EFFICIENT POWER QUALITY ANALYSIS OF BIG DATA (CASE STUDY FOR A DISTRIBUTION NETWORK OPERATOR)
EFFICIENT POWER QUALITY ANALYSIS OF BIG DATA (CASE STUDY FOR A DISTRIBUTION NETWORK OPERATOR)
复制标题
大数据的高效电能质量分析（配电网运营商案例研究）
DOI：
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发表时间：
2015
期刊：
影响因子：
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通讯作者：
Enso Netz
中科院分区：
文献类型：
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作者：
E. Gasch;Jan Meyer;P. Schegner;K. Schmidt;Enso Netz
电能质量（PQ）监测对于配电网的无故障运行起着重要作用。PQ监测设备的价格在过去十年中不断下降。特别是集成到其他设备（IED -智能电子设备），如电能表，实现了非常实惠的解决方案。由于这种趋势，网络运营商加强了他们的PQ测量活动，监测站点的数量快速增长。因此，电能质量测量数据的数量变得越来越大，其有效的管理和分析成为一个日益复杂的挑战。正如CIRED/CIGRE工作组C4.112“电能质量监测指南”[1]所确定的那样，分析这些大数据的有效算法是未来的关键问题。从未来PQ监测的一些主要挑战的简短讨论开始，本文提出了一种易于解释和灵活的聚合PQ指数的计算方法。接下来，提供了针对测量数据的设备独立处理而开发的技术的简要描述。本文的主要部分解决了高效的图形可视化的大型PQ数据量的方法。提出了两种基于固定和灵活PQ缩放级别的地图的方法。最后，这两种可视化方法的应用说明了一个案例研究与80多个测量站点由当地的配电系统运营商（DSO）。
Power Quality (PQ) monitoring plays an important role for a trouble-free operation of distribution grids. Prices for PQ monitoring equipment have continuously decreased during the last decade. Especially the integration into other equipment (IED – Intelligent electronic devices) like energy meters enables extremely affordable solutions. Due to this trend, network operators have intensified their PQ measurement activities and the number of monitored sites grows fast. As consequence the amount of PQ measurement data gets larger and larger and its efficient management and analysis becomes an increasing complex challenge. As also identified be the CIRED/CIGRE working group C4.112 “Guidelines for Power quality monitoring” [1], efficient algorithms to analyze this big data are a key issue in the future. Starting with a short discussion of some major challenges of future PQ monitoring, the paper proposes a method for the calculation of an easy-to-interpret and flexible to aggregate PQ index. Next a brief description of the techniques developed for a device-independent handling of measurement data is provided. The main part of the paper addresses methods for efficient graphical visualization of large PQ data amounts. Two different approaches based on maps with fixed and flexible PQ zoom level are proposed. Finally the application of both visualization methods is illustrated in a case study with more than 80 measurement sites operated by a local distribution system operator (DSO).