The ideas in this paper are motivated by an increased need for systematic data-enabled
resource management of large-scale electric energy systems. The basic control objective is …

This paper addresses the problem of overloading in power distribution networks, which
stems from the transmission systems being incapable of delivering power from source to …

This paper introduces a fundamental energy-based modeling framework for complex electric
energy systems. This approach captures dynamic interactions within such systems in terms …

With recent trends in computation and communication architecture, it is becoming possible
to simulate complex networked dynamical systems by employing high-fidelity models. The …

Large-scale computing, including machine learning (MI) and AI, offer a great promise in
enabling sustainability and resiliency of electric energy systems. At present, however, there …

In this paper we propose a multi-layered method for estimating the grid admittance matrix
with a limited number of measurement devices. Via the proposed multi-layered process with …

Model Predictive Control (MPC) is a well-established technique for process control. It is
based on a dynamical model that is used to predict and optimize the behavior of a …

This paper points out some key drawbacks of today's modeling and control underlying
hierarchical electric power system operations and planning as the hidden roadblocks on the …

This paper concerns a difficult multidisciplinary problem of data-enabled sustainable and
resilient electric energy service. Taking the view of the changing electric energy systems as …

Feedback optimization (FO) is a control paradigm that is gaining popularity for the optimal
steady-state operation of complex systems through the use of optimization algorithms in …