhatt; Baseem Khan; Sanjeevikumar Padmanaban; Frede Blaabjerg. A Hybrid Algorithm for Recognition of Power Quality Disturbances. IEEE Access 2020, 8, 229184 -229200.
AMA StyleRajkumar Kaushik, Om Prakash Mahela, Pramod Kumar Bhatt, Baseem Khan, Sanjeevikumar Padmanaban, Frede Blaabjerg. A Hybrid Algorithm for Recognition of Power Quality Disturbances. IEEE Access. 2020; 8 ():229184-229200.
Chicago/Turabian StyleRajkumar Kaushik; Om Prakash Mahela; Pramod Kumar Bhatt; Baseem Khan; Sanjeevikumar Padmanaban; Frede Blaabjerg. 2020. "A Hybrid Algorithm for Recognition of Power Quality Disturbances." IEEE Access 8, no. : 229184-229200.
To judge the ability of convolutional neural networks (CNNs) to effectively and efficiently transfer image representations learned on the ImageNet dataset to the task of recognizing COVID-19 in this work, we propose and analyze four approaches. For this purpose, we use VGG16, ResNetV2, InceptionResNetV2, DenseNet121, and MobileNetV2 CNN models pre-trained on ImageNet dataset to extract features from X-ray images of COVID and Non-COVID patients. Simulations study performed by us reveal that these pre-trained models have a different level of ability to transfer image representation. We find that in the approaches that we have proposed, if we use either ResNetV2 or DenseNet121 to extract features, then the performance of these approaches to detect COVID-19 is better. One of the important findings of our study is that the use of principal component analysis for feature selection improves efficiency. The approach using the fusion of features outperforms all the other approaches, and with this approach, we could achieve an accuracy of 0.94 for a three-class classification problem. This work will not only be useful for COVID-19 detection but also for any domain with small datasets.
Tanmay Garg; Mamta Garg; Om Prakash Mahela; Akhil Ranjan Garg. Convolutional Neural Networks with Transfer Learning for Recognition of COVID-19: A Comparative Study of Different Approaches. AI 2020, 1, 586 -606.
AMA StyleTanmay Garg, Mamta Garg, Om Prakash Mahela, Akhil Ranjan Garg. Convolutional Neural Networks with Transfer Learning for Recognition of COVID-19: A Comparative Study of Different Approaches. AI. 2020; 1 (4):586-606.
Chicago/Turabian StyleTanmay Garg; Mamta Garg; Om Prakash Mahela; Akhil Ranjan Garg. 2020. "Convolutional Neural Networks with Transfer Learning for Recognition of COVID-19: A Comparative Study of Different Approaches." AI 1, no. 4: 586-606.
The complexity of power system networks is increasing continuously due to the addition of high capacity transmission lines. Faults on these lines may deteriorate the power flow pattern in the network. This can be avoided by the use of effective protection schemes. This paper presents an algorithm for detecting and classifying faults on the transmission network. Fault detection is achieved by utilizing the fault index, which depends on a combination of characteristics extracted from the current signal by the application of the Stockwell transform and Wigner distribution function (WDF). Various faults are categorized using the quantity of phases with a faulty nature. The fault events like phase to-ground (L-G), two phases (LL), two phases to-ground (LL-G), and three phases to-ground (LLL-G) are investigated in this study. The performance of the algorithm designed for the protection scheme is tested for the variations in the impedance during the fault event, variations in the angle of the fault incidence, different fault locations, the condition of the power flow in the reverse direction, the availability of noise, and the fault on the hybrid line consisting of two sections of underground cable and the overhead line. The algorithm is also analyzed for discriminating switching incidents from fault cases. A comparative study is used to establish the superiority of the proposed technique as compared to the Wavelet transform (WT) based protection scheme. The performance of the protection technique is established in MATLAB/Simulink software using a test network of the transmission line with two terminals.
Atul Kulshrestha; Om Prakash Mahela; Mukesh Gupta; Baseem Khan; Hassan Haes Alhelou; Pierluigi Siano. Hybridization of the Stockwell Transform and Wigner Distribution Function to Design a Transmission Line Protection Scheme. Applied Sciences 2020, 10, 7985 .
