Postdoctoral Researcher (ECE, Georgia Tech)

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Research Interests:

• Power System Optimization, Control and Planning of Distributed Energy Resources, Optimal Power Flow
• Distributed Optimization, ADMM
• Electric Vehicle Control and Planning
• Synthetic Networks, Hosting Capacity Analysis
• Data-driven Control, Model-less Control Schemes

Education

• Ph.D., Electrical Engineering

  Swiss Federal Institute of Technology - EPFL, Switzerland (Jan 2023) Thesis link

• M.Sc., Electrical Engineering

  Swiss Federal Institute of Technology - EPFL, Switzerland (July 2018)

• B.Tech., Electrical Engineering

  National Institute of Technology, Rourkela, India (July 2014)

Work Experience

Postdoctoral Researcher, Georgia Tech, USA (Oct 2023 - present)

• Synthetic network generation for the USA region.
• Hosting capacity analysis for the power distribution systems

Postdoctoral Researcher, Distributed Electrical Systems Laboratory, EPFL, Switzerland (Feb 2023 - Sep 2023)

• Real-time control and day-ahead scheduling of electric vehicle charging stations (EVCSs) for dispatching active distribution networks. Experimental validation of a dispatching scheme on the real-life medium voltage (MV) power grid of the EPFL.
• Optimal Power Flow (OPF)-based control and planning of multi-energy systems in a microgrid. Multi-energy systems include modeling and optimization of electrochemical, gas, and thermal storage systems.

Doctoral Researcher, Distributed Electrical Systems Laboratory, EPFL, Switzerland (Sept 2018 - Jan 2023)

• Optimal Power Flow (OPF)-based grid-aware scheduling and control frameworks for the active distribution networks (ADNs). Stochastic optimization-based dispatch plan computation considering uncertainties on demand and generation by scenarios. Real-time model predictive control of stochastic and energy storage units.
• Measurement-based/data-driven estimation and control frameworks for distribution networks. Recursive estimation of power-flow sensitivity coefficients for robust voltage control. Estimating compound admittance matrix of an untransposed distribution network using voltage and branch currents measurements.
• Distributed control and optimization of ADNs with heterogeneous distributed energy resources (batteries, curtailable photovoltaic plants, electrolyzers, fuel cells, etc.) using a method such as ADMM and its variants.
• Experimental validation of the above control schemes on real-life low-voltage microgrid (hosted at the Distributed Electrical Systems Laboratory, EPFL) and medium-voltage distribution networks (in Aigle, Switzerland).

Visiting Doctoral Researcher, ParisTech MINES, Nice, France (Sept 2019 - Jan 2020)

• Development of a countrywide planning tool for estimating photovoltaic (PV) hosting capacity and battery energy storage requirements (as an alternative to grid reinforcement) of power distribution networks.
• Synthetic power distribution network generation tool for countrywide planning and operation study, made publicly available. link

Projects

Countrywide/Large-scale Assessment of Renewable Energy Resources Hosting Capacity and Flexibility Requirements of the Power Distribution Grids in the USA using Synthetic Models (funded by Swiss National Science Foundation) link

The aim of the project is to build realistic synthetic models of electricity distribution networks that can be characterized as a function of geo-specific factors such as the density of electricity demand, weather conditions, types of regions (urban or rural), topography, etc. We will then use these synthetic networks to calculate their capacity to accommodate renewable energies, using a tool developed as part of this project. In addition, we will also develop an optimal planning tool to optimize the amount of energy storage and network reinforcement required to increase the capacity of existing networks. These analyses will enable engineers to design future electricity networks and policymakers to make informed decisions on different energy system policies for different regions of the country.

MESH4U (co-funded by European Union’s Horizon 2020 and ERA-Net Smart Energy Systems) link

Experimental validation of a grid-aware dispatching framework by utilizing the flexibility from electric vehicle charging stations (EVCS).

SWEET PATHFNDR (funding agency: Swiss Federal Office of Energy’s ``SWEET’’ program) link

Modeling and control of multi-energy systems. Validation of multi-grid dispatch framework.

REEL Demonstrator (funding agency: Swiss Federal Office of Energy’s ``SCCER-FURIES’’ program) link

• Validation of OPF-based real-time control algorithm on a real-life medium voltage distribution network in Aigle, Switzerland, hosting 2.5MWh/1.5MW battery storage capacity, 3.2MWp photovoltaic, 3.4 MVA hydro and 2.8MW base demand.
• Development of the software for the operation of the battery energy storage system for real-time control.

Joint Activity Scenario and Modelling (funding agency: Swiss Federal Office of Energy, Innosuisse) link

• Providing a set of robust scenarios for realizing the Swiss Energy Strategy 2050.
• Assessment of photovoltaic generation hosting capacity for the power distribution networks of Switzerland.
• Computing cost-optimal placement of energy storage systems for different levels of photovoltaic generation.

