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Varsha N. Behrunani

Varsha N. Behrunani
Varsha N. Behrunani
PhD Student
ETH Zurich, Empa
varsha.behrunani@empa.ch
Curriculum Vitae
Collaboration sparks innovation. This is the chance for me to work with and learn from people with similar interests, as we work toward the same goals.

Varsha N. Behrunani is a PhD candidate in NCCR Automation. She is supervised by Prof. John Lygeros at Automatic Control Lab in ETH Zurich in collaboration with Dr. Kristina Orehounig at Empa. She holds a B.Sc. in Electrical Eng. from the Rochester Institute of Technology, NY from its satellite campus in Dubai, UAE. She previously worked as an electrical and project engineer in different companies including Schneider electric and Nestle Manufacturing. She received her M.Sc. in Electrical Eng. from ETH Zürich in September 2020. Her research interests are in the field of the control of power systems and her work is focused on data-based decentralized control of multi-energy systems including the coordination of multiple stakeholders within the system.

Scientific Publications

Published
Efficient sample selection for safe learning
ArXiv
Marta Zagorowska, Efe C. Balta, Varsha N. Behrunani, Alisa Rupenyan, John Lygeros
Collection
Published
Control of Multicarrier Energy Systems from Buildings to Networks
Annual Review of Control, Robotics, and Autonomous Systems
Vol 6 No 1 Pages 391-414
Roy Smith, Varsha N. Behrunani, John Lygeros
Doi.org Collection

Research projects as Researcher

Title
Principal Investigators

Decentralized control of multi-energy systems

Kristina Orehounig, John Lygeros

Summary

Electrical, thermal and chemical processes follow individual demand and supply patterns under distinct time scales, from sub-second (electrical) to weekly (thermal) and seasonal (chemical) applications. In these applications, digitalization enables a coordination of the related technologies. So, next to sector specific technological limitations, the systemic coupling of energy carriers needs to take into account  the coupling of different time scales as well as different production and consumption patterns. As the technological landscape is getting more decentral in terms of energy production, also more stakeholders are involved in the energetic supply chain. These actors can benefit if they share information on their capabilities and intended production and consumption. Moreover, information sharing and local decision making could potentially reduce the need for extending large-scale infrastructure, such as transmission grids or international imports of energy. The project investigates the use of distributed decision making and control methods to address the large scale nature of the problem, as well as data driven methods to deal with the uncertainty inherent in the problem. Validation of the methodological approach is foreseen on the NEST building at Empa.

People involved

Varsha N. Behrunani
Philipp Heer
Kristina Orehounig, John Lygeros, Varsha N. Behrunani, , Philipp Heer
Decentralized control of multi-energy systems
Kristina Orehounig, John Lygeros

Electrical, thermal and chemical processes follow individual demand and supply patterns under distinct time scales, from sub-second (electrical) to weekly (thermal) and seasonal (chemical) applications. In these applications, digitalization enables a coordination of the related technologies. So, next to sector specific technological limitations, the systemic coupling of energy carriers needs to take into account  the coupling of different time scales as well as different production and consumption patterns. As the technological landscape is getting more decentral in terms of energy production, also more stakeholders are involved in the energetic supply chain. These actors can benefit if they share information on their capabilities and intended production and consumption. Moreover, information sharing and local decision making could potentially reduce the need for extending large-scale infrastructure, such as transmission grids or international imports of energy. The project investigates the use of distributed decision making and control methods to address the large scale nature of the problem, as well as data driven methods to deal with the uncertainty inherent in the problem. Validation of the methodological approach is foreseen on the NEST building at Empa.

Varsha N. Behrunani
Philipp Heer
Kristina Orehounig, John Lygeros, Varsha N. Behrunani, , Philipp Heer
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34ab7ee3-eae2-4be6-a009-595eb7b858b4

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