Wang, WenbinHe, ZhiyuBelgioioso, GiuseppeBolognani, SaverioDörfler, Florian2025-05-282025-05-282025-05-242024-12-1610.1109/cdc56724.2024.10886448https://infoscience.epfl.ch/handle/20.500.14299/250839Online feedback optimization (OFO) enables optimal steady-state operations of a physical system by employing an iterative optimization algorithm as a dynamic feedback controller. When the plant consists of several interconnected subsystems, centralized implementations become impractical due to the heavy computational burden and the need to pre-compute system-wide sensitivities, which may not be easily accessible in practice. Motivated by these challenges, we develop a fully distributed model-free OFO controller, featuring consensus-based tracking of the global objective value and local iterative (projected) updates that use stochastic gradient estimates. We characterize how the closed-loop performance depends on the size of the network, the number of iterations, and the level of accuracy of consensus. Numerical simulations on a voltage control problem in a direct current power grid corroborate the theoretical findings.text::conference output::conference proceedings::conference paper