I am interested in control of dynamic systems with applications related to Power and Energy Systems . My research interests are on Wind-integrated power system modeling, analysis and control, Power systems dynamic performance, Wide area monitoring and control, Optimal and Robust control, Adaptive dynamic programming (ADP)/Reinforcement Learning (RL) and Power Electronics for renewable integration.
5. S. Mukherjee, A. Darvishi, A. Chakrabortty, and B. Fardanesh, Learning Power System Dynamic Signatures using LSTM-Based Deep Neural Network: A Prototype Study on the New York State Grid. IEEE PES General Meeting, Atlanta, GA, 2019.
4. S. Mukherjee, A. Chakrabortty, and H. Bai. Block-Decentralized Model-Free Reinforcement Learning Control of Two Time-Scale Networks. American Control Conference, Philadelphia, 2019.
3. S. Mukherjee, H. Bai, and A. Chakrabortty. On Model-Free Reinforcement Learning of Reduced-order Optimal Control for Singularly Perturbed Systems. 59th IEEE Conference on Decision and Control, FL, Dec. 2018.
2. S. Mukherjee, N. Xue, and A. Chakrabortty. A Hierarchical Design for Damping Control of Wind-Integrated Power Systems Considering Heterogeneous Wind Farm Dynamics. 2nd IEEE Conference on Control Technology and Applications, Denmark, Aug. 2018.
1. S. Mukherjee, S. Babaei, and A. Chakrabortty. A Measurement-based Approach for Optimal Damping Control of the New York State Power Grid. IEEE PES General Meeting, Portland, OR, 2018.
Graduate Research Asst
Keystone Science Center 100
|Type of Degree||Degree Program||School||Year|
|B.E.||Electrical Engineering||Jadavpur University, India||2015|
- Power Systems