AC optimal power flow (AC-OPF) problems need to be solved more frequently in the future to
maintain stable and economic power system operation. To tackle this challenge, a deep …

Power dispatch is a core problem for smart grid operations. It aims to provide optimal
operating points within a transmission network while power demands are changing over …

Machine learning assisted optimal power flow (OPF) aims to reduce the computational
complexity of these non-linear and non-convex constrained optimization problems by …

Due to the high nonlinearity of AC optimal power flow (OPF), numerous efforts have been
made in recent decades to find efficient methods. Machine learning (ML) has proven to …

AC optimal power flow (AC-OPF) is a significant problem in the economic operation of power
systems. Traditional AC-OPF calculation methods only consider a specific operation pattern …

Increasing levels of renewable generation motivate a growing interest in data-driven
approaches for AC optimal power flow (AC OPF) to manage uncertainty; however, a lack of …

Optimal power flow (OPF) is a crucial tool in the operation and planning of modern power
systems. However, as power system optimization shifts towards larger-scale frameworks …

This paper introduces a framework to capture previously intractable optimization constraints
and transform them to a mixed-integer linear program, through the use of neural networks …

Recently there has been a surge of interest in adopting deep neural networks (DNNs) for
solving the optimal power flow (OPF) problem in power systems. Computing optimal …

This article addresses the challenge of efficiently recovering exact solutions to the optimal
power flow problem in real-time electricity markets. The proposed solution, named Physics …