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Comparison of Voltage Instability Identification Methods Based on Synchronized Measurements | IEEE Conference Publication | IEEE Xplore

Comparison of Voltage Instability Identification Methods Based on Synchronized Measurements


Abstract:

This paper carries out the evaluation and comparison of three methods of real-time monitoring of power system longterm voltage stability using synchronized phasor measure...Show More

Abstract:

This paper carries out the evaluation and comparison of three methods of real-time monitoring of power system longterm voltage stability using synchronized phasor measurements, namely, adaptive method (AD), coupled single-port method (CP) and modified coupled single-port method (CP-M). Based on Thevenin theorem, these methods estimate an equivalent two-bus circuit seen from a specific bus of interest. The methods estimate an equivalent impedance in front of an equivalent voltage, or vice-versa. A significant difference among the methods is that AD relies only on measurements, whereas CP and CP-M rely on measurements and network topology. The performance of the methods is analyzed for constant current type loads with different load growth profiles. The time-domain simulations are performed in the modified IEEE 9-bus test system and in the reduced 32-bus Nordic system. The results are analyzed through several comparisons, including: 1) the difference between the magnitude of the load impedance and the magnitude of the equivalent impedance; 2) the similarity between the PV curves of the monitored bus computed by time-domain simulation and the PV curves of the corresponding equivalent circuits; 3) the proximity of the power margin curve indicated by each algorithm and the actual power margin also computed by time-domain simulation; and, finally, 4) the difference between the reactive power response factor (RPRF) for each equivalent and the RPRF of the grid seen from the monitored bus.
Date of Conference: 21-23 May 2019
Date Added to IEEE Xplore: 05 August 2019
ISBN Information:
Conference Location: College Station, TX, USA

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