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Automated analysis of power systems disturbance records: Smart Grid big data perspective

机译:电力系统骚扰记录的自动分析:智能电网大数据视角

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摘要

Analysis of faults and disturbances play crucial roles in secure and reliable electrical power supply. Digital fault recorders (DFR) enable digital recording of the power systems transient events with high quality and huge quantity. However, transformation of data to information, expectedly in an automated way, is a big challenge for the power utilities worldwide. This is a key focus for realizing the ‘Smart Grid’. In this paper, the architecture and specifications for the primary and the secondary information for the automated systems are described. This provides qualitative and quantitative guidelines about the information to derive out of the disturbance data. A quantified estimate of big data for the substations, has been estimated in the paper. Possible ways of reducing the big data by utilizing intelligent segmentation techniques are described, substantiated by real example. Utilization of centralized protection and remote disturbance analysis for reducing big disturbance data are also discussed.
机译:故障和干扰的分析在安全可靠的电源供应中起着至关重要的作用。数字故障记录器(DFR)可高质量,大量地数字记录电力系统的瞬态事件。但是,以自动化的方式将数据转换为信息对全球的电力公司来说是一个巨大的挑战。这是实现“智能电网”的重点。在本文中,描述了自动化系统的主要和辅助信息的体系结构和规范。这为从干扰数据中得出的信息提供了定性和定量指导。本文已经对变电站的大数据进行了量化估计。描述了通过利用智能分割技术来减少大数据的可能方式,并以实际示例为依据。还讨论了利用集中保护和远程干扰分析来减少大的干扰数据。

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