Nandan Gopinathan

About

NANDAN GOPINATHAN (Member, IEEE) received the B.Tech. degree in electrical and electronics engineering from the University of Kerala, India, in 2008, and the M.E. degree in power systems from Anna University, Chennai, India, in 2012. He is currently pursuing the Ph.D. with the School of Electrical Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu, India. After nine years of teaching experience as an Assistant Professor. His research interests include wide area monitoring systems, decentralized grid regulation, data analytics in power systems, electric mobility, smart charging stations, smart grids, and congestion management. He is a Lifetime Member of Indian Society for Technical Education (ISTE) and the International Association for the Engineers (IAENG).

Employment

• Vellore Institute of Technology University PhD scholar
  2021 - Present
• VELLORE INSTITUTE OF TECHNOLOGY

Education

• Anna University Masters in Engineering
  2010 - 2012

Projects & Funding

Projects & funding information is unavailable.

Publications (13)

• Adaptive congestion management for EV charging in synchrophasor enabled ADNs: A decentralised distributed approach with concordance framework
  Energy Reports 2026 DOI: 10.1016/j.egyr.2026.109238
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• Deep-cycle battery sizing and strategic battery management in solar-EV systems using UDDS drive cycles with real-time environment
  Engineering Research Express 2025 DOI: 10.1088/2631-8695/adfb22
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• Enhanced Grid Inertia Management: A PSO-Trained ANN Approach for Flexible Power Point Tracking in Photovoltaic Operation
  2025 Innovations in Power and Advanced Computing Technologies (i-PACT) 2025 DOI: 10.1109/i-pact65952.2025.11307824
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• Improved real-time Lithium-ion battery parameter extraction and prediction analysis using ML framework
  Engineering Research Express 2025 DOI: 10.1088/2631-8695/adc657
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• Improved Real-Time Lithium-Ion Battery Parameter Extraction and Prediction Analysis Using Ml Framework
  Ssrn 2024 DOI: 10.2139/ssrn.4753993
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• Synchrophasor Forensics: Tracking Spatiotemporal Anomalies and Diagnosing Grid Frequency Events with Machine Learning for Enhanced Situational Awareness
  IEEE Access 2024 DOI: 10.1109/ACCESS.2024.3495018
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• Wavelet-ARIMA-Based Forensic Analysis of Synchrophasor Data Using Machine Learning
  2024 International Conference on Sustainable Technology and Engineering I Coste 2024 2024 DOI: 10.1109/i-COSTE63786.2024.11024660
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• Minimising Energy Consumption Cost Using Ant Colony Optimization with Power Quality Considerations Under HEMS Environment
  2023 Innovations in Power and Advanced Computing Technologies (i-PACT) 2023 DOI: 10.1109/i-pact58649.2023.10434471
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• Smart Grid Architecture Model (SGAM) for resilience using Energy Internet of Things (EIoT)
  2022 22nd National Power Systems Conference (NPSC) 2022 DOI: 10.1109/npsc57038.2022.10069412
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• Energy Anxiety in Decentralized Electricity Markets: A Critical Review on EV Models
  Energies 2022 DOI: 10.3390/en15145230
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