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Browsing by Author "Vichare, Nitin Shrikrishna"

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    Measurement and modelling of errors for relaying current transformers and voltage transformers
    Vichare, Nitin Shrikrishna (Virginia Tech, 1990)
    A measurement tool has been developed to estimate errors in relaying current transformers and voltage transformers. The tool has been developed to collect data in a substation and send it to a remote location over a telephone line. Different schemes were evaluated and tested in the laboratory. The final choice was made on the basis of the hardware and transmission cost constraints. The measurement unit was developed using hardware similar to that used in a computer relay. The signals from the current and voltage transducers were sampled using a microprocessor and an analog to digital converter in real-time. The measurement device has been installed in the field. The data from the field was collected remotely and analyzed in the Virginia Tech Power Systems laboratory. The analysis of the data is presented at the end.
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    Robust Mahalanobis distance in power systems state estimation
    Vichare, Nitin Shrikrishna (Virginia Tech, 1993)
    The dissertation presents a new robust method for estimating the standardized distances of the data points associated with the weighted Jacobian matrix in power system state estimation. These distances, called robust Mahalanobis distances, can be used as weight functions to robustify the residuals of both the M-estimators and the least median of squares estimators for outlier diagnostics. They can also be used for leverage diagnostics and for alleviating the ill-conditioning problem of the Jacobian matrix. The robust Mahalanobis distances are calculated in three steps. First, projection distances are calculated and statistical tests applied to them to identify leverage points. Then, the sample covariance matrix is estimated from the data set without the identified leverage points. Finally robust Mahalanobis distances are calculated from the estimated covariance matrix. The projection distances are provided by a new version of the projection algorithm proposed by Donoho and Stahel, which has been specially adapted for power systems. The new projection algorithm consists of selecting relevant directions for each measurement in the factor space and projecting on these directions only the subset of data points that have non-zero projections. It is shown that this subset is the union of the fundamental sets containing the selected measurement. The fundamental set of a state variable consists of all those measurements that observe this state variable. The probability distributions of the projection distances and the statistical cutoff values for leverage point identification have been determined through Monte Carlo simulations and Q-Q plots. It is found that the projection distances follow x²-distributions with degrees of freedom much smaller than the dimension of the factor space. Simulation results performed on various test systems have revealed that the projection algorithm can handle a large fraction of leverage points, whatever their positions in the factor space. In addition, it is very fast and compatible with real-time environment, even for very large systems. Its computing times grow linearly with system size.