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Synchrophasor Missing Data Recovery via Data-Driven Filtering

Stavros Konstantinopoulos, Genevieve M. De Mijolla, Joe H. Chow, H. Lev-Ari, Meng Wang

2020IEEE Transactions on Smart Grid28 citationsDOI

Abstract

To enhance reliability and observability, power systems in North America have installed a significant number of Phasor Measurement Units (PMUs) to monitor dynamic behaviors. For real-time applications, the PMU data are streamed via the Internet from the substations to the phasor data concentrators, in the control centers. The transmission of the PMU data however, is not always reliable and can be subjected to quality issues and losses due to latency and equipment malfunctions. In this paper, a temporal version of the OnLine Algorithm for PMU data processing (OLAP) is proposed to recover the missing data. The algorithm is geared toward prolonged data outages and especially signals exhibiting significant temporal patterns. The method is connected to adaptive filtering and a necessary stability criterion for the algorithm is derived.The method is compared against several low rank and streaming data recovery methods to evaluate its effectiveness.

Topics & Concepts

PhasorObservabilityComputer scienceMissing dataPhasor measurement unitReal-time computingElectric power systemReliability (semiconductor)Data qualityLatency (audio)Units of measurementData transmissionData miningData modelingData recoveryEngineeringPower (physics)Computer networkDatabaseQuantum mechanicsOperations managementMachine learningPhysicsApplied mathematicsMetric (unit)TelecommunicationsMathematicsComputer hardwareSeismic Imaging and Inversion TechniquesPower System Optimization and StabilityComputational Physics and Python Applications
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