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Application of a Hadoop-based Distributed System for Offline Processing of Power Quality Disturbances

机译:基于Hadoop的分布式系统在电能质量扰动离线处理中的应用

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Electric power quality is a critical issue for electric utilities and their customers and identification of the power quality disturbances is an important task in power system monitoring and protection. Offline processing of power quality disturbances provides an economic alternative for electric distribution companies, not capable of buying enough number of power quality analyzers for monitoring the disturbances online. Due to the wide frequency range of the disturbances which may happen in a power system, a high sampling rate is necessary for digital processing of the disturbances. Therefore, a large volume of data must be processed for this purpose for each node of an electric distribution network and such a processing has not yet been practical. However, thanks to the rapid developments of digital processors and computer networks, processing big databases is not so hard today. Apache Hadoop is an open-source software framework that allows for the distributed processing of large datasets using simple programming models. In this paper, application of Hadoop distributed computing software for offline processing of power quality disturbances is proposed and it is shown that this application makes such a processing possible and leads to a very cheaper system with widespread usage, compared to the power quality analyzers.
机译:电力质量是电力公司及其客户的关键问题,识别电力质量扰动是电力系统监视和保护的重要任务。电能质量扰动的离线处理为配电公司提供了经济的选择,这些公司无法购买足够数量的电能质量分析仪来在线监测扰动。由于可能在电力系统中发生的干扰的频率范围很广,因此对干扰进行数字处理需要高采样率。因此,为此目的必须针对配电网络的每个节点处理大量数据,并且这种处理尚不可行。但是,由于数字处理器和计算机网络的迅猛发展,如今处理大型数据库并不那么困难。 Apache Hadoop是一个开源软件框架,它允许使用简单的编程模型对大型数据集进行分布式处理。在本文中,提出了将Hadoop分布式计算软件用于电能质量扰动的离线处理的应用,并且表明与电能质量分析仪相比,该应用使得这种处理成为可能,并且导致了一种具有广泛使用的廉价系统。

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