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Tuofei Chen
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Francis Chen

Ph.D. Student in Electrical Engineering, admitted Autumn 2017

TomKat Graduate Fellow for Translational Research

Research Lab: William Dally

Year Awarded: 2020


Tuofei (Francis) Chen is a PhD Candidate in the Electrical Engineering Department at Stanford. He is advised by Prof. Bill Dally and his research interest lies in design, modeling and control of multilevel power electronics converters for renewable energy systems. Francis came from Shenzhen, China, where the world largest electronic component markets in Huaqiang Bei (华强北) sparked his interest in electrical engineering from a young age. He obtained his BS and MS in EE from Northwestern University, where he worked under Prof. Aggelos Katsaggelos in the Image and Video Processing Lab. He has also worked for Tesla and Johnson Controls to develop their battery management systems.

A Novel Three Phase Multilevel Inverter for the Future Power Grid

The electric grid is undergoing rapid technology change in response to increasing renewable energy resources, deployment of stationary storage systems and large numbers of electric vehicles (EVs). High-voltage, high-power electronic inverters are critical for this transformation. New inverters must be efficient, compact and highly controllable to provide grid services. Multilevel inverter (MLI) that series connect multiple inverter outputs to directly interface with the medium voltage grid is a promising transformer-less alternative to central inverters widely adopted today.  However, simple and effective control of multilevel converters remains challenging due to the more complex system dynamics.  We propose a novel design of a three-phase MLI for utility-scale PV applications. Our design leverages constant three phase AC power to eliminate the need for bulky DC link capacitors, while only requiring each PV string to be connected to two of three phases. This novel and economical converter topology is enabled via multiple-input, multiple-output (MIMO) control methods that ensure the PV arrays are operating at their maximum power and feeding into the grid with high power quality. The modeling and control techniques developed through this research can also be used to control and coordinate aggregated generators/loads such as EV charging stations, solid-state transformers, stationary battery systems, etc. We seek to address the sustainability challenge by advancing grid-tied MLI design to allow more efficient, compact and controllable integration of clean energy resources.