Daniel Arnold

Daniel Arnold serves as an Adjunct Professor in the Department of Civil and Environmental Engineering within the College of Engineering at the University of California, Berkeley. He maintains a dual affiliation with Lawrence Berkeley National Laboratory (LBNL), where he conducts research within the Energy Storage & Distributed Resources Division's Grid Integration Group. His work bridges academic research with practical applications in power systems engineering.

Arnold's educational background includes a Ph.D. in Mechanical Engineering from UC Berkeley (2015), an M.S. in Engineering Science from UC San Diego (2006), and a B.S. in Mechanical Engineering from UC San Diego (2005). This multidisciplinary foundation supports his research at the intersection of electrical engineering, control systems, and data science.

His research focuses on developing innovative control strategies for managing distributed energy resources in electric power distribution systems, with particular emphasis on applying machine learning techniques to analyze high-resolution distribution system Phasor Measurement Unit (PMU) data. Arnold is recognized as an emerging leader in using modern data science tools, including artificial intelligence, machine learning, and control theory, to improve the stability and security of energy and power systems. His work addresses critical challenges in grid security, including developing algorithms to mitigate attacks or unintentional outages by enabling real-time control that utilizes non-compromised system components.

Analysis of his publication record reveals a consistent focus on extremum seeking control applications for power systems, distributed energy resource management, and cybersecurity in grid operations. His research has evolved from foundational work on smart inverter control (2015) to increasingly sophisticated approaches integrating machine learning with power system operations and addressing cyber-physical security challenges.

Arnold actively contributes to the professional community through service as a peer reviewer for leading journals, leadership of conference sessions, and participation in application-oriented workshops aimed at translating research into practical solutions. His work at Lawrence Berkeley National Laboratory complements his academic role, providing a platform for large-scale implementation of his research findings.

His laboratory work primarily involves power hardware-in-the-loop testing and simulation of distribution systems, with applications focused on ensuring the security of distributed systems like home batteries and rooftop solar systems to prevent large-scale outages and blackouts. This research has significant implications for grid resilience in the face of increasing distributed energy resource penetration.