Scalable Integration of High Sampling Rate Measurements in Deterministic Process-level Networks

F. Hohn, V. Fodor, G. Zanuso, L. Nordström
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Abstract

Travelling wave (TW) based protection functions, which process the time of arrival of TWs, require high sampling rates in the range of hundreds of kilohertz to several megahertz. In digital substations merging units (MU) publish the sampled values of current and voltage signals on process-level networks. However, publishing these highly sampled signals for TW-based protection functions limits severely the number of MUs in a process-level network due to the significant increase of communication load. To circumvent this problem, distributed signal processing units (DSPU) extract directly the necessary signal features and publish these at a lower publishing rate in order to decrease the communication load. This paper provides an mathematical analysis on the scalable integration of DSPUs in deterministic process-level networks based on the High-availability Seamless Redundancy (HSR) protocol, time-aware network nodes and traffic scheduling. It is shown that the distributed signal processing architecture provides a scalable integration of high sampling rate measurements for TW-based protection functions. Lastly the analytical model has been validated through a discrete-event simulation.
确定性过程级网络中高采样率测量的可扩展集成
基于行波(TW)的保护功能处理行波的到达时间,需要在数百千赫兹到几兆赫兹范围内的高采样率。在数字变电站中,并合单元(MU)在过程级网络上发布电流和电压信号的采样值。然而,由于通信负载的显著增加,将这些高采样信号发布到基于tw的保护功能中严重限制了进程级网络中的mu数量。为了避免这个问题,分布式信号处理单元(DSPU)直接提取必要的信号特征,并以较低的发布速率发布这些特征,以减少通信负载。基于高可用无缝冗余(HSR)协议、时间感知网络节点和流量调度,对确定性进程级网络中dsp的可扩展集成进行了数学分析。结果表明,分布式信号处理架构为基于tw的保护功能提供了可扩展的高采样率测量集成。最后,通过离散事件仿真对分析模型进行了验证。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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