AMA StyleAtul Kulshrestha, Om Prakash Mahela, Mukesh Gupta, Baseem Khan, Hassan Haes Alhelou, Pierluigi Siano. Hybridization of the Stockwell Transform and Wigner Distribution Function to Design a Transmission Line Protection Scheme. Applied Sciences. 2020; 10 (22):7985.
Chicago/Turabian StyleAtul Kulshrestha; Om Prakash Mahela; Mukesh Gupta; Baseem Khan; Hassan Haes Alhelou; Pierluigi Siano. 2020. "Hybridization of the Stockwell Transform and Wigner Distribution Function to Design a Transmission Line Protection Scheme." Applied Sciences 10, no. 22: 7985.
Enhancement in solar energy (SE) injection into the power system network creates power quality (PQ) issues in the supply. This article presents an approach supported by Stockwell transform ( $S$ -transform) for assessment of PQ issues related with the grid interfaced solar photovoltaic (SPV) system under various operating conditions. This will help to enhance the SE integration level into the utility grid. The set up, to perform assessment of the PQ issues includes an emulated SPV system interfaced with the utility at the point of common coupling (PCC). Measurements of voltage and current signals are performed by utilizing power network analyzer. The captured voltage signals are analyzed using $S$ -transform for the detection of a variety of PQ problems associated with the grid interfacing and outage of the SPV system. Effects on PQ due to presence of the various types of loads at PCC have also been investigated under the same operating conditions. Effect of partial shading of SPV plates on the PQ is also investigated. Harmonic analysis is performed for all the investigated events. The proposed algorithm proved to be successful for detecting different PQ disturbances under all the investigated operating conditions.
Om Prakash Mahela; Abdul Gafoor Shaik; Neeraj Gupta; Mahdi Khosravy; Baseem Khan; Hassan Haes Alhelou; Sanjeevikumar Padmanaban. Recognition of Power Quality Issues Associated With Grid Integrated Solar Photovoltaic Plant in Experimental Framework. IEEE Systems Journal 2020, 15, 3740 -3748.
AMA StyleOm Prakash Mahela, Abdul Gafoor Shaik, Neeraj Gupta, Mahdi Khosravy, Baseem Khan, Hassan Haes Alhelou, Sanjeevikumar Padmanaban. Recognition of Power Quality Issues Associated With Grid Integrated Solar Photovoltaic Plant in Experimental Framework. IEEE Systems Journal. 2020; 15 (3):3740-3748.
Chicago/Turabian StyleOm Prakash Mahela; Abdul Gafoor Shaik; Neeraj Gupta; Mahdi Khosravy; Baseem Khan; Hassan Haes Alhelou; Sanjeevikumar Padmanaban. 2020. "Recognition of Power Quality Issues Associated With Grid Integrated Solar Photovoltaic Plant in Experimental Framework." IEEE Systems Journal 15, no. 3: 3740-3748.
The ever increasing wind energy penetration into the utility grid causes challenges in the power quality (PQ) of the electrical supply. Therefore, this work proposed PQ assessment in the utility grid which is interfaced with the wind energy generation using Stockwell's transform (ST) under various operating events. The experimental set-up for assessing the PQ included an emulated wind generator synchronised with the utility grid at the point of common coupling. The current and voltage measurements are carried out using PQ analyser associated with WTViewer application software. The recorded signals of the voltage waveforms are assessed using ST to detect the various PQ issues related to the grid integration and wind generator's outage. To investigate the effects of various types of loads on the PQ, the same events are carried out. Various PQ disturbances are successfully detected using the proposed algorithm. Performance of the proposed algorithm is also tested on the grid integrated solar photovoltaic (PV) system to investigate and compare the PQ disturbances associated with the grid integrated solar PV system.
Om Prakash Mahela; Baseem Khan; Hassan Haes Alhelou; Sudeep Tanwar. Assessment of power quality in the utility grid integrated with wind energy generation. IET Power Electronics 2020, 13, 2917 -2925.
AMA StyleOm Prakash Mahela, Baseem Khan, Hassan Haes Alhelou, Sudeep Tanwar. Assessment of power quality in the utility grid integrated with wind energy generation. IET Power Electronics. 2020; 13 (13):2917-2925.
Chicago/Turabian StyleOm Prakash Mahela; Baseem Khan; Hassan Haes Alhelou; Sudeep Tanwar. 2020. "Assessment of power quality in the utility grid integrated with wind energy generation." IET Power Electronics 13, no. 13: 2917-2925.
