PMU-Based Estimation of Systematic Measurement Errors, Line Parameters, and Tap Changer Ratios in Three-Phase Power Systems

Abstract

The availability of accurate data is fundamental for several monitoring and control applications of modern power grids. Nevertheless, the knowledge of critical data such as transmission line and transformer parameters is often affected by uncertainty. This can lead to important problems in the correct management of the power systems. In spite of a monitoring infrastructure that is being renewed thanks to new generation devices providing synchronized measurements, the actual values of line parameters and tap changer ratios are still affected by uncertainty sources that need to be properly considered. The behaviour of all the elements involved in the measurement chain must be duly modelled. This paper proposes an improved method to carry out the simultaneous estimation of line parameters, tap changer ratios, and systematic measurement errors for a three-phase power system. The proposed method is based on the suitable modelling of the measurement chain and on three-phase constraint equations (voltage drop and current balance) of all the components involved. Its effectiveness is confirmed by tests performed on a IEEE 14 bus test system reproduced as a threephase system under different operative conditions.

Compensation of Systematic Errors for Improved PMU-based Fault Detection and Location in Three-Phase Distribution Grids

“…Thus, the DSSE used in this paper runs with measurements of node voltage and current injection. Branch currents, together with node voltage measurements, are instead used for the line parameters estimation method as presented in [40], [41]. Operators can apply such a method, in quasi-steady-state conditions, both online or offline depending on the needs, to periodically update the estimates of line parameters and systematic errors of the measurement chain.…”

Estimation of Line Parameters, Tap Changer Ratios, and Systematic Measurement Errors Based on Synchronized Measurements and a General Model of Tap-Changing Transformers

“…These synchrophasor measurements are referred to the same time instant t, i.e an UTC (Coordinated Universal Time) timestamp. The π-models of transmission lines and transformers, like in [16], allow the definition of a measurement model that links synchrophasor measurements to the magnitude and phase-angle measurement errors and to line parameters deviations from their nominal (or available) values. Thanks to this model, it is possible to express each synchrophasor measurement as function of its reference value (indicated in this paper with superscript R ) and all associated measurement errors as follows:…”

“…where β sr and τ sr are the unknowns relative deviations from the nominal transformer reactance and tap ratio, while X 0 sr and a 0 sr are the associated nominal (or available) values. Like in [16], tap changer ratios are here considered uncertain because they cannot be known exactly.…”

“…The proposed methodology is inspired by the outcomes of [15] and [16], where a traditional model of the tap-changing transformer was applied, and therefore the simultaneous estimation of systematic measurement errors along with the parameters associated with π-models of transmission lines and tap-changing transformers is conducted: both the systematic and random errors of the measurement chain affecting synchronized measurements in modern power systems are appropriately modelled and taken into account. With respect to [15] and [16], the more general model of tap-changing transformer is now introduced in the estimation framework, which is therefore completely redesigned relying on new constraints among the measurements and the quantities to estimate.…”

Deep Learning for Short-Term Voltage Stability Assessment of Power Systems

“…Reference [9] mentioned the problem of data loss caused by PMUs and reference [10] showed a method of using PMUs' synchronous measurement data to determine the uncertainty bounds of transmission lines. Reference [11] designed a PMU-based robust state estimation method for real-time monitoring of a power system under different operational conditions, and reference [12] constructed a Kalman filter approach to power system state estimation based on PMUs. The real-time assessment of STVS is based on the dynamic information collected by PMUs after the power system experiences disturbances, and the power system will trigger emergency control in a timely manner when an unstable state is predicted.…”