11 papers
Choose Wisely: Data-driven Predictive Control for Nonlinear Systems Using Online Data Selection
Joshua Näf, Keith Moffat, Jaap Eising +1
This paper proposes Select-Data-driven Predictive Control (Select-DPC), a new method for controlling nonlinear systems using output-feedback for which data are available but an exp…
Revisiting Power System Stabilizers with Increased Inverter-Based Generation: A Case Study
Jovan Krajacic, Keith Moffat, Gustavo Valverde
As power systems evolve with increasing production from Inverter-Based Resources (IBRs), their underlying dynamics are undergoing significant changes that can jeopardize system ope…
Model-Free Power System Stability Enhancement with Dissipativity-Based Neural Control
Yifei Wang, Han Wang, Kehao Zhuang +2
The integration of converter-interfaced generation introduces new transient stability challenges to modern power systems. Classical Lyapunov- and scalable passivity-based approache…
Data-Driven Predictive Control for Wide-Area Power Oscillation Damping
Giacomo Mastroddi, Jan Poland, Mats Larsson +1
We study damping of inter-area oscillations in transmission grids using voltage-source-converter-based high-voltage direct-current (VSC-HVDC) links. Conventional power oscillation…
PRIME: Fast Primal-Dual Feedback Optimization for Markets with Application to Optimal Power Flow
Nicholas Julian Behr, Mattia Bianchi, Keith Moffat +2
Online Feedback Optimization (OFO) controllers iteratively drive a plant to an optimal operating point that satisfies input and output constraints, relying solely on the input-outp…
Robust Feedback Optimization with Model Uncertainty: A Regularization Approach
Winnie Chan, Zhiyu He, Keith Moffat +3
Feedback optimization optimizes the steady state of a dynamical system by implementing optimization iterations in closed loop with the plant. It relies on online measurements and l…