Deteriorated quality of power leads to problems, such as equipment failure, automatic device resets, data errors, failure of circuit boards, loss of memory, power supply issues, uninterrupted power supply (UPS) systems generate alarm, corruption of software, and heating of wires in distribution network. These problems become more severe when complex (multiple) power quality (PQ) disturbances appear. Hence, this manuscript introduces an algorithm for identification of the complex nature PQ events in which it is supported by Stockwell’s transform (ST) and decision tree (DT) using rules. PQ events with complex nature are generated in view of IEEE-1159 standard. Eighteen different types of complex PQ issues are considered and studied which include second, third, and fourth order disturbances. These are obtained by combining the single stage PQ events such as sag & swell in voltage, momentary interruption (MI), spike, flicker, harmonics, notch, impulsive transient (IT), and oscillatory transient (OT). The ST supported frequency contour and proposed plots such as amplitude, summing absolute values, phase and frequency-amplitude obtained by multi-resolution analysis (MRA) of signals are used to identify the complex PQ events. The statistical features such as sum factor, Skewness, amplitude factor, and Kurtosis extracted from these plots are utilized to classify the complex PQ events using rule-based DT. This is established that proposed approach effectively identifies a number of complex nature PQ events with accuracy above 98%. Performance of the proposed method is tested successfully even with noise level of 20 dB signal to noise ratio (SNR). Effectiveness of the proposed algorithm is established by comparing it with the methods reported in literature such as fuzzy c-means clustering (FCM) & adaptive particle swarm optimization (APSO), Wavelet transform (WT) & neural network (NN), spline WT & ST, ST & NN, and ST & fuzzy expert system (FES). Results of simulations are validated by comparing them with real time results computed by Real Time Digital Simulator (RTDS). Different stages for design of complex PQ monitoring device using the proposed approach are also described. It is verified that the proposed approach can effectively be employed for design of the online complex PQ monitoring devices.
Om Prakash Mahela; Abdul Gafoor Shaik; Baseem Khan; Rajendra Mahla; Hassan Haes Alhelou. Recognition of Complex Power Quality Disturbances Using S-Transform Based Ruled Decision Tree. IEEE Access 2020, 8, 173530 -173547.
AMA StyleOm Prakash Mahela, Abdul Gafoor Shaik, Baseem Khan, Rajendra Mahla, Hassan Haes Alhelou. Recognition of Complex Power Quality Disturbances Using S-Transform Based Ruled Decision Tree. IEEE Access. 2020; 8 (99):173530-173547.
Chicago/Turabian StyleOm Prakash Mahela; Abdul Gafoor Shaik; Baseem Khan; Rajendra Mahla; Hassan Haes Alhelou. 2020. "Recognition of Complex Power Quality Disturbances Using S-Transform Based Ruled Decision Tree." IEEE Access 8, no. 99: 173530-173547.
Integration of RE sources to the utility grid offers technical and operational challenges causing problems of PQ, stability, identification of operational events, etc. This article presents an algorithm to identify events including islanding, grid integration, and outage of the solar PV and WG plants in grid using a ST. Islanding event may occur in the presence of any kind of plant. Processing of negative sequence component of voltage is performed by utilizing ST based multiresolution analysis at the test node and the output matrix is evaluated. The features (F1–F4), VI and STD indexes are obtained from this matrix. These features are utilized for identifying the events and transient phenomenon. The VI and STD indexes are used to recognize the type of RE source present during the islanding and outage events. Moreover, for recognizing the type of RE source at the time of synchronization event, an SI is proposed. This is computed by the ST depended processing of voltage signals. Performance of the algorithm is found satisfactory for all incidence angles and complete voltage cycle under the noisy conditions of 10 dB SNR. As compared to the time–frequency transform based coefficients of the voltage signal, the proposed technique is found to be superior in terms of small NDZ and low computation time and least affected by noise. Further, the developed technique is also efficient to detect various events stated above and the type of RE source. Study is performed using MATLAB/Simulink software and validated in real time using RTDS.
Rajkumar Kaushik; Om Prakash Mahela; Pramod Kumar Bhatt; Baseem Khan; Akhil Ranjan Garg; Hassan Haes Alhelou; Pierluigi Siano. Recognition of Islanding and Operational Events in Power System With Renewable Energy Penetration Using a Stockwell Transform-Based Method. IEEE Systems Journal 2020, PP, 1 -10.
