Results 261 to 270 of about 2,362,134 (317)

Design and Optimization of Low-Dropout Voltage Regulator Using Relational Graph Neural Network and Reinforcement Learning in Open-Source SKY130 Process

2023 IEEE/ACM International Conference on Computer Aided Design (ICCAD), 2023
Design automation and optimization for analog integrated circuits (ICs) are challenging, especially for transistor sizing. Given certain design specifications and circuit topology, circuit designers need to size various components to achieve the desired ...
Z. Li, A. C. Carusone
semanticscholar   +1 more source

Graph Theory Based Voltage Sag Mitigation Cluster Formation Utilizing Dynamic Voltage Restorers in Radial Distribution Networks

IEEE Transactions on Power Delivery, 2022
Voltage sag mitigation utilizing dynamic voltage restorers (DVRs) can be classified as a common-pool resource (CPR) good. However, the ability of DVRs in improving voltage sag performance of only downstream customers provides the ability to exclude the ...
Subir Majumder, S. Khaparde, A. Agalgaonkar, S. V. Kulkarni, S. Perera   +4 more
semanticscholar   +1 more source

The 3D graph approach for breakdown voltage calculation in BaTiO₃ ceramics

International Journal of Modern Physics B, 2021
After pioneering attempts for the introduction of graph theory in the field of ceramics and microstructures, where 1D and 2D graphs were used, in this paper we applied 3D graphs for the breakdown voltage calculation in BaTiO3 sample with some predefined constraints.
Vojislav V. Mitić, Vojislav V. Mitić, An-Lu Chun, Branislav Randjelovic, Branislav Randjelovic, Srdjan Ribar, Ivana Ilić, Branislav Vlahovic, Aleksandar Stajcic   +8 more
openaire   +5 more sources

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

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

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 Convolutional Network-Based Interpretable Machine Learning Scheme in Smart Grids

IEEE Transactions on Automation Science and Engineering, 2023
Smart grid is a typical application of industrial cyber-physical systems (ICPS) in the electric power industry. Due to the exposure to different kinds of uncertainties and unpredictable faults, how to reliably assess the short-term voltage stability (SVS)
Yonghong Luo, Chao Lu, Lipeng Zhu, Jie Song   +3 more
semanticscholar   +1 more source

Cloud-Edge Collaboration-Based Local Voltage Control for DGs With Privacy Preservation

IEEE Transactions on Industrial Informatics, 2023
The increased distributed generators (DGs) have exacerbated voltage violations in active distribution networks (ADNs). Local reactive power control of DG inverters can realize a fast response to frequent voltage fluctuations. However, commonly used model-
Jinli Zhao, Ziqi Zhang, Hao Yu, H. Ji, Peng Li, W. Xi, Jinyue Yan, Chengshan Wang   +7 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

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