Distribution systems are integrating a growing number of distributed energy resources and
converter-interfaced generators to form active distribution networks (ADNs). Numerous …

Many power system operation and planning problems use the DC power flow approximation
to address computational challenges from the nonlinearity of the AC power flow equations …

The power flow equations are fundamental to power system planning, analysis, and control.
However, the inherent non-linearity and non-convexity of these equations present …

The DistFlow model accurately represents power flows in distribution systems, but the
model's nonlinearities result in computational challenges for many optimization applications …

The power flow equations are central to many problems in power system planning, analysis,
and control. However, their inherent non-linearity and non-convexity present substantial …

This is the second part of a two-part tutorial on data-driven power flow linearization (DPFL).
The motivations, challenges, and training algorithms for DPFL were reviewed and discussed …

The inherent nonlinearity of the power flow equations poses significant challenges in
accurately modeling power systems, particularly when employing linearized approximations …

This paper proposes a novel physics-data-driven method for the linearization of AC power
flow equations in the context of topological remedial actions. As opposed to physics-based …

This work presents an efficient data-driven method to construct probabilistic voltage
envelopes (PVE) using power flow learning in grids with network contingencies. First, a …

El Flujo de Cargas Optimo (OPF) es un problema de optimización cuyo objetivo es
determinar el despacho de potencia de las centrales generadoras de una red eléctrica para …