Mathematical optimization is one of the cornerstones of modern engineering research and
practice. Yet, throughout all application domains, mathematical optimization is, for the most …

We develop, in this paper, a machine learning approach to optimize the real-time operation
of electric power grids. In particular, we learn feasible solutions to the AC optimal power flow …

Electric power systems are taking drastic advances in deployment of information and
communication technologies; numerous new measurement devices are installed in forms of …

With a large-scale integration of distributed energy resources (DERs), distribution systems
are expected to be capable of providing capacity support for the transmission grid. To …

Distributed energy resources (DERs)-which can include solar photovoltaic (PV), fuel cells,
microturbines, gensets, distributed energy storage (eg, batteries and ice storage), and new …

In this paper, we propose a distributed voltage control in power distribution networks through
reactive power compensation. The proposed control can operate in a distributed fashion …

Adaptive robust optimization (ARO) is a well-known technique to deal with the parameter
uncertainty in optimization problems. While the ARO framework can actually be borrowed to …

With the increasing penetration of distributed energy resources such as photovoltaics (PVs),
frequent voltage and congestion problems are expected to occur in distribution grids …

This paper proposes a Lyapunov optimization-based online distributed (LOOD) algorithmic
framework for active distribution networks (ADNs) with numerous photovoltaic inverters and …

This paper proposes a data-driven and fully distributed volt/var control (VVC) method for
active distribution networks (ADNs) with multiple virtual power plants (VPPs), which is model …