Critical buses identification for voltage stability assessment considering the application of modal analysis and a robust state estimation with bad data suppression

This paper investigates the application of modal analysis in the results of a proposed robust state estimation technique to determine the most critical buses of power distribution systems within the context of voltage stability assessment. In the proposed approach, the Weighted Least Squares (WLS) technique is used to estimate state variables based on micro-PMUs (Phasor Measurement Units) and SMs (smart meters) measurements. The estimated voltage magnitudes and angles are used to form a reduced Jacobian matrix which provides the sensitivities of reactive powers and voltage magnitudes at each load bus. Based on the calculation of eigenvalues and eigenvectors, participation factors are estimated for each load bus. In order to minimize the influence of gross errors, a bad data detection procedure is performed using Chi-squared test. The proposed identification procedure is based on the Median Absolute Deviation (MAD) of the normalized measurement residuals. The corrupted measurements are re-weighted in the proposed methodology to suppress its influence on the results yielding high accurate estimates. Simulations are carried out using a 33-bus test system. The impact of distributed generation units, aleatory errors and bad data is evaluated by different case studies to prove the efficiency of the proposed method.