AMA StyleRajkumar Kaushik, Om Prakash Mahela, Pramod Kumar Bhatt, Baseem Khan, Akhil Ranjan Garg, Hassan Haes Alhelou, Pierluigi Siano. Recognition of Islanding and Operational Events in Power System With Renewable Energy Penetration Using a Stockwell Transform-Based Method. IEEE Systems Journal. 2020; PP (99):1-10.
Chicago/Turabian StyleRajkumar Kaushik; Om Prakash Mahela; Pramod Kumar Bhatt; Baseem Khan; Akhil Ranjan Garg; Hassan Haes Alhelou; Pierluigi Siano. 2020. "Recognition of Islanding and Operational Events in Power System With Renewable Energy Penetration Using a Stockwell Transform-Based Method." IEEE Systems Journal PP, no. 99: 1-10.
This study presented a new multi-species binary coded algorithm, Mendelian evolutionary theory optimization (METO), inspired by the plant genetics. This framework mainly consists of three concepts: first, the “denaturation” of DNA’s of two different species to produce the hybrid “offspring DNA”. Second, the Mendelian evolutionary theory of genetic inheritance, which explains how the dominant and recessive traits appear in two successive generations. Third, the Epimutation, through which organism resist for natural mutation. The above concepts are reconfigured in order to design the binary meta-heuristic evolutionary search technique. Based on this framework, four evolutionary operators—(1) Flipper, (2) Pollination, (3) Breeding, and (4) Epimutation—are created in the binary domain. In this paper, METO is compared with well-known evolutionary and swarm optimizers: (1) binary hybrid GA, (2) bio-geography-based optimization, (3) invasive weed optimization, (4) shuffled frog leap algorithm, (5) teaching–learning-based optimization, (6) cuckoo search, (7) bat algorithm, (8) gravitational search algorithm, (9) covariance matrix adaptation evolution strategy, (10) differential evolution, (11) firefly algorithm and (12) social learning PSO. This comparison is evaluated on 30 and 100 variables benchmark test functions, including noisy, rotated, and hybrid composite functions. Kruskal–Wallis statistical rank-based nonparametric H-test is utilized to determine the statistically significant differences between the output distributions of the optimizer, which are the result of the 100 independent runs. The statistical analysis shows that METO is a significantly better algorithm for complex and multi-modal problems with many local extremes.
Neeraj Gupta; Mahdi Khosravy; Nilesh Patel; Nilanjan Dey; Om Prakash Mahela. Mendelian evolutionary theory optimization algorithm. Soft Computing 2020, 1 -46.
AMA StyleNeeraj Gupta, Mahdi Khosravy, Nilesh Patel, Nilanjan Dey, Om Prakash Mahela. Mendelian evolutionary theory optimization algorithm. Soft Computing. 2020; ():1-46.
Chicago/Turabian StyleNeeraj Gupta; Mahdi Khosravy; Nilesh Patel; Nilanjan Dey; Om Prakash Mahela. 2020. "Mendelian evolutionary theory optimization algorithm." Soft Computing , no. : 1-46.
Penetration level of solar photovoltaic (PV) energy in the utility network is steadily increasing. This changes the fault level and causes protection problems. Furthermore, multi-tapped structure of distribution network deployed to integrate solar PV energy to the grid and supplying loads at the same time also raised the protection challenges. Hence, this manuscript is aimed at introducing an algorithm to identify and classify the faults incident on the network of utilities where penetration level of the solar PV energy is high. This fault recognition algorithm is implemented in four steps: (1) calculation of Stockwell transform-based fault index (STFI) (2) calculation of Wigner distribution function-based fault index (WDFI) (3) calculation of combined fault index (CFI) by multiplying STFI and WDFI (4) calculation of index for ground fault (IGF) used to recognize the involvement of ground in a fault event. The STFI has the merits that its performance is least affected by the noise associated with the current signals and it is effective in identification of the waveform distortions. The WDFI employs energy density of the current signals for estimation of the faults and takes care of the current magnitude. Hence, CFI has the merit that it considers the current magnitude as well as waveform distortion for recognition of the faults. The classification of faults is achieved using the number of faulty phases. An index for ground fault (IGF) based on currents of zero sequence is proposed to classify the two phase faults with and without the ground engagement. Investigated faults include phase to ground, two phases fault without involving ground, two phases fault involving ground and three phase fault. Fault recognition algorithm is tested for fault recognition with the presence of noise, various angles of fault incidence, different impedances involved during faulty event, hybrid lines consisting of overhead line (OHL) and underground cable (UGC) sections, and location of faults on all nodes of the test grid. Fault recognition algorithm is also tested to discriminate the transients due to switching operations of feeders, loads and capacitor banks from the faulty transients. Performance of the fault recognition algorithm is compared with the algorithms based on discrete wavelet transform (DWT), Stockwell transform (ST) and hybrid combination of alienation coefficient and Wigner distribution function (WDF). Effectiveness of the fault recognition algorithm is established using a detailed study on the IEEE-13 nodes test feeder modified to incorporate solar PV plant of capacity 1 MW in MATLAB/Simulink. Algorithm is also validated on practical utility grid of Rajasthan State of India.