Talks & Lectures

Invited

• Joint US-European Workshop on Flexible Electric Grid Critical Infrastructure for Resilient Society, Temple University Conference Center, April 21-22, 2023, Philadelphia, PA.
• The 7th Purple Mountain Forum Panel Session - Advanced Optimization and Control Methods towards a Carbon Neutral Energy Internet, Nanjing China (Virtual): Grid aware Model Predictive Control of Distributed Energy Resources in a Distribution network Theory and Experimental Validation, Gupta, R., 2022.

Conference presentations

• Experimental validation of model-less robust voltage control using measurement-based estimated voltage sensitivity coefficients. IEEE Belgrade PowerTech, 2023.
• Performance comparison of alternating direction optimization methods for linear-opf based real-time predictive control. IEEE Madrid PowerTech. 2021.
• Performance assessment of linearized opf-based distributed real-time predictive control. IEEE Milan PowerTech, 2019.
• An admm-based coordination and control strategy for pv and storage to dispatch stochastic prosumers: Theory and experimental validation. Power Systems Computation Conference (PSCC), 2018.

Publications

Journals

1. Rahul Gupta. Quantifying uncertainty on the power-flow sensitivity coefficients from uncertain branches parameters and noisy grid-state measurements. IEEE Transactions on Instrumentation and Measurement, 2023 Link
2. Rahul Gupta, Fabrizio Sossan, and Mario Paolone. Optimal sizing and siting of energy storage systems considering curtailable photovoltaic generation in power distribution networks. Applied Energy, 339, 2023. Link
3. Rahul Gupta, Antonio Zecchino, Ji-Hyun Yi, and Mario Paolone. Reliable dispatch of active distribution networks via a two-layer grid-aware model predictive control. IEEE Open Access Journal of Power and Energy, 2022. Link
4. Rahul Gupta, Sherif Fahmy, and Mario Paolone. Coordinated day-ahead dispatch of multiple power distribution grids hosting stochastic resources: An admm-based framework. Electric Power Systems Research, 212:108555, 2022. Link
5. Rahul Gupta, Fabrizio Sossan, and Mario Paolone. Model-less robust voltage control in active distribution net- works using sensitivity coefficients estimated from measurements. Electric Power Systems Research, 212:108547, 2022 Link
6. Francesco Gerini, Yihui Zuo, Rahul Gupta, Antonio Zecchino, Zhao Yuan, Elena Vagnoni, Rachid Cherkaoui, and Mario Paolone. Optimal grid-forming control of battery energy storage systems providing multiple services: Modeling and experimental validation. Electric Power Systems Research, 212:108567, 2022. Link
7. Rahul Gupta, Fabrizio Sossan, Jean-Yves Le Boudec, and Mario Paolone. Compound admittance matrix estima- on of three-phase untransposed power distribution grids using synchrophasor measurements. IEEE Transactions on Instrumentation and Measurement, 70:1–13, 2021. Link
8. Rahul Gupta, Fabrizio Sossan, and Mario Paolone. Countrywide pv hosting capacity and energy storage re- requirements for distribution networks: The case of Switzerland. Applied Energy, 281:116010, 2021. Link
9. Rahul Gupta, Fabrizio Sossan, and Mario Paolone. Grid-aware distributed model predictive control of hetero- neous resources in a distribution network: Theory and experimental validation. IEEE Transactions on Energy Conversion, 36(2):1392–1402, 2020. Link
10. Sherif Fahmy, Rahul Gupta, and Mario Paolone. Grid-aware distributed control of electric vehicle charging stations in active distribution grids. Electric Power Systems Research, 189:106697, 2022. Link
11. Fabrizio Sossan, Enrica Scolari, Rahul Gupta, and Mario Paolone. Solar irradiance estimations for modeling the variability of photovoltaic generation and assessing violations of grid constraints: A comparison between satellite and pyranometers measurements with load flow simulations. Journal of Renewable and Sustainable Energy, 11(5):056103, 2019. Link

Conference

1. Rahul Gupta, and Mario Paolone. (2023). Experimental validation of model-less robust voltage control using measurement-based estimated voltage sensitivity coefficients. In 2023 IEEE Belgrade PowerTech, pages 1–8. IEEE, 2023. Link
2. Rahul Gupta, Vladimir Sovljanski, Fabrizio Sossan, and Mario Paolone. Performance comparison of alternating direction optimization methods for linear-opf based real-time predictive control. In 2021 IEEE Madrid PowerTech, pages 1–6. IEEE, 2021. Link
3. Rahul Gupta, Fabrizio Sossan, and Mario Paolone. Performance assessment of linearized opf-based distributed real-time predictive control. In 2019 IEEE Milan PowerTech, pages 1–6. IEEE, 2019. Link
4. Rahul Gupta, Fabrizio Sossan, Enrica Scolari, Emil Namor, Luca Fabietti, Colin Jones, and Mario Paolone. An admm-based coordination and control strategy for pv and storage to dispatch stochastic prosumers: Theory and experimental validation. In 2018 Power Systems Computation Conference (PSCC), pages 1–7. IEEE, 2018. Link