Daniel Arnold

Arnold's research focuses on improving distributed energy systems' stability and security by using emerging data and computational science tools, including autonomous control, artificial intelligence, and machine learning. Looking to the future, he intends to continue and extend his work on power and energy systems, and also to expand his work to include control and optimization of cyber-physical systems more broadly. Some of Arnold's key research contributions stem from work to mitigate attacks or unintentional outages in energy systems. He has developed strategies that enable real-time control of the methods to contain attacks and prevent system destabilization. He has done this by developing algorithms for adaptive control that utilize non-compromised components of the system. Initial applications of his work include ensuring the security of distributed systems, like home batteries and rooftop solar systems, to prevent large-scale outages and blackouts. Still, the methods can be extended to distributed interdependent systems more broadly.