Optimal Feedback Control Architecture for Power Systems with High Penetration of Renewables

Zoom Link for remote participants, password ECECAN

Abstract: The increasing penetration of renewable energy resources (RES) in power systems is bringing about unprecedented changes to the current operation scheme. As penetration levels of RESs reach a substantial fraction of the total supplied power, the current power systems will face high operational risks due to the stochastic nature of renewables. This will call for specific approaches to tackle the uncertainties in different operational layers and tasks of power systems with significant time-scale separation.

This talk presents an optimal feedback control architecture for power systems to model and manage the uncertainties in transmission systems and distribution networks under different time scales. In the first part of his talk, a data-based stochastic optimal power flow (OPF) for transmission systems will be presented, by closing a loop between the real-time dispatch decision of power plants and the structural information of wind forecasts. Next, he will show an online optimization-estimation joint architecture for extremely large-scale distribution networks with insufficient monitoring infrastructure. In the second part of this talk, he will present a novel stochastic swing equation where the low- and time-varying inertia parameters are modeled as multiplicative noises of a linear dynamical system. The analysis results show that a mean-square stability condition is closely related to the variation of inertia parameters and the network topology. A wide-area frequency feedback control with a sparse structure is proposed to stabilize the system for mean-square stability.

Bio: He is currently an ETH Postdoctoral Fellow at the Power Systems Laboratory (PSL) at ETH Zürich, Zürich, Switzerland. He received his B.S. degree in Electrical Engineering from Xi’an Jiaotong University, Xi’an, China, in 2013 and an M.S. degree in Electrical Engineering from The University of Michigan, Dearborn, MI, USA, in 2015. He received an M.S. and his Ph.D. degree in Mechanical Engineering at The University of Texas at Dallas, Richardson, TX, USA, in 2020. He was a summer research intern at National Renewable Energy Laboratory (NREL) in 2019.  He received a Best Paper Award from IEEE Transactions on Power Systems for papers published between 2017-2019. His research interests are control and optimization in networks, with applications to electric power networks, water networks, and multi-energy networked systems.