A5024008257- Power Systems Fault Detection
- Islanding Detection in Power Systems
- Smart Grid Security and Resilience
- Microgrid Control and Optimization
- Advanced Control Systems Design
- Advanced Battery Technologies Research
- EEG and Brain-Computer Interfaces
- HVDC Systems and Fault Protection
- Power System Optimization and Stability
- Neuroscience and Neural Engineering
- Photovoltaic System Optimization Techniques
- Advanced Control Systems Optimization
- Fuel Cells and Related Materials
- Electric and Hybrid Vehicle Technologies
- Multilevel Inverters and Converters
- Advanced DC-DC Converters
- Network Security and Intrusion Detection
- Advanced Adaptive Filtering Techniques
- Supercapacitor Materials and Fabrication
- Advanced Memory and Neural Computing
- Diabetes Management and Research
- Extremum Seeking Control Systems
- Power Quality and Harmonics
- Psoriasis: Treatment and Pathogenesis
- Metaheuristic Optimization Algorithms Research
National Institute of Technology Raipur
2016-2025
Rajshahi University of Engineering and Technology
2024
National Institute of Technology Rourkela
2007-2022
Science Museums
2019
Birla Institute of Technology, Mesra
2010-2017
National Institute of Technology Calicut
2016
Cognizant (India)
2016
Rajiv Gandhi Technical University
2013
Indian Institute of Technology Kharagpur
2008
The proliferation of non-linear loads in recent times has a strong bearing on power quality due to the presence harmonics system. Harmonics lead erroneous measurement and malfunctioning protective relays, thus reducing efficacy transmission line protection. With aim improving dependability protection scheme under varying loading condition, study presents hybrid support vector machine (SVM), artificial neural network (ANN) Kalman filter based algorithm using voltage for three-phase line....
Restrictions on right of way and increasing power demand has boosted development six phase transmission. It offers a viable alternative for transmitting more power, without major modification in existing structure three double circuit transmission system. Inspite the advantages, low acceptance system is attributed to unavailability proper protection scheme. The complexity arising from large number possible faults lines makes quite challenging. proposed work presents hybrid wavelet transform...
The need for enhancing grid resilience has led to wider acceptance of photo voltaic (PV) integrated microgrid. variation in fault current during connected and islanding operation makes the microgrid protection task challenging. A scheme based on ensemble classifiers been devised by exploiting effectiveness a classifier set coupled with voting strategy. Unlike existing classifier‐based approaches involving single classifier, ensemble‐based approach is insensitive biasness individual...
The nuisance tripping of distance relay during power swing has been identified as one the major causes for system blackouts. Avoiding risk maloperation and hence improving resilience swing, demands development a scheme capable generating blocking signal detecting fault occurring with from measurement current signal. In this regard, protection based on hybrid framework an ensemble tree, least square, Adaline algorithm to perform task detection/classification, zone identification, location...
The ever increasing power demand and stress on reducing carbon footprint have paved the way forwidespread use of photovoltaic (PV) integrated microgrid. However, thedevelopment a reliable protection scheme for PV microgrid ischallenging because similar voltage‐current profile array faultsand symmetrical line faults. Conventional schemes based onpre‐defined threshold setting are not able to distinguish between andsymmetrical faults, hence fail provide separate controlling actions forthe two...
In recent times, lithium iron phosphate (LFP) batteries have found wide usage in electric vehicles (EVs). Efficient utilization of the storage capacity any battery used EVs is heavily dependent on accuracy state charge (SOC) estimation. The classical SOC-OCV (open circuit voltage) based approach for estimation SOC quite ineffective under rapid variation operating condition EVs. impact parameter variations and unknown disturbances due to widely varying environmental conditions drive terrain,...
Accurate and reliable control of a magnetic levitation (maglev) plant is challenging due to position tracking irregularities, parameter perturbations, external disturbances, stringent dynamic requirements. In this study, radial basis function neural network-based adaptive gain super-twisting sliding mode controller (RBF-ASTC) proposed achieve high-performance the maglev system. The presence unknown model uncertainties disturbances limit performance classical higher-order sliding-mode (HOSM)...