PMU Interoperability, Steady-State and Dynamic Performance Tests

Moraes, Rachel Maria Campos Menezes de; Hu, Yi; Stenbakken, Gerard N.; Martin, Kenneth E.; Alves, J.E.R.; Phadke, A.G.; Volskis, H. A. R.; Centeno, Virgilio

doi:10.1109/tsg.2012.2208482

Cited by 32 publications

(5 citation statements)

References 3 publications

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“…Xp (hrT s ), f p 1 (hrT s ), and ROCOF p (hrT s ) are the predicted synchrophasor, frequency and ROCOF values, respectively, at t = hrT s , which are obtained as mentioned above, i.e., applying (6), (7), and (8) considering the instant t i−1 = h(i − 1)rT s , 1 The index scanning the reporting instants is h = 0, 1, . .…”

Section: B Adaptive Measurement Decimationmentioning

confidence: 99%

Tracking Power Systems Events: PMU, Reporting Rate, Interpolation

Frigo

Pegoraro

Toscani

2022

2022 International Conference on Smart Grid Synchronized Measurements and Analytics (SGSMA)

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Fast dynamics and transient events are becoming more and more frequent in power systems, due to the high penetration of renewable energy sources and the consequent lack of inertia. In this scenario, Phasor Measurement Units (PMUs) are expected to track the monitored quantities. Such functionality is related not only to the PMU accuracy (as per the IEC/IEEE 60255-118-1 standard) but also to the PMU reporting rate (RR). High RRs allow tracking fast dynamics, but produce many redundant measurement data in normal conditions. In view of an effective tradeoff, the present paper proposes an adaptive RR mechanism based on a real-time selection of the measurements, with the target of preserving the information content while reducing the data rate. The proposed method has been tested considering real-world datasets and applied to four different PMU algorithms. The results prove the method effectiveness in reducing the average data throughput as well as its scalability at PMU concentrator or storage level.

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Section: B Adaptive Measurement Decimationmentioning

confidence: 99%

Tracking Power Systems Events: PMU, Reporting Rate, Interpolation

Frigo

Pegoraro

Toscani

2022

2022 International Conference on Smart Grid Synchronized Measurements and Analytics (SGSMA)

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“…PMU Evaluation was done using Omicron make Relay test system with GPS feature CMC 256 plus 8 . Moraes et al developed a comprehensive test program to evaluate PMU under steady‐state as well as dynamic/transient conditions using NIST PMU Calibration system for Brazilian Utility as per IEEE C37.118‐2005 9 . Harding et al tested PMU MiCOM P847 using high precision calibration set and associated Synchronizing equipment of Omicron make CMC 256 plus 10 .…”

Section: Description Of Pmu Calibration Systemmentioning

confidence: 99%

Assessment of compliance of phasor measurement units ( PMUs ) for smart grid applications

Kaliappan

Meera

Selvan

2021

Int Trans Electr Energ Syst

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Summary This paper introduces a method for evaluating phasor measurement units (PMUs) using the Fluke PMU Calibration system (6135A/PMUCAL), in both steady state and transient conditions, considering its applications in a smart power transmission system. Two numerical distance protection intelligent electronic devices (IEDs) enabled with PMU functionalities and one standalone PMU, are evaluated at different reporting rates (10, 25 and 50FPS) for both M and P class, at nominal frequency of 50 Hz. The PMUs are tested for critical parameters such as total vector error (TVE), response time, frequency error (FE), delay time, and rate of change of frequency error (RFE). The entire testing process is fully automated and controlled remotely. A detailed review of the PMU tests data output is conducted and a comprehensive analysis of the results are presented. The PMU performance is evaluated for compliance with IEEE C37.118‐1:2011 and IEEE C37.118‐1a:2014 product and standards certification. This automated testing methodology makes the entire testing process simple, accurate, and very efficient.

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“…In category 2, the impact of PMU measurement errors on power system analysis and control results is analysed, including wide‐area damping control [4], line parameter estimation [5], and state estimation [6]. In category 3, PMU dynamic performance and data quality evaluation and test are conducted in [7–11].…”

Section: Introductionmentioning

confidence: 99%