ITRI-Rosenfeld Postdoc Fellowship Candidate Seminar: Model-free and Communication-light Control Strategies for Intelligent Devices in DistributiSystems
The desire to connect large amounts of renewables to the electric power distribution system, coupled with the emergence of a diverse set of actionable resources, necessitate the development of control strategies that can coordinate heterogeneous devices for a common goal. Many approaches for controlling such components in distribution systems are framed as centralized control/optimization problems, where a single decision-maker collects all relevant information, computes a decision, and disseminates control signals to actuators. While these methods can, theoretically, achieve very high levels of performance, they suffer from two critical pitfalls: 1) lack of suitable models, and 2) large communications requirements. These burdens hinder the ability of such strategies to be implemented in the field. In this talk, I will present initial efforts towards developing model-free and communications-light control strategies that address important objectives such as loss minimization and voltage regulation in distribution systems. The methods I will present aim to achieve high levels of performance associated with centrally-based approaches, while maintaining decentralized decision-making. In addition, I will outline a future research agenda to facilitate further development of model-free and communications-light control strategies in high PV penetration scenarios.
Energy/Environmental Policy Research Scientist/Engineer, Grid Integration Group, Energy Storage & Distributed Resources Division, Distribution Grid
Daniel Arnold received the B.S. degree in mechanical engineering from the University of California, San Diego, in 2005, the M.S. degree in engineering science from the University of California, San Diego, in 2006. From 2006 to 2009 he was conducted research and development of unmanned underwater vehicles for the United States Navy. He then received his Ph.D. from the Mechanical Engineering Dept. at the University of California, Berkeley in 2015. He is currently a 2015 ITRI-Rosenfeld Postdoctoral Fellow at the Lawrence Berkeley National Laboratory. Presently, his research focuses on the development of control strategies for the management of distributed energy resources in electric power distribution systems. Additionally, he is studying the application of machine learning techniques to analyze high resolution distribution system Phasor Measurement Unit (PMU) data. His research interests include controls, optimization, power systems, and robotics.