A Novel Approach to Noninvasive Measurement of Overhead Line Impedance Parameters

Ritzmann, Deborah; Rens, Johan; Wright, P.S.; Holderbaum, William

doi:10.1109/tim.2017.2665958

Cited by 31 publications

(17 citation statements)

References 14 publications

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“…In the following, we assume that we have determined prior limits on maximum line resistance and reactance errors, as well as maximum ratio and phase displacement errors for transducers. When more accurate information is available , it can be used to redefine the uncertainties in (10) or to redefine parameters in (3).…”

Section: A Definition Of the Network And Measurement Modelmentioning

confidence: 99%

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Line Impedance Estimation Based on Synchrophasor Measurements for Power Distribution Systems

Pegoraro

Brady

Meier

2019

IEEE Trans. Instrum. Meas.

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Effective monitoring and management applications on modern distribution networks require a sound network model and the knowledge of line parameters. Network line impedances are used, among other things, for state estimation and protection relay setting. Phasor Measurement Units (PMUs) give synchronized voltage and current phasor measurements, referred to a common time reference (coordinated universal time). All synchrophasor measurements can thus be temporally aligned and coordinated across the network. This feature, along with high accuracy and reporting rates, could make PMUs useful for the evaluation of network parameters. However, instrument transformer behavior strongly affects parameter estimation accuracy. In this paper, a new PMU-based iterative line parameter estimation algorithm for distribution networks, which includes in the estimation model systematic measurement errors, is presented. This method exploits the simultaneous measurements given by PMUs on different nodes and branches of the network. A complete analysis of uncertainty sources is also performed, allowing the evaluation of estimation uncertainty. Issues related to operating conditions, topology and measurement uncertainty are thoroughly discussed and referenced to a realistic model of a distribution network to show how a full network estimator is possible.

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Section: A Definition Of the Network And Measurement Modelmentioning

confidence: 99%

“…In this context, the accuracy of any measurement device is an important prerequisite for the overall accuracy of the estimation results. It is important to mention here, though, that there are many uncertainty sources that cannot be neglected [10].…”

Section: Introductionmentioning

confidence: 99%

Line Impedance Estimation Based on Synchrophasor Measurements for Power Distribution Systems

Pegoraro

Brady

Meier

2019

IEEE Trans. Instrum. Meas.

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“…In the recent past, methods have been presented that utilize PMU data to estimate the overhead-line parameters [4][5][6][7][8]. These methods estimate line parameters utilizing voltage and current phasors at both ends of the line segment and could give frequent parameter estimates.…”

Section: Introductionmentioning

confidence: 99%

“…Three-phase lines have mutual coupling elements and estimating the parameters has challenges in terms of modeling and signal excitation requirements. Hence, it was noted in [7] that the application of such an algorithm for 3-phase lines would require more complex models. Also, no tests were done to demonstrate the performance of the method for actual measurements.…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2019

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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.

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“…The use of the total least-squares (TLS) technique for estimating TL parameters is proposed in [17]. [21] and [22] propose methods for eliminating systematic errors introduced by ITs into the measurements. However, these methods assume the TLs to be fully transposed and symmetric.…”

mentioning

confidence: 99%

Parameter Estimation of Three-Phase Untransposed Short Transmission Lines From Synchrophasor Measurements

Wehenkel

Mukhopadhyay

Boudec

et al. 2020

IEEE Trans. Instrum. Meas.

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We present a new approach for estimating the parameters of three-phase untransposed electrically short transmission lines using voltage/current synchrophasor measurements obtained from phasor measurement units. The parameters to be estimated are the entries of the longitudinal impedance matrix and the shunt admittance matrix at the rated system frequency. Conventional approaches relying on the admittance matrix of the line cannot accurately estimate these parameters for short lines, due to their high sensitivity to measurement noise. Our approach differs from the conventional ones in the following ways: First, we model the line by the three-phase transmittance matrix that is observed to be less sensitive to measurement noise than the admittance matrix. Second, we compute an accurate noise covariance matrix using the realistic specifications of noise introduced by instrument transformers and phasor measurement units. This noise covariance matrix is then used in least-squares-based estimation methods. Third, we derive different least-squares-based estimation methods based on a statistical model of estimation and show that the weighted leastsquares and the maximum likelihood methods, which make use of the noise covariance matrix produce the best estimates of the line parameters. Finally, we apply the proposed methods to a real dataset and show that our approach significantly outperforms existing ones. I. INTRODUCTION Fundamental functionalities used in the operation of power grids, e.g., state estimation (SE) [1], [2], [3], optimal power flow (OPF)-based control [4], [5], [6], [7], , Model Predictive Control [8], [9] and optimal relay tuning [10], [11], require the knowledge of transmission line (TL) parameters at the rated system frequency. Conventionally, TL parameters are obtained either by using the physical properties of the line (such as conductor dimensions, types of wires, tower geometries, ground electrical parameters) [12], [13] or by making measurements on the line when it is off-grid [14]. The first method is applicable only when accurate conductor characteristics are known, whereas the second method, although reliable, is time consuming and difficult to implement in practice. With the availability of highly accurate measurement devices, e.g., phasor measurement units (PMUs), instrument transformers (ITs), estimation methods based on measurements from these devices have gained significant research

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A Novel Approach to Noninvasive Measurement of Overhead Line Impedance Parameters

Cited by 31 publications

References 14 publications

Line Impedance Estimation Based on Synchrophasor Measurements for Power Distribution Systems

Line Impedance Estimation Based on Synchrophasor Measurements for Power Distribution Systems

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

Parameter Estimation of Three-Phase Untransposed Short Transmission Lines From Synchrophasor Measurements

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