Atul Kulshrestha; Om Prakash Mahela; Mukesh Kumar Gupta; Neeraj Gupta; Nilesh Patel; Tomonobu Senjyu; Mir Sayed Shah Danish; Mahdi Khosravy. A Hybrid Fault Recognition Algorithm Using Stockwell Transform and Wigner Distribution Function for Power System Network with Solar Energy Penetration. Energies 2020, 13, 3519 .
AMA StyleAtul Kulshrestha, Om Prakash Mahela, Mukesh Kumar Gupta, Neeraj Gupta, Nilesh Patel, Tomonobu Senjyu, Mir Sayed Shah Danish, Mahdi Khosravy. A Hybrid Fault Recognition Algorithm Using Stockwell Transform and Wigner Distribution Function for Power System Network with Solar Energy Penetration. Energies. 2020; 13 (14):3519.
Chicago/Turabian StyleAtul Kulshrestha; Om Prakash Mahela; Mukesh Kumar Gupta; Neeraj Gupta; Nilesh Patel; Tomonobu Senjyu; Mir Sayed Shah Danish; Mahdi Khosravy. 2020. "A Hybrid Fault Recognition Algorithm Using Stockwell Transform and Wigner Distribution Function for Power System Network with Solar Energy Penetration." Energies 13, no. 14: 3519.
In practical operating conditions, the Solar-Photo Voltaic (SPV) system experiences multifarious irradiation and temperature levels, which generate power with multiple peaks. This is considered as the nonuniform operating condition (NUOC). This requires accurate tracking of global power peaks to achieve maximum power from SPV, which is a challenging task. Hence, this paper presents an incremental Conductance based Particle Swarm Optimization (ICPSO) algorithm for accurate tracking of maximum global power from active power multiple peaks generated by the SPV. The proposed algorithm continuously adjusts the individual particle’s weight component, which depends on its distance from the global best position during the tracking process. The proposed algorithm has the merit of continuous adjustment of weight components which reduces active power oscillations at the optimal global position area. Proposed ICPSO algorithm has been successfully designed and implemented for Solar-photo voltaic (PV) under nonuniform operating condition. It is established that the proposed algorithm enhances the output power of the Solar-PV up to 7% with the maximum power tracking of 0.1 s compared to other maximum power point tracking algorithms.
Gajendra Singh Chawda; Om Prakash Mahela; Neeraj Gupta; Mahdi Khosravy; Tomonobu Senjyu. Incremental Conductance Based Particle Swarm Optimization Algorithm for Global Maximum Power Tracking of Solar-PV under Nonuniform Operating Conditions. Applied Sciences 2020, 10, 4575 .
AMA StyleGajendra Singh Chawda, Om Prakash Mahela, Neeraj Gupta, Mahdi Khosravy, Tomonobu Senjyu. Incremental Conductance Based Particle Swarm Optimization Algorithm for Global Maximum Power Tracking of Solar-PV under Nonuniform Operating Conditions. Applied Sciences. 2020; 10 (13):4575.
Chicago/Turabian StyleGajendra Singh Chawda; Om Prakash Mahela; Neeraj Gupta; Mahdi Khosravy; Tomonobu Senjyu. 2020. "Incremental Conductance Based Particle Swarm Optimization Algorithm for Global Maximum Power Tracking of Solar-PV under Nonuniform Operating Conditions." Applied Sciences 10, no. 13: 4575.