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An Architecture Based on Digital Twins for Smart Power Distribution System

机译:基于数字孪生的智能配电系统架构

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Constructing an effective architecture based on digital twins using advanced artificial intelligent technologies remains a key challenge in smart power distribution system. Despite recent advances in important domains such as device health maintenance and manufacturing process, the conventional architecture does not offer a satisfactory solution for rapidly providing data models, a set of analytics or algorithms, and knowledge. In this work, we employ ideas from distributed network based on digital twins and from recent advances that augment artificial intelligent with big data. Our architecture provides a paradigm that uses a distributed network makes computer programming, software, and data spread out across more than one terminal, but communicate complex messages through terminal nodes, and are dependent upon each other, obviating the pressure from master station. We demonstrate the usefulness of digital twins that are used to track the performance of devices such as transformer during normal operation to detect possible defects and fix them before they result in failure. We also conclude that using digital twin technology will understand, predict, and optimize performance in order to achieve improved business outcomes, and apply machine learning and knowledge to predict the future.
机译:使用先进的人工智能技术构建基于数字孪生的有效架构仍然是智能配电系统中的关键挑战。尽管最近在诸如设备健康维护和制造过程等重要领域取得了进展,但是常规体系结构仍无法提供令人满意的解决方案来快速提供数据模型,一组分析或算法以及知识。在这项工作中,我们采用了基于数字双胞胎的分布式网络中的思想,以及从利用大数据增强人工智能的最新进展中获得的思想。我们的体系结构提供了一种使用分布式网络的范例,该范例使计算机编程,软件和数据分布在多个终端上,但是通过终端节点传递复杂的消息,并且彼此依赖,从而避免了主站的压力。我们展示了数字孪生的有用性,该孪生子在正常运行期间用于跟踪诸如变压器之类的设备的性能,以检测可能的缺陷并在导致故障之前对其进行修复。我们还得出结论,使用数字孪生技术将理解,预测和优化绩效,以实现改善的业务成果,并运用机器学习和知识来预测未来。

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