Advancements in digital automation for smart grids have led to the installation of
measurement devices like phasor measurement units (PMUs), micro-PMUs (-PMUs), and …

The increasing integration of distributed energy resources has led to heightened complexity
in distribution network models, posing challenges of uncertainty and volatility to the …

Accurate and efficient power flow (PF) analysis is crucial in modern electrical networks'
operation and planning. Therefore, there is a need for scalable algorithms that can provide …

This letter proposes a novel data-driven probabilistic physics-informed graph convolutional
network (GCN) for active distribution system voltage prediction with PVs and EVs. It …

The effective representation, processing, analysis, and visualization of large-scale structured
data over graphs, especially power grids, are gaining a lot of attention. So far most of the …

Understanding spatiotemporal correlations in power systems is crucial for maintaining grid
stability, reliability, and efficiency. By discerning connections between spatial and temporal …

Power system state estimation is a primary and major method for monitoring power grids in
real time. Massive synchrophasor data contains temporal correlations and spatial …

Accurate and timely prediction of power system states is one of the most important
challenging tasks in modern power systems. Considering the integration of renewable …

This paper proposes an analytic neural network Gaussian process (NNGP)-based chance-
constrained real-time voltage regulation method for active distribution systems with …

The deployment of microphasor measurement units, supervisory control and data
acquisition systems, and smart meters has revolutionized distribution systems, moving …