Most existing data-driven power system short-term voltage stability assessment (STVSA)
approaches presume class-balanced input data. However, in practical applications, the …

As failure data is usually scarce in practice upon preventive maintenance strategy in
prognostics and health management (PHM) domain, transfer learning provides a …

In a modern power system with an increasing proportion of renewable energy, wind power
prediction is crucial to the arrangement of power grid dispatching plans due to the volatility …

A community integrated energy system (CIES) is an important carrier of the energy internet
and smart city in geographical and functional terms. Its emergence provides a new solution …

As an important cyber-physical system (CPS), smart grid is highly vulnerable to cyber
attacks. Amongst various types of attacks, false data injection attack (FDIA) proves to be one …

An operating entity utilizing community-integrated energy systems with a large number of
small-scale distributed energy sources can easily trade with existing distribution markets. To …

In order to improve the penetration of renewable energy resources for distribution networks,
a joint planning model of distributed generations (DGs) and energy storage is proposed for …

In the context of transition towards cleaner and sustainable energy production, microgrids
have become an effective way for tackling environmental pollution and energy crisis issues …

Multi-uncertainties from power sources and loads have brought significant challenges to the
stable demand supply of various resources at islands. To address these challenges, a …

Facing the difficulty of expensive and trivial data collection and annotation, how to make a
deep learning-based short-term voltage stability assessment (STVSA) model work well on a …