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    Conditioning of FNET Data and Triangulation of Generator Trips in the Eastern Interconnected System

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    Date
    2005-07-29
    Author
    Gardner, Robert Matthew
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    Abstract
    Using data from the frequency disturbance recorders (FDRs) that comprise the nation-wide frequency monitoring network known as FNET, disturbances in the eastern interconnected system (EI) have been monitored and recorded over the past several years. Analysis of this and other data by a wide variety of research scientists and engineers has rendered the idea that frequency disturbances from generator trips, transmission line trips, load trips, and other events, travel with finite speed as electromechanical waves throughout any power system (in this case the EI). Using FNET data as a tool, it is possible to measure and output the arrival times of these disturbance waves with a time resolution of 100 ms. To observe with certainty the arrival time of the frequency disturbance waves, field data collected by the FDRs must first be conditioned in a robust manner. The current method that uses the moving mean of raw FDR data is analyzed and two computationally efficient robust methods are suggested in this report. These new methods that rely on robust statistics are more resistant to the effect of outliers contained within the raw FDR data. Furthermore, like the moving mean, these methods smooth the raw data without removing the general trend. Having recorded and conditioned the FDR data, three conventional triangulation techniques taken from the field of seismology are proposed and analyzed. This study reconfirms the fact that the EI is not a medium of continuous elasticity though which the frequency perturbations travel but rather a discontinuous patchwork of varying elasticities. Within this report, nine generator trip events are analyzed and the aforementioned triangulation methods are applied. The advantages and disadvantages of each method are discussed. To conclude, axioms of future research are proposed and delineated.
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    http://hdl.handle.net/10919/34338
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    • Masters Theses [21534]

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