用于低地球轨道卫星星座网络的实时网络-物理数字孪生增强型广域电网

IF 5.2 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC
Tianshi Cheng;Tong Duan;Venkata Dinavahi
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引用次数: 0

摘要

低地球轨道(LEO)卫星网络,如 SpaceX 的 Starlink,为当代电网测量和控制提供了更大的通信潜力。然而,这些网络的动态特性使其建模和仿真变得复杂。本研究介绍了一个模块化、面向数据的数字孪生框架,用于利用低地轨道卫星网络对广域交流-直流电网进行实时仿真。该框架集成了用于卫星跟踪的 RustSat、用于 SDN 仿真的 SatSDN 和 MiniNet,以及用于实时电力系统仿真的实体-组件-系统(ECS)-电网。它采用以数据为中心的设计,使用 ECS 框架和阵列结构内存布局,优化了缓存效率和计算性能,并为跨学科仿真提供了高度的可扩展性。这标志着为大规模电力系统和低地轨道卫星星座网络实时协同仿真开发数字孪生系统的初步努力。在具有多种卫星网络类型的广域合成交流-直流系统上进行的评估证实了我们方法的效率和精确性,强调了它在连接低地轨道卫星网络和电力系统应用方面的潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Real-Time Cyber-Physical Digital Twin for Low Earth Orbit Satellite Constellation Network Enhanced Wide-Area Power Grid
Low Earth orbit (LEO) satellite networks, such as SpaceX's Starlink, offer enhanced communication potential for contemporary power grid measurement and control. Yet, the dynamic nature of these networks complicates their modeling and simulation. This study introduces a modular, data-oriented digital twin framework for real-time simulation of wide-area ac–dc grids with LEO satellite networks. The framework integrates RustSat for satellite tracking, SatSDN with MiniNet for SDN simulations, and entity-component-system (ECS)-Grid for real-time power system simulation. It features a data-centric design using an ECS framework with a structure-of-arrays memory layout, optimizing cache efficiency and computational performance, and offers high extensibility for interdisciplinary simulations. This marks the initial effort to develop a digital twin for real-time co-simulation of large-scale power systems and LEO satellite constellation networks. Evaluations on a wide-area synthetic ac–dc system with multiple satellite network types confirm the efficiency and precision of our approach, underscoring its potential in bridging LEO satellite networks with power system applications.
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来源期刊
IEEE Open Journal of the Industrial Electronics Society
IEEE Open Journal of the Industrial Electronics Society ENGINEERING, ELECTRICAL & ELECTRONIC-
CiteScore
10.80
自引率
2.40%
发文量
33
审稿时长
12 weeks
期刊介绍: The IEEE Open Journal of the Industrial Electronics Society is dedicated to advancing information-intensive, knowledge-based automation, and digitalization, aiming to enhance various industrial and infrastructural ecosystems including energy, mobility, health, and home/building infrastructure. Encompassing a range of techniques leveraging data and information acquisition, analysis, manipulation, and distribution, the journal strives to achieve greater flexibility, efficiency, effectiveness, reliability, and security within digitalized and networked environments. Our scope provides a platform for discourse and dissemination of the latest developments in numerous research and innovation areas. These include electrical components and systems, smart grids, industrial cyber-physical systems, motion control, robotics and mechatronics, sensors and actuators, factory and building communication and automation, industrial digitalization, flexible and reconfigurable manufacturing, assistant systems, industrial applications of artificial intelligence and data science, as well as the implementation of machine learning, artificial neural networks, and fuzzy logic. Additionally, we explore human factors in digitalized and networked ecosystems. Join us in exploring and shaping the future of industrial electronics and digitalization.
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