Synchrophasor Missing Data Recovery via Data-Driven Filtering

Stavros Konstantinopoulos

doi:10.1109/TSG.2020.2986439

Synchrophasor Missing Data Recovery via Data-Driven Filtering

2020-09-01

22

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AI

S

Stavros Konstantinopoulos *

G

Genevieve M. De Mijolla

DOI：10.1109/TSG.2020.2986439

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Abstract

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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.

Keywords:

Phasor measurement units

Real-time systems

Heuristic algorithms

Power system stability

Time measurement

Microsoft Windows

Power system dynamics

Synchrophasor

PMU

low rank recovery

adaptive filtering

OLAP

Synchrophasor Missing Data Recovery via Data-Driven Filtering

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