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- W4297668734 abstract "The analysis of multiple sets of data usually of different types or modalities is a challenging problem in power system stability analysis. Examination of system disturbances may involve a large number of measured signals with composite record lengths on the order of several minutes or hours [1-5] and be complicated by noise, trends, and other artifacts.In addition, comparisons are also needed against model simulations, dynamic probing tests, and previous events [4-6]. Dynamic analysis of measured data faces two major challenges. First, records collected on the wide-area monitoring systems (WAMS) are high-dimensional, complex, and may be contaminated by noise from different sources [6-9]. Second, spatiotemporal data are heterogeneous and highly variable, especially when anomalies resulting from system disturbances change over space or time and exhibit irregular or intermittent behavior.In this chapter, measured data from an actual system event are used to investigate the ability of wide-area monitoring techniques to monitor and visualize system behavior. Several multisensor data fusion-based forecasting architectures are investigated and tested. The applications covered include the assessment and use of various signal processing techniques in measured synchrophasor data.Practical methods for obtaining approximations to system behavior are discussed, and the accuracy of the models is evaluated using standard metrics. Visualization techniques are also presented.The experience in the analysis of collected data from phasor measurement units (PMUs) is presented, and critical factors that influence the system's operation are examined. The issues of data collection, conditioning, and extraction of the primary oscillation frequency are discussed." @default.
- W4297668734 created "2022-09-30" @default.
- W4297668734 date "2022-09-08" @default.
- W4297668734 modified "2023-10-17" @default.
- W4297668734 title "Interpretation and visualization of wide-area phasor measurement unit measurements" @default.
- W4297668734 doi "https://doi.org/10.1049/pbpo213e_ch10" @default.
- W4297668734 hasPublicationYear "2022" @default.
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