Pampa sinha

Dr. Pampa Sinha received Ph.D. Degree in Electrical Engineering from Jadavpur University in 2017 and obtained her M-tech degree in Electrical Engineering from University of Calcutta (Govt), West Bengal, India in 2009. Currently she is the Associate Professor in School of Electrical Engineering, KIIT deemed to be University, Bhubaneswar, India. Her research area is Power Quality assessment, Power Quality Management and Energy storage device. She has published many papers in referred journals. Currently she has two granted Indian Patent and completed two Projects.

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Email :
[email protected]
Scopus Id :
http://57197501221
Google Scholar :
https://scholar.google.co.in/citations?user=

Social Links

Educational Qualification
Ph.D.

Research Interests
Power Quality Management

Projects
Recomended for DST

Administrative Responsibility
FIC of Industrial Visit

Awards & Honours
P.h.D Degree

Memberships
IET and IE

Outreach Activity
Jadavpur University, ISRO Research guidance a.Master: 8 b.Ph.D.: 2 Completed and 3 Ongoing 7. Projects (Ongoing/ Completed): One Consultancy Project Completed : One International Project Completed with the collaboration with Ignium Laboratory (France) 8. Details of Patents: 1. Thermal Screening Door (Indian patent Granted) 2. An Edge Computing Based Fault Identification and Localization for Intelligent DG Unit Disconnection in Power System (Indian Patent Granted)
Journals/Conferences :
Sinha, Pampa. (n.d.). Power quality assessment of distribution systems under stationary and nonstationary disturbances.
Sinha, Pampa, Paul, K., Deb, S., Vidyarthi, A., Kilak, A. S., & Gupta, D. (2023). A New Approach to Detect Power Quality Disturbances in Smart Cities Using Scaling-Based Chirplet Transform with Strategically Placed Smart Meters. Journal of Circuits, Systems and Computers, 2450093.
Sinha, Pampa, Paul, K., Deb, S., & Sachan, S. (2023). Comprehensive Review Based on the Impact of Integrating Electric Vehicle and Renewable Energy Sources to the Grid. Energies, 16(6), 2924.
Sinha, Pampa, Paul, K., Chatterjee, S., García Márquez, F. P., Ogale, J., Ali, A., & Khan, B. (2023). Cross‐country high impedance fault diagnosis scheme for unbalanced distribution network employing detrended cross‐correlation. IET Generation, Transmission & Distribution.
Sinha, Pampa, Paul, K., Saiprakash, C., Abdelaziz, A. Y., Omar, A. I., Su, C.-L., & Elsisi, M. (2023). Identification of cross-country fault with high impedance syndrome in transmission line using tunable Q wavelet transform. Mathematics, 11(3), 586.
Paul, K., Sinha, P., Bouteraa, Y., Skruch, P., & Mobayen, S. (2023). A Novel Improved Manta Ray Foraging Optimization Approach for Mitigating Power System Congestion in Transmission Network. IEEE Access, 11, 10288–10307.
Vennila, H., Giri, N. C., Nallapaneni, M. K., Sinha, P., Bajaj, M., Abou Houran, M., & Kamel, S. (2022). Static and dynamic environmental economic dispatch using tournament selection based ant lion optimization algorithm. Frontiers in Energy Research, 10, 972069.
Lenka, S., Sinha, P., Paul, K., Jena, C., Das, S., & Khan, B. (2022). Identification of the Dominant Harmonic Source Type in the Distribution Network Using the Soft Computing Technique. International Transactions on Electrical Energy Systems, 2022.
Paul, K., Sinha, P., Mobayen, S., El-Sousy, F. F. M., & Fekih, A. (2022a). A novel improved crow search algorithm to alleviate congestion in power system transmission lines. Energy Reports, 8, 11456–11465.
Joga, S. Ramana Kumar, Sinha, P., & Maharana, M. K. (2023). A novel graph search and machine learning method to detect and locate high impedance fault zone in distribution system. Engineering Reports, 5(1), e12556.
Sinha, Pampa, Goswami, S. K., & Nath, S. (2016). Wavelet‐based technique for identification of harmonic source in distribution system. International Transactions on Electrical Energy Systems, 26(12), 2552–2572.
Nath, Sudipta, Sinha, P., & Goswami, S. K. (2012). A wavelet based novel method for the detection of harmonic sources in power systems. International Journal of Electrical Power & Energy Systems, 40(1), 54–61.
Joga, S. Ramana K., Sinha, P., Maharana, M. K., Kothari, D. P., & Jena, C. (2022). IDENTIFICATION OF FAULT ZONE IN DISTRIBUTION SYSTEM IN THE PRESENCE OF PV MODULE AND ESD BY DTCWT–STATE VECTOR MACHINE ALGORITHM USING OPTIMALLY PLACED MEASURING DEVICES. International Journal of Power and Energy Systems, 42(10).
Scopus Publications
Sinha, Pampa, Debath, S., & Goswami, S. K. (2016). Classification of power quality events using wavelet analysis and probabilistic neural network. IAES International Journal of Artificial Intelligence (IJ-AI), 5(1), 1–12.
Sinha, Pampa, Goswami, S. K., & Debnath, S. (2017). Harmonic source identification in distribution system using non-active power quantities. International Journal of Power and Energy Conversion, 8(1), 90–111.
Nath, S., & Sinha, P. (1981). Survival after complete excision of renal vein of a solitary kidney. Medical Journal of Zambia, 15(4), 65–66.
Chatterjee, S., Gatla, R. K., Sinha, P., Jena, C., Kundu, S., Panda, B., … Pradhan, A. (2023). Fault detection of a Li-ion battery using SVM based machine learning and unscented Kalman filter. Materials Today: Proceedings, 74, 703–707.
Ponukumati, B. K., Sinha, P., Maharana, M. K., Kumar, A. V. P., & Karthik, A. (2022). An Intelligent Fault Detection and Classification Scheme for Distribution Lines Using Machine Learning. Engineering, Technology & Applied Science Research, 12(4), 8972–8977.
Jena, C., Sinha, P., Nanda, L., Pradhan, A., & Panda, B. (2022). Optimal scheduling with opposition based differential evolution optimized fixed head hydro-thermal power system. Materials Today: Proceedings, 58, 227–232.

