Hello! My name is Bennet Meyers. I’m a Senior Researcher with the National Renewable Energy Lab and an Adjunct Professor in Electrical Engineering at Stanford University. My research is focused on mathematical optimization for signal processing, estimation, and control with applications in energy. I am particularly interested in the large-scale management and grid integration of renewable power generation. I am also interested in auditable, computationally efficient algorithms and the development of so-called “white-box” machine learning approaches.

I completed my PhD in Electrical Engineering at Stanford University in 2023, advised by Stephen Boyd. We recently wrote a book on signal decomposition (publisher’s page). On December 8, 2022, I successfully defended my dissertation.

Since 2018, I have been running the PVInsight project for SETO, developing tools to solve digital operations and maintence problems in the solar PV industy. Some of these tools can be found here.

Since 2024, I have been running the REGROW (renewable energy generator risk under outlier weather) project for the Office of Electricity Grid Controls Division. In this project, we are modeling severe weather and the adverse impacts on renewable generation and grid operations. We are developing renewable probabilistic risk forecasting models and robust battery planning and control methods to handle these outlier weather conditions.

Both these projects are currently active and ongoing. If you like what you see, feel free to contact me!

Papers and code

An up-to-date list of my papers is available on Google Scholar. Related software and code is available on GitHub.

Contact me

My email address is bennet.meyersim [at] nrel [dot] gov or bennetm [at] stanford [dot] edu. If I do not respond right away, please try again, I probably just missed your message. You are welcome to try my Twitter or LinkedIn, which are linked below, but I generally don’t respond to cold messages there.