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Knowledge discovery for smart grid operation, control, and situation awareness — a big data visualization platform

机译:智能电网运营,控制和态势感知的知识发现—大数据可视化平台

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In this paper, a big data visualization platform is designed to discover the hidden useful knowledge for smart grid (SG) operation, control and situation awareness. The spawn of smart sensors at both grid side and customer side can provide large volume of heterogeneous data that collect information in all time spectrums. Extracting useful knowledge from this big-data poll is still challenging. In this paper, the Apache Spark, an open source cluster computing framework, is used to process the big-data to effectively discover the hidden knowledge. A high-speed communication architecture utilizing the Open System Interconnection (OSI) model is designed to transmit the data to a visualization platform. This visualization platform uses Google Earth, a global geographic information system (GIS) to link the geological information with the SG knowledge and visualize the information in user defined fashion. The University of Denver's campus grid is used as a SG test bench and several demonstrations are presented for the proposed platform.
机译:本文设计了一个大数据可视化平台,以发现对于智能电网(SG)的运行,控制和态势感知而言隐藏的有用知识。网格端和客户端的智能传感器的产生可以提供大量的异构数据,这些数据可以收集所有时间范围内的信息。从这次大数据调查中提取有用的知识仍然充满挑战。在本文中,Apache Spark是一个开放源代码集群计算框架,用于处理大数据以有效地发现隐藏的知识。利用开放系统互连(OSI)模型的高速通信体系结构旨在将数据传输到可视化平台。该可视化平台使用Google Earth(全球地理信息系统(GIS))将地质信息与SG知识链接在一起,并以用户定义的方式可视化该信息。丹佛大学的校园网格用作SG测试台,并针对该建议的平台提供了一些演示。

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