oConferences
Sinha, Pampa, Maharana, M. K., Jena, C., Kumar, A. V. P., & Akkenaguntla, K. (2021). Power System Fault Detection Using Image Processing And Pattern Recognition. IEEE.
De, S., Nath, S., Sinha, P., & Saha, S. (2011). A virtual instrument for real time power quality measurement under nonsinusoidal conditions. IEEE.
Joga, S. Ramana Kumar, Sinha, P., Maharana, M. K., & Jena, C. (2021). Tunable Q-Wavelet Transform Based Entropy Measurement to Detect and Classify Faults in CERTS Microgrid Test Bed. IEEE.
Sinha, Pampa, & Nath, S. (2010). Assessment of Power Quality based on Fuzzy Logic and Discrete Wavelet Transform for Nonstationary Disturbances (Vol. 1298). American Institute of Physics.
Roshan, R., Samal, P., & Sinha, P. (2020). Optimal placement of FACTS devices in power transmission network using power stability index and fast voltage stability index. IEEE.
Sinha, Pampa, & Maharana, M. K. (2019). Artificial intelligence in classifying high impedance faults in electrical power distribution system.
Kumar, A., Ramana Kumar Joga, S., & Sinha, P. (2022). Fault Detection in Hybrid AC/DC Micro-grid by Using DTCWT and KNN-Based Classifier. In Advances in Data and Information Sciences: Proceedings of ICDIS 2021 (pp. 261–269). Springer Singapore Singapore.
Lenka, S., Sinha, P., & Jena, C. (2022a). A review on power quality improvement of grid connected PV with lithium-ion and super capacitor based hybrid energy storage system using a new control strategy. Renewable Energy Optimization, Planning and Control: Proceedings of ICRTE 2021, Volume 1, 1–10.
Joga, S. Ramana Kumar, Sinha, P., & Maharana, M. K. (2021b). Performance study of various machine learning classifiers for arc fault detection in AC microgrid (Vol. 1131). IOP Publishing.
Krishna, P. B., & Sinha, P. (2018). Detection of power system harmonics using NBPSO based optimally placed harmonic measurement analyser units. IEEE.
Sinha, Pampa, Goswami, S. K., & Debnath, S. (2016). Disturbing load identification in distribution system network. IEEE.
Sinha, P., Debnath, S., & Goswami, S. K. (2015). A new wavelet and fuzzy based power quality index for distribution systems under stationary and nonstationary disturbances.
Joga, S. Ramana Kumar, Sinha, P., & Maharana, M. K. (2021a). Measurement of Power in Distribution System using DTCWT Based Signal Processing Technique (Vol. 795). IOP Publishing.
Tripathy, S., Mohanty, S. N., Ghatak, S. R., & Sinha, P. (2021). Modeling of EV Load and Its Impacts on the Distribution System for Static Condition. IEEE.
Lenka, S., Sinha, P., & Jena, C. (2021). A Improvement Review on Power Quality of Grid Connected PV with Lithium-Ion and Super Capacitor Based Hybrid Energy Storage System Using a New Control Strategy. Renewable Energy Optimization, Planning and Control: Proceedings of ICRTE 2021, Volume 1, 1.
Roy, S., Mandal, M., Jena, C., Sinha, P., & Jena, T. (2021). Programmable-logic-controller based robust automatic cleaning of solar panel for efficiency improvement. IEEE.
Joga, S. Ramana Kumar, Sinha, P., & Maharana, M. K. (2020). Genetic algorithm and graph theory approach to select protection zone in distribution system. In Advances in Smart Grid Technology: Select Proceedings of PECCON 2019—Volume II (pp. 165–174). Springer Singapore Singapore.
