Abstract: 

We developed a feedback-based methodology for solving power network optimization. The main idea is to outsource complicated real-time computation from physical measurements, which leads to a distributed architecture that features guaranteed convergence and optimality as well as enhanced scalability and responsiveness under increased penetration of distributed energy resources and variable renewable generation. In this talk, I will interpret the proposed methodology with two novel designs of power network optimization and control schemes. The first design is an optimal frequency control scheme that can stabilize a power network at an optimal equilibrium satisfying frequency and power flow security requirements at minimal cost. The second design is a hierarchical distributed scheme to solve an optimal power flow problem, which dispatches distributed energy resources for voltage regulation at minimum cost in multiphase distribution networks. 

About the speaker :

Dr. Changhong Zhao will join the Department of Information Engineering, the Chinese University of Hong Kong, as an Assistant Professor. His research interests include distributed control of network systems, real-time convex and nonconvex optimization, smart power grid, multi-energy systems, and smart-city infrastructure. 

Changhong received BE degree in Automation from Tsinghua University in 2010 and PhD degree in Electrical Engineering from Caltech in 2016. His PhD thesis received two Best Thesis Awards from Caltech EE Department and Engineering Division. From 2016 to 2019, he worked as a researcher at the National Renewable Energy Laboratory, Colorado, USA, where he led multiple projects on control and optimization of smart grid in collaboration with US Department of Energy and academic and industry partners.