基于谐波电流时序分析的低压电网用户拓扑识别

M. Domagk, Jan Meyer, P. Schegner
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引用次数: 1

摘要

公共低压电网的电能质量水平主要受电网、接入用户、接入发电装置和气候条件的影响。连接的消费者(消费者拓扑)预计会对电能质量(PQ)水平产生很大影响。像谐波这样的连续现象与一天的周期密切相关,这意味着连续PQ参数的或多或少的周期性行为。像办公楼或住宅区这样的消费者拓扑结构在谐波发射行为上是不同的。因此,时间序列分析是一种合适的工具,可以推导出允许区分不同消费者拓扑的因素。本文首先阐述了影响电能质量的相关因素。它进一步描述了广泛的测量活动,建立为了获得必要的电能质量数据,以识别相关性。然后,本文介绍了一种基于可加构件模型的消费者拓扑识别方法。最后,通过实例说明了该方法的适用性。
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Identification of consumer topologies in low voltage grids by time series analysis of harmonic currents
Power quality levels in public Low Voltage (LV) grids are mainly influenced by the network, connected consumers, the connected generating installations and climatic conditions. The connected consumers (consumer topology) are expected to have a high influence on power quality (PQ) levels. Continuous phenomena like harmonics are closely linked to a one-day-cycle, which means a more or less periodic behavior of the continuous PQ parameters. Consumer topologies like office buildings or residential areas differ in their harmonic emitting behavior. Therefore, time series analysis is a suitable tool to derive factors which allow distinguishing between different consumer topologies. The paper starts with an explanation of relevant factors influencing power quality. It furthermore describes the extensive measurement campaign, set up in order to get the necessary power quality data for the identification of the correlations. Afterwards, the paper introduces a method based on the additive component model to distinguish between different consumer topologies. Finally, the suitability of the method is presented by several example applications.
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