Results 251 to 260 of about 2,418,705 (282)

Graph Multi-Agent Reinforcement Learning for Inverter-Based Active Voltage Control

IEEE Transactions on Smart Grid
Active voltage control (AVC) is a widely-used technique to improve voltage quality essential in the emerging active distribution networks (ADNs). However, the voltage fluctuation caused by intermittent renewable energy makes it difficult for traditional ...
C. Mu, Zhaoyang Liu, Jun Yan, H. Jia, Xiaoyu Zhang   +4 more
semanticscholar   +1 more source

Graph Learning-Based Voltage Regulation in Distribution Networks With Multi-Microgrids

IEEE Transactions on Power Systems
Microgrids (MGs), as localized small power systems, can effectively provide voltage regulation services for distribution networks by integrating and managing various distributed energy resources.
Yi Wang, D. Qiu, Yu Wang, Mingyang Sun, G. Strbac   +4 more
semanticscholar   +1 more source

Multi-Agent Graph-Attention Deep Reinforcement Learning for Post-Contingency Grid Emergency Voltage Control

IEEE Transactions on Neural Networks and Learning Systems
Grid emergency voltage control (GEVC) is paramount in electric power systems to improve voltage stability and prevent cascading outages and blackouts in case of contingencies.
Ying Zhang, Meng Yue, Jianhui Wang, Shinjae Yoo   +3 more
semanticscholar   +1 more source

Deep Reinforcement Learning for Voltage Control and Renewable Accommodation Using Spatial-Temporal Graph Information

IEEE Transactions on Sustainable Energy
Renewable energy resources (RERs) have been increasingly integrated into distribution networks (DNs) for decarbonization. However, the variable nature of RERs introduces uncertainties to DNs, frequently resulting in voltage fluctuations that threaten ...
Jinhao Li, Ruichang Zhang, Hao Wang, Zhi Liu, Hongyang Lai, Yanru Zhang   +5 more
semanticscholar   +1 more source

Enhancing the Tolerance of Voltage Regulation to Cyber Contingencies via Graph-Based Deep Reinforcement Learning

IEEE Transactions on Power Systems
The volatility from the high penetration of distributed energy resources (DERs) makes distribution networks more susceptible to voltage violations. Besides, with the increasing coupling of cyber and physical sides in modern power systems, the risk of ...
Yu Zhao, Jun Liu, Xiaoming Liu, Keyu Yuan, Tao Ding   +4 more
semanticscholar   +1 more source

Dual-Space Graph-Based Interaction Network for RGB-Thermal Semantic Segmentation in Electric Power Scene

IEEE transactions on circuits and systems for video technology (Print), 2023
Real-time scene comprehension is the basis for automatic electric power inspection. However, existing RGB-based scene comprehension methods may achieve unsatisfied performance when dealing with complex scenarios, insufficient illumination or occluded ...
Chang Xu, Qingwu Li, Xiongbiao Jiang, Dabing Yu, Yaqin Zhou   +4 more
semanticscholar   +1 more source

Employing Graph Neural Networks for Predicting Electrode Average Voltages and Screening High-Voltage Sodium Cathode Materials.

ACS Applied Materials and Interfaces
For many years, humans have been relentlessly focused on enhancing battery longevity and boosting energy storage capacities. The performance and durability of a battery depend significantly on the material used for its electrodes.
Xiaoyue He, Yanxu Chen, Shao Wang, Genqiang Zhang   +3 more
semanticscholar   +1 more source

Unrolled Spatiotemporal Graph Convolutional Network for Distribution System State Estimation and Forecasting

IEEE Transactions on Sustainable Energy, 2023
Timely perception of distribution system states is critical for the control and operation of power grids. Recently, it has been seriously challenged by the dramatic voltage fluctuations induced by high renewables.
Huayi Wu, Zhao Xu, Minghao Wang
semanticscholar   +1 more source

Real-Time Cascading Failure Risk Evaluation With High Penetration of Renewable Energy Based on a Graph Convolutional Network

IEEE Transactions on Power Systems, 2023
When renewable energy penetration increases and the power network becomes more complex, vulnerability and security concerns typically also become more prevalent. A proper evaluation method focused on risk prediction and failure identification is required
Yuhong Zhu, Yongzhi Zhou, Wei Wei, Leiqi Zhang   +3 more
semanticscholar   +1 more source

Applications of ordinary voltage graph theory to graph embeddability

Journal of Graph Theory, 2015
Let p be a prime greater than 5. We show that, while the generalized Petersen graphs of the form GP(2p,2) have cellular toroidal embeddings, they have no such embeddings having the additional property that a free action of a group on the graph extends to
S. Schluchter
semanticscholar   +1 more source