Estimation of Impedance and Susceptance Parameters of a 3-Phase Cable System Using PMU Data

Abstract

This paper proposes a new regression-based method to estimate resistance, reactance, and susceptance parameters of a 3-phase cable segment using phasor measurement unit (PMU) data. The novelty of this method is that it gives accurate parameter estimates in the presence of unknown bias errors in the measurements. Bias errors are fixed errors present in the measurement equipment and have been neglected in previous such attempts of estimating parameters of a 3-phase line or cable segment. In power system networks, the sensors used for current and voltage measurements have inherent magnitude and phase errors whose measurements need to be corrected using calibrated correction coefficients. Neglecting or using wrong error correction coefficients causes fixed bias errors in the measured current and voltage signals. Measured current and voltage signals at different time instances are the variables in the regression model used to estimate the cable parameters. Thus, the bias errors in the sensors become fixed errors in the variables. This error in variables leads to inaccuracy in the estimated parameters. To avoid this, the proposed method uses a new regression model using extra parameters which facilitate the modeling of present but unknown bias errors in the measurement system. These added parameters account for the errors present in the non- or wrongly calibrated sensors. Apart from the measurement bias, random measurement errors also contribute to the total uncertainty of the estimated parameters. This paper also presents and compares methods to estimate the total uncertainty in the estimated parameters caused by the bias and random errors present in the measurement system. Results from simulation-based and laboratory experiments are presented to show the efficacy of the proposed method. A discussion about analyzing the obtained results is also presented.

PMU-Based Cable Temperature Monitoring and Thermal Assessment for Dynamic Line Rating

“…Deviations in estimates of the elements of B and Z matrices were calculated. For the simulated system, it was observed in [15] that the error in is most sensitive to K 1 . It was found that ignoring coefficients K 1 alone could lead to a maximum error of 15% in B estimates.…”

“…Accurate modelling of the cable system impedance and admittance matrix is of prime importance as it facilitates the selection of significant parameters to estimate. Impedance and admittance models of overhead line and a cable for 3-phase parameter estimation is shown in [10] and [15] respectively. The cable section in the grid was a 3-core cable whose cores are arranged in a trefoil arrangement.…”

Joint Detection and State Estimate with GSAs in PMU-Based Smart Grids

“…Phasor Measurement Units (PMUs) based on global positioning system have been widely used in wide area measurement system [1,2]. PMU is an advanced digital instrument used for real-time monitoring of grid operation in smart grids.…”