Due to the nonlinear and non-convex attributes of the optimization problems in power
systems such as Optimal Power Flow (OPF), traditional iterative optimization algorithms …

To cope with increasing uncertainty from renewable generation and flexible load, grid
operators need to solve alternative current optimal power flow (AC-OPF) problems more …

Non-convex AC optimal power flow (AC-OPF) is a fundamental optimization problem in
power system analysis. The computational complexity of conventional solvers is typically …

This paper introduces, for the first time to our knowledge, physics-informed neural networks
to accurately estimate the AC-Optimal Power Flow (AC-OPF) result and delivers rigorous …

We develop a Deep Neural Network (DNN) approach, namely DeepOPF, for solving optimal
power flow (OPF) problems that are critical for daily power system operation. DeepOPF …

Optimal power flow (OPF) is at the heart of many power system operation tools and market
clearing processes. Several mathematical and heuristic approaches have been presented in …

With the increasing penetration of renewable energy, power grid operators are observing
both fast and large fluctuations in power and voltage profiles on a daily basis. Fast and …

Abstract The Optimal Power Flow (OPF) problem is a fundamental building block for the
optimization of electrical power systems. It is nonlinear and nonconvex and computes the …

Optimal Power Flow (OPF) is a fundamental problem in power systems. It is computationally
challenging and a recent line of research has proposed the use of Deep Neural Networks …

The dc optimal power flow (DCOPF) problem is a fundamental problem in power systems
operations and planning. With high penetration of uncertain renewable resources in power …