2016 IEEE/PES Transmission and Distribution Conference and Exposition (T&D) 2016
DOI: 10.1109/tdc.2016.7519975
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Micro-synchrophasor data for diagnosis of transmission and distribution level events

Abstract: Abstract-This paper describes the benefits of time synchronized advanced sensor data for event detection. We present measurement data collected from a network of micro-synchrophasors (µPMU) installed at Lawrence Berkeley National Laboratory (LBNL)-the first pilot network of distribution-level phasor measurement units (PMUs). The time-synchronized, high fidelity voltage magnitude and phase angle data described provides indicators for events originating at transmission or local distribution level events sensed t… Show more

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Cited by 26 publications
(12 citation statements)
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“…Some events in distribution networks are sinusoidal or non-sinusoidal transients in voltage and current waveforms that may be caused by faults, topology changes, load behavior, and source dynamics. The distribution operators can detect the events in real-time, by investigating data from the µPMU installed in the distribution network [26]. For example, using µPMU data, reverse power flow in distribution networks can be easily detected [27].…”
Section: Monitoring and Diagnostic Applicationsmentioning
confidence: 99%
“…Some events in distribution networks are sinusoidal or non-sinusoidal transients in voltage and current waveforms that may be caused by faults, topology changes, load behavior, and source dynamics. The distribution operators can detect the events in real-time, by investigating data from the µPMU installed in the distribution network [26]. For example, using µPMU data, reverse power flow in distribution networks can be easily detected [27].…”
Section: Monitoring and Diagnostic Applicationsmentioning
confidence: 99%
“…Studies by Lawrence Berkeley National Laboratory (LBNL) on high-precision μ-PMUs being developed by Power Standards Lab is presented in [14,16] where LBNL focuses on synchrophasor data for control and diagnostic applications in distribution systems. The capabilities of synchrophasor in distribution grid along with challenges and lessons learned are discussed in [16,17]. Synchrophasor data from μ-PMU deployed at multiple campus locations as well as utilities are used to analyze the planning and operation of supporting distribution system and DG control which includes generation and storage.…”
Section: μ-Pmu For Smart Distribution Systemmentioning
confidence: 99%
“…Synchrophasor data from μ-PMU deployed at multiple campus locations as well as utilities are used to analyze the planning and operation of supporting distribution system and DG control which includes generation and storage. Diagnostic as well as control applications are delineated in [17]. Diagnostic applications aid the power system planners and operators to comprehend the present or past state of the distribution system better, thus providing enhanced decision making capability on equipment maintenance, interconnection of resources or network rearrangement.…”
Section: μ-Pmu For Smart Distribution Systemmentioning
confidence: 99%
“…An event detection algorithm using micro synchrophasor data is presented in [200]. The authors proposed an automatic anomaly detection algorithm for a fast-changing distribution grid using Micro-PMU data.…”
Section: Intrusion Detectionmentioning
confidence: 99%