Sinha, Pampa, & Jena, C. (2021). Application of Probabilistic Neural Network and Wavelet Analysis to Classify Power Quality. In Microgrids (pp. 217–229). CRC Press.
Swain, G., Sinha, P., & Maharana, M. K. (2017). Detection of islanding and power quality disturbance in micro grid connected distributed generation. IEEE.
Joga, S. Ramana Kumar, Kumar, A., Sinha, P., & Maharana, M. K. (2022). Detecting the Change in Microgrid Using Pattern Recognition and Machine Learning. Springer Singapore.
Mishra, S., Sinha, P., & Swain, S. C. (2018). An Innovative fuzzy based Power Quality Assessment of Distorted Electrical Power System. IEEE.
Ponukumati, B. K., Sinha, P., Maharana, M. K., Jenab, C., Kumar, A. V. P., & Akkenaguntla, K. (2021). Pattern Recognition Technique Based Fault Detection in Multi-Microgrid. IEEE.
Nath, Sudipta, & Sinha, P. (2009). Measurement of power quality under nonsinusoidal condition using wavelet and fuzzy logic. IEEE.
Jena, C., Sinha, P., Nanda, L., Samal, S., Panda, B., & Pradhan, A. (2022). Generation Scheduling of Solar-Wind-Hydro-Thermal Power System with Pumped Hydro Energy Storage using Squirrel Search Algorithm (SSA). In Industrial Transformation (pp. 321–344). CRC Press.
Jena, C., Sinha, P., Nanda, L., Panda, B., Pradhan, A., & Mohapatra, S. (2022). Opposition Based Group Search Optimized Optimal Scheduling of Fixed Head hydrothermal Power System. IEEE.
Lenka, S., Sinha, P., & Jena, C. (2022b). Study on Integration of Electric Vehicle with Wind Energy. IEEE.
Joga, S. Ramana Kumar, Sinha, P., Maharana, M. K., Jena, C., Mishra, A., & Roy, A. (2022). Stockwell Transform and Data Mining based Fault Diagnosis Method to protect Microgrid. IEEE.
Samal, P., Swain, R. R., Jena, C., Sinha, P., Mishra, S., & Swain, S. C. (2022). A Modified Differential Evolution Algorithm Solving for Engineering Optimization Problems. IEEE.
Joga, S. Ramana Kumar, Saiprakash, C., Mohapatra, A., Sinha, P., Nayak, B., & Maharana, M. K. (2022). Fault Diagnosis in PV system using DWT and Ensembled k-NN Machine Learning Classifier. IEEE.
Tripathy, S., Mohanty, S. N., Ghatak, S. R., & Sinha, P. (2022). Probabilistic Modeling of PHEV Load and Its Impacts in Unbalanced Distribution System with D-STATCOM. IEEE.
Saiprakash, C., Joga, S. R. K., Mohapatra, A., Sinha, P., Nayak, B., & Maharana, M. K. (2021). Stockwell Transform & Data Mining based method for Fault detection and classification in PV Array. IEEE.
Joga, S. Ramana Kumar, Ray, L., Saiprakash, C., Sinha, P., Jena, C., & Priyadarshini, S. (2022a). A Comparative Technique to detect and classify Power Quality Disturbances with Noise Signals. IEEE.
Joga, S. Ramana Kumar, Ray, L., Saiprakash, C., Sinha, P., Jena, C., & Priyadarshini, S. (2022b). PQD’s Detection and Classification Under Normal and Noisy Conditions Based on RADWT & SVM Based Technique. IEEE.
Bhagat, V. K., Paul, K., Dutta, R., Sinha, P., & Debnath, M. K. (2022). Performance Analysis of FLC & ANN Based MPPT Controller For Solar PV System. IEEE.
Joga, S. Ramana Kumar, Saiprakash, C., Sinha, P., Ray, L., Jena, C., & Krishna, T. V. (2022). Detecting and Classifying PQD’s occur in Microgrid by Scaling Basis Chirplet Transform and SVM classifier based Technique. IEEE.