面向智能电网停电检测的流计算框架

Shibily Joseph, E. A. Jasmin
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引用次数: 10

摘要

先进计量基础设施的实施可以提高系统的CAIDI和SAIDI等性能指标。但是,通过将数百万消费者连接到智能电网,AMI系统产生的数据现在已经发展到大数据的水平。如果应用高速数据处理技术,那么检测事件的系统响应时间将会减少,因此计划和执行操作所花费的时间可以缩短。这将直接提高智能电网的性能指标。本文揭示了流计算应用于AMI数据处理以检测故障的潜力。更快地检测中断将导致更快地启动中断恢复操作。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Stream computing framework for outage detection in smart grid
Implementation of Advanced Metering Infrastructures can improve system performance indices like CAIDI and SAIDI. But data generated by AMI systems are now grow to the level of big data by connecting millions of consumers to the smart grid. If high speed data processing techniques are applied then system response time to detect events will be reduced and hence time taken to plan and execute action can be shortened. This will directly improve the performance indices of smart grid. This paper reveals the potential of stream computing applied to AMI data processing to detect outages. Faster detection of outages leads to faster initiation of outage restoration actions.
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