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Quantitative Assessment of Stochastic Property of Network-Induced Time Delay in Smart Substation Cyber Communications

机译:网络诱导智能变电站网络通信随机性随机性能的定量评估

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Smart substation, in which various types of information are being exchanged on a communication network, is regarded as a typical cyber-physical system (CPS). The network-induced time delay, inherently stochastic, makes the performance of power system operation and protection unpredictable. This paper attempts to study the stochastic properties of end-to-end network-induced time delay in a time-critical smart substation CPS environment. The components in a smart substation CPS, including data flow, communication network, and intelligent electronic device (IED), are modeled. The data flow on the network is categorized into two different stochastic types according to their source: Poisson and Pareto data flow. The numerical simulation of the hybrid data sources on substation network is implemented to evaluate the stochastic property, by combining Monte Carlo method and queueing theory. The obtained distribution results are identified by using chi-square and Kolmogorov-Smirnov tests. It is identified that Normal distribution can best characterize the delay in smart substation, meanwhile, the proposed model is verified with the experiment. A typical 220kV smart substation is studied under various scenarios.
机译:智能变电站,其中在通信网络上交换各种类型的信息,被认为是典型的网络物理系统(CPS)。网络诱导的时间延迟,固有的随机性,使得电力系统运行和保护不可预测的性能。本文试图研究一段时间关键智能变电站CPS环境中端到端网络诱导的时间延迟的随机性能。智能变电站CP中的组件,包括数据流,通信网络和智能电子设备(IED)。根据其来源:泊松和帕累托数据流量,网络上的数据流分为两种不同的随机类型。通过组合Monte Carlo方法和排队理论,实施了变电站网络上的混合数据源的数值模拟来评估随机性质。通过使用Chi-Square和Kolmogorov-Smirnov测试来鉴定所获得的分布结果。结果确定正常分布可以最好地表征智能变电站的延迟,同时,通过实验验证了所提出的模型。在各种场景下研究了典型的220kV智能变电站。

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