Welcome! I am a Ph.D. student advised by Assistant Professor Dominic Groß. My work is motivated by decarbonization of the electricity sector and lies within the nexus of power electronics, power systems, and control theory research. At UW-Madison, I am studying the dynamics of large-scale power grids with high penetrations of inverter-based resources. I am interested in understanding how emerging inverter control technologies, such as grid-forming control, impact the stability and performance of transmission systems. My current focus is on developing device-level specifications that guarantee stable interactions between next-generation inverter-based resources and existing network devices, thus achieving interoperability. Additionally, I am pursuing an Energy Analysis and Policy graduate certificate to understand the energy and environmental justice implications of the energy transition. My goal is to accelerate the global transition toward a reliable, resilient, affordable, and fully renewable grid.
Projects
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Universal Input-Output Model of Grid-Forming Functions and Data-Driven Verification Methods
The UNIFI Consortium has identified system- and unit-level functional requirements and performance criteria that ensure interoperability of grid-forming inverter-based resources in electric power systems at any scale without requiring vendors or system operators to reveal proprietary information in. It is then necessary to translate these high-level principles into rigorous mathematical specifications that can be enforced and validated across a wide range of devices and systems. While it is challenging to establish uniform vendor-agnostic specifications for the growing number and complexity of implementations of GFM and IBR technologies, input-output modeling can support the development of universal reduced-order models of GFM functions parameterized by general network and control variables. By observing the dynamic behavior of a GFM IBR at its terminals and only considering signals that can be experimentally collected, it is possible to identify salient GFM functions without details on hardware or controls. Input-output data can be obtained using hardware experiments and blackbox models and form the basis for developing data-driven verification methods. The input-output modeling framework is envisioned to help formulate and validate specifications that bound GFM dynamics within which vendors can innovate while interoperability and stability (e.g., frequency and voltage magnitude) are guaranteed.
In Jan. 2023 at the UNIFI Consortium’s Team Meeting, I presented a poster on this work and received a “Best Poster” award.
Universal Input-Output Model of Grid-Forming Functions and Data-Driven Verification Methods
Publications
On Campus
NSF Graduate Research Fellowship Program (GRFP): In 2023, I was awarded an NSF fellowship to support my research at UW-Madison.
Graduate Engineering Research Scholars (GERS): I am a research fellow with the GERS program, which was founded to support underrepresented graduate students within the College of Engineering at UW-Madison.
Energy Analysis and Policy (EAP) Program: In 2022, I was awarded the Wes and Ankie Foell Scholarship to support my EAP studies.
Jennifer Bui
In 2020, I earned an honors B.Sc. in Engineering and Physics, a joint program between the School of Engineering and the Department of Physics, from Brown University. My thesis, titled "Design and Optimization of a Solar Photovoltaic with Storage System," documented my work for the Solar District Cup -- a national collegiate competition.
I grew up on the East and West coasts. I love all things dessert and knitting.