This article studies the influence of PMU's accuracy in voltage stability assessment, considering the specific case of Thévenin equivalent based methods that include wide-area information in its calculations. The objective was achieved by producing a set of synthesized PMU measurements from a time domain simulation and using the Monte Carlo method to reflect the accuracy for the PMUs. This is given by the maximum value for the Total Vector Error defined in the IEEE standard C37.118. Those measurements allowed to estimate the distribution parameters (mean and standard deviation) of the studied voltage stability indices and grid transformation coefficients which have applications in voltage stability assessment. The obtained distributions have a direct impact in the number of samples needed for estimating system parameters and compromise between timescale and uncertainty in those estimations is shown.

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Abstract-A method that exploits Thevenin equivalent representation for obtaining post-contingency steady-state nodal voltages is integrated with a method of detecting post-contingency aperiodic small-signal instability. The task of integrating stability assessment with contingency assessment is challenged by the cases of unstable post-contingency conditions. For unstable postcontingency conditions there exists no credible steady-state which can be used for basis of a stability assessment. This paper demonstrates how Thevenin Equivalent methods can be applied in algebraic representation of such bifurcation points which may be used in assessment of post-contingency aperiodic small-signal stability. The assessment method is introduced with a numeric example.

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It is expected that bad data and missing topology information will become an issue of growing concern when power system state estimators are to exploit the high measurement reporting rates from phasor measurement units. This paper suggests to design state estimators with enhanced resilience against those issues. The work presented here include a review of a pre-estimation filter for bad data. A method for detecting branch status errors which may also be applied before the state estimation is then proposed. Both methods are evaluated through simulation on a novel test platform for wide-area measurement applications. It is found that topology errors may be detected even under influence of the large dynamics following the loss of a heavily loaded branch.