Ashwin Balakrishna Receives 2017 Henry Ford II Scholar Award
Electrical Engineering student Ashwin Balakrishna, advised by Professor Steven Low is a recipient of the 2017 Henry Ford II Scholar Award. He enjoys interdisciplinary research with a focus on intelligent systems. He has been using machine learning to improve sensor based systems in different contexts including medical diagnostics, electrical vehicle charging, and earthquake detection. The Henry Ford II Scholar Award is funded under an endowment provided by the Ford Motor Company Fund. The award is made annually to engineering students with the best academic record at the end of the third year of undergraduate study.
Henry Ford II Scholar Award
Caltech’s Smart Charging Network for Electrical Vehicles
Charging electric vehicles (EVs) can require a substantial amount of electricity (most EVs charge at 7 kilowatts, the equivalent of simultaneously running 70 desktop computers). Steven Low, Professor of Computer Science and Electrical Engineering, has developed Caltech's adaptive charging network, which uses a smart algorithm to coordinate the charging schedule with the Institute's existing electrical infrastructure. This program helps minimize energy usage and about 30 percent of the electricity at each charging station is from carbon-free renewable sources. [Caltech story]
Next-Generation Distribution Infrastructure
Caltech’s smart grid team led by Professors John Doyle, Steven Low, and Adam Wierman along with their collaborators have been awarded $3.9 million for an Advanced Research Projects Agency - Energy (ARPA-E) Network Optimized Distributed Energy System (NODES) project entitled "Real-time Optimization and Control of Next-Generation Distribution Infrastructure." NODES is ARPA-E’s new program focused on enabling more than 50% usage of renewable power on the grid. The Caltech team will develop a comprehensive distribution network management framework that unifies real-time voltage and frequency control at the home/distributed energy resource controllers’ level with network-wide energy management at the utility/aggregator level. [Learn more]