Electric power systems are moving toward more decentralized models, where energy
generation is performed by small and distributed power plants, often from renewables. With …

Today's power systems are seeing a paradigm shift under the energy transition, sparkled by
the electrification of demand, digitalisation of systems, and an increasing share of …

The increasing integration of variable renewable energy resources through power
electronics has brought about substantial changes in the structure and dynamics of modern …

Digitalization is one of the key drivers for energy system transformation. The advances in
communication technologies and measurement devices render available a large amount of …

This paper presents a novel, unified approach for generating high-quality datasets for
training machine-learned models for real-time security assessment in power systems …

Distribution factors (DFs) are vital for power system monitoring and secure operation.
However, it is challenging to accurately estimate dominant DFs while promoting the sparsity …

Abstract Machine learning (ML) for real-time security assessment requires a diverse training
database to be accurate for scenarios beyond historical records. Generating diverse …

Over the years, electricity has developed into a crucial commodity for any nation. The need
to evaluate the rate of electricity consumption in regard to utility management and the spatial …

This paper proposes a novel data-driven algorithm for measurement-based coherency
detection in power systems, which is based on Monte Carlo Consensus Clustering (M3C) …

As power systems evolve from synchronous to inverter-based generation, short-term voltage
stability evaluation plays an increasingly important role. Voltage perturbations become faster …