National Institute of Technology Rourkela

राष्ट्रीय प्रौद्योगिकी संस्थान राउरकेला

ଜାତୀୟ ପ୍ରଯୁକ୍ତି ପ୍ରତିଷ୍ଠାନ ରାଉରକେଲା

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Faculty Profile

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EXPERTISE INFORMATION

Research Group
  • Power Systems
Areas of Interest
  • Power System Operation and Control
  • Power System Protection
  • Artificial Intelligence
  • Machine Learning
  • Formal Verification

Ananyo Sengupta Assistant Professor Grade-I, Electrical Engineering

senguptaa@nitrkl.ac.in

0661 - 246 2446

Biosketch

7

PUBLICATIONS

2

DOCTORAL STUDENTS

PERSONAL INFORMATION

Ananyo Sengupta

Assistant Professor Grade-I

Electrical Engineering

Room Number: EE-224

Department of Electrical Engineering, National Institute of Technology Rourkela, Sundargarh, Odisha, India - 769008

Ph.D., IIT Kharagpur

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Total Publications: 7
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A. Sengupta, S. Mukhopadhyay, and A.,"Automated verification of power system protection schemes—Part I: modeling and specifications", IEEE TRANSACTIONS ON POWER DELIVERY, vol.30, no.5, pp.2077-2086, IEEE, October 2015       Article

A. Sengupta, S. Mukhopadhyay, and A.,"Automated verification of power system protection schemes—part II: test case generation using swarm intelligence", IEEE Transactions on Power Delivery, vol.30, no.5, pp.2087 - 2095, IEEE, October 2015, 10.1109/TPWRD.2014.2376592       Article

A. Sengupta,"Prevention of Load Encroachment Using Model Predictive Control", IEEE Transactions on Power Delivery, vol.36, no.6, pp.3657-3670, IEEE 2021, 10.1109/TPWRD.2020.3046359       Article

A. Das and A. Sengupta,"Power system voltage stabilization using model predictive control", Electrical Engineering, vol.106, pp.2765-2783, Springer 2024, https://doi.org/10.1007/s00202-023-02099-5       Article

A. Das and A. Sengupta,"Model predictive control for resilient frequency management in power systems", Electrical Engineering, vol.106, pp.6131–6157, Springer 2024, 10.1007/s00202-024-02352-5       Article

  • Advanced Machine Learning {Theory}
  • Artificial Intelligence {Theory}
  • Basic Electrical Engineering {Theory}
  • Introduction to AI and ML {Theory}
  • Introduction to Machine Learning {Theory}
  • Power System Analysis and Control {Theory}
  • Power System Operation and Control {Theory}
  • Power System Protection {Theory}
  • Power Systems Operation and Control {Theory}
  • Soft Computing Techniques {Theory}
  • Switch Gear and Protective Devices {Theory}
  • AI and ML Laboratory {Practical}
  • Basic Electrical Engineering Laboratory {Practical}
  • Computer Aided Power System Laboratory {Practical}
  • Control and Electrical Systems Design Laboratory {Practical}
  • Electrical Engineering Laboratory {Practical}
  • Electrical Engineering Laboratory – I {Practical}
  • Electrical Machines Laboratory – I {Practical}
  • Machine Learning Applications to Power Systems Lab {Practical}
  • Power System Simulation Laboratory {Practical}
  • Power Systems Design Laboratory {Practical}
  • Soft Computing Laboratory {Practical}

Ph.D. Students [2]
Optimal Load Frequency and Voltage Control in Interconnected Power Systems: A Model Predictive Control Approach
Anurag Das
Enrolled: Jan 2018
Graduated :  Dec 2024
Supervisor
POWER SYSTEM
Sourav Das
Enrolled: Sep 2020
Continuing
Supervisor

Memberships / Fellowships
  • IEEE,