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Hi, I’m Ashwin Shirsat

I am an Electrical Engineering Ph.D. student with the Grid Analytics, Markets, Economics, and Systems (GAMES) research group within the FREEDM systems center at North Carolina State University, working under the guidance of Dr. Wenyuan Tang.

My research focuses on data-driven decision-making under uncertainty for smart electric grid applications using techniques in electrical engineering, optimization, machine learning, and data analytics. My expertise lies in electric distribution/microgrid operations and optimization.

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Education
  • North Carolina State University, Raleigh, NC, USA

    Doctor of Philosophy in Electrical Engineering

    2018-2022

Last updated 2021-08-23

News
My Publications

  1. Data-Driven Stochastic Model Predictive Control for DC-Coupled Residential PV-Storage Systems
    Shirsat, A., and Tang, W.
    IEEE Transactions on Energy Conversion 2021
  2. Quantifying residential demand response potential using a mixture density recurrent neural network
    Shirsat, A., and Tang, W.
    International Journal of Electrical Power & Energy Systems 2021
  3. Hierarchical Multi-timescale Framework For Operation of Dynamic Community Microgrid
    Shirsat, A., Muthukaruppan, V., Hu, R., Lu, N., Baran, M., Lubkeman, D., and Tang, W.
    Accepted for IEEE Power and Energy Society General Meeting (PESGM) 2021
  4. A Load Switching Group based Feeder-level Microgrid Energy Management Algorithm for Service Restoration in Power Distribution System
    Hu, R., Li, Y., Zhang, S., Shirsat, A., Muthukaruppan, V., Tang, W., Baran, M., Lubkeman, D., and Lu, N.
    Accepted for IEEE Power and Energy Society General Meeting (PESGM) 2021
  5. Sustainable Community based PV-Storage Planning using the Nash Bargaining Solution
    Liang, J., Shirsat, A., and Tang, W.
    International Journal of Electrical Power and Energy Systems (IJEPES) 2020
  6. Sensitivity Analysis of Time-of-Use Rates on Operations of Home Energy Management Systems
    Shirsat, A., and Tang, W.
    IEEE Power and Energy Society General Meeting (PESGM) 2020
  7. Identification of the Potential of Residential Demand Response Using Artificial Neural Networks
    Shirsat, A., and Tang, W.
    North American Power Symposium (NAPS) 2019
  8. Dual tracking efficiency improvement method for photovoltaic systems
    Kak, A., Srinivasan, M., Shirsat, A., and Chandle, J. O.
    International Conference on Microelectronics, Computing and Communications (MicroCom) 2016

My Patents

  1. Volt-var device monitor
    Joshi, V., and Shirsat, A.
    Google Patents 2019

Relevant Course Work
My Projects
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Photovoltaic Analysis and Response Support Platform for Solar Situational Awareness and Resiliency Services
The goal of this project is to design algorithms for resilient microgrid energy management that are robust to uncertainties, can sustain microgrid operations for extended duration outages. The application of the algorithms ranges from small microgrids to distribution feeders that have high penetration of PV generation. The developed algorithms will be validated on real world systems in a hardware-in-loop environment.
Technologies
CPLEX Python R Matlab OpenDSS Git

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