The volatility of renewable energy leads to numerous voltage changes in a short period, thus
affecting the quality of the power supply. A real-time smart voltage control framework of …

Out-of-step oscillation is a very destructive physical phenomenon in power system, which
could directly cause big blackout accompanied by serious sociology-economic impacts. Out …

Today, the majority of the leading power companies place a significant emphasis on
forecasting the electricity load in the balance of power and administration. Meanwhile, since …

The advent of federated learning has facilitated large-scale data exchange amongst
machine learning models while maintaining privacy. Despite its brief history, federated …

Timely, effective, and robust artificial intelligence (AI) technology is urgently needed to
improve decision-making efficiency in the presence of renewable energy with high …

Electricity load patterns in buildings are increasingly diverse and inherently present building-
by-building and temporal variations. This study develops structured stochastic models to …

Out-of-step (OOS) oscillation is a key link in the power system outage evolution. Precise
islanding control can prevent system outages. Renewable energy is connected to the power …

This article presents a deep reinforcement learning-based control framework for adaptive
generator protection in wide-area power systems. Out-of-step (OOS) generator tripping is an …

The decision-making of generator start-up sequence plays a pivotal role in the power system
restoration process following the blackout. In this paper, an optimized deep Q-learning …

Introduction: This paper proposes a power system fault prediction method that utilizes a GA-
CNN-BiGRU model. The model combines a genetic algorithm (GA), a convolutional neural …