CPS: TTP Option: Small: Adaptive Charging Network Research Portal

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This project is motivated by challenges in future energy cyber-physical systems (CPS). It will build a one-of-a-kind research facility that will enable new CPS research on smart grid and electric vehicles. It will advance the state of the art in the clean-energy space and facilitate the development and adoption of these technologies. The result of this project will be integrated with the power system analysis course at California Institute of Technology (Caltech). Preliminary work on this project has already been used at Caltech and other places around the world for classroom projects as well as smart grid research. This project will equip a new generation of students with the passion and the interdisciplinary knowledge for tackling one of the biggest challenges of our time. A seed community of contributors and users has already formed organically. This project will grow this open-source community. The PI's Lab has been working with a Caltech startup and Caltech Facilities department to design, deploy, and manage an Adaptive Charging Network (ACN) for electric vehicles at one of Caltech's parking garages. The primary goal of this project is to develop a suite of open-source software and hardware that will make Caltech ACN not just a production facility, but also a live testbed for CPS researchers at, and outside, Caltech. A secondary goal is to use the ACN Research Portal to study the joint optimization of distributed energy resources to provide both charging service to electric vehicles as well as energy services to electricity markets and utility companies. The key idea is to treat the production ACN as a physical layer and create an inter- mediate layer, called the ACN Research Portal, to allow safe, secure and easy access to charging data as well as push of charging commands for real-world testing of new algorithms on ACN. It will make large high-resolution charging data, data-driven simulator and experimental platform publicly available for the first time. This will allow CPS researchers to learn detailed statistical models, perform data analysis of real-world charging behavior, and easily and fairly compare control algorithms in a common platform driven by detailed real data. This is currently impossible.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.