在智能电网应用中使用相量数据进行可视化和数据挖掘

Anupam Mukherjee, Ranganath Vallakati, Valentin Lachenaud, P. Ranganathan
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引用次数: 4

摘要

提出了一种基于密度的聚类(DBSCAN)技术,用于智能电网数据的可视化和分析。该技术将有助于检测坏数据、各种故障类型、频率偏差、电压或电流值,从而更好地了解情况。同步相量(或PMU)是放置在传输线上的传感器,用于跟踪线路的电压、电流、相位和频率。为了提高智能电网实时监控的态势感知能力,电力公司必须监控传感器提供的相量数据测量。时间戳同步度量为事件前后分析提供了巨大的好处。本文使用openPDC框架中的数据来帮助系统运营商进行各种预测分析和决策。
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Using phasor data for visualization and data mining in smart-grid applications
This paper presents a density based clustering (DBSCAN) technique to visualize and analyze the smart-grid data. The technique will aid in detecting bad-data, various fault types, deviation on frequency, voltage or current values for better situational awareness. Synchrophasors (or a PMU) is a sensor placed on a transmission line that tracks voltage, current, phase and frequency of the line. To improve situational awareness of the smart grid monitoring in real-time, the utility must monitor the phasor data measurement delivered by the sensors. Time-stamped synchronized measurements offer tremendous benefit for pre and post-event analysis. The paper uses data from openPDC framework to aid system operators in carrying various predictive analytics, decisions.
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