Sugandh Pratap Singh
Indian Institute of Technology Kanpur, National Institute of Technology Raipur, Galgotias College of Engineering and Technology
About
Sugandh Pratap Singh ( Student Member, IEEE) received the bachelor’s degree in electrical engineering
from Uttar Pradesh Technical University, Lucknow, India, in 2013, and the M.Tech. degree in electrical
engineering from the National Institute of Technology (NIT), Raipur, India, in 2017. He is currently
pursuing the Ph.D. degree with the Electrical Engineering Department, IIT Kanpur, Kanpur, India. His
research interests include smart grid monitoring and control, wide area monitoring protection and control,
and smart grid cyber security.
Employment
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Indian Institute of Technology Kanpur Technical Superintendent2024 - Present
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Indian Institute of Technology Kanpur Junior Technical superintendent2017 - 2024
Education
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Indian Institute of Technology Kanpur PhD2023 - Present
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National Institute of Technology Raipur M.TECH2015 - 2017
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Galgotias College of Engineering and Technology B.Tech2009 - 2013
Projects & Funding
Projects & funding information is unavailable.
Publications (13)
- Securing sustainable digital substations: A survey on cyber vulnerabilities and defenses Save
- Support Vector Regression Model Assisted Robust Frequency Control for Marine Microgrids Under Stochastic Conditions With Real-Time Validation Save
- Development and implementation of a MATLAB-based phasor data concentrator for synchrophasor applications Save
- Symbiotic organisms search algorithm based model reduction of higher order continuous systems Save
- Analytic hierarchy process-based model reduction of higher order continuous systems using sine cosine algorithm Save
- Best-case, worst-case and mean integral-square-errors for reduction of continuous interval systems Save
- Coordinated tuning of controller-parameters using symbiotic organisms search algorithm for frequency regulation of multi-area wind integrated power system Save
- PID controller tuning using hybrid optimisation technique based on box's evolutionary optimisation and teacher-learner-based-optimisation Save
- Analytic hierarchy process based approximation of high-order continuous systems using TLBO algorithm Save
- Economic load dispatch problem: quasi-oppositional self-learning TLBO algorithm Save