Calculating sequence impedances of transmission line using PMU measurements

Zhou, Haibin; Xuanyu, Zhao; Shi, Di; Zhao, Huashi; Jing, Chaoyang

doi:10.1109/pesgm.2015.7285981

Cited by 7 publications

(6 citation statements)

References 9 publications

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“…Normally, synchophasors are communicated to a central computer, and this information can be used to undertake state estimation, fault detection/location and wide area monitoring, including protection [55]- [57]. While the use of synchrophasors from multiple PMUs can be used to measure line impedance [51], [58], [59], the focus of this article is on the local techniques which utilise local measurements only. A single PMU, benefiting from the accurate time stamping of phasors, can be used to estimate the Thévenin equivalent properties of the network.…”

Section: ) Local Pmu Derived Observersmentioning

confidence: 99%

Review of Local Network Impedance Estimation Techniques

et al. 2020

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Section: ) Local Pmu Derived Observersmentioning

confidence: 99%

Review of Local Network Impedance Estimation Techniques

et al. 2020

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“…In practice, these parameters are read off from EMS database and were originally calculated based on tower geometries, conductor dimensions, estimates of line length, and conductor sags, etc. They only approximate the effects of conductor sags and ignore the dependence of impedance parameters on temperature and loading conditions [17]- [18]. Therefore, the challenge is that only approximates of line impedances are known and without knowing their true values the calculated bias errors might be far from being accurate.…”

Section: A Least Square Estimator (Lse)mentioning

confidence: 99%

Online Calibration of Phasor Measurement Unit Using Density-Based Spatial Clustering

Wang

Shi

Wang

et al. 2018

IEEE Trans. Power Delivery

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Abstract-Data quality of Phasor Measurement Unit (PMU) is receiving increasing attention as it has been identified as one of the limiting factors that affect many wide-area measurement system (WAMS) based applications. In general, existing PMU calibration methods include offline testing and model based approaches. However, in practice, the effectiveness of both is limited due to the very strong assumptions employed. This paper presents a novel framework for online bias error detection and calibration of PMU measurement using density-based spatial clustering of applications with noise (DBSCAN) based on much relaxed assumptions. With a new problem formulation, the proposed data mining based methodology is applicable across a wide spectrum of practical conditions and one side-product of it is more accurate transmission line parameters for EMS database and protective relay settings. Case studies demonstrate the effectiveness of the proposed approach.

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“…Other authors use PMU measurements in combination with a small number of calibrated instrument transformers to calibrate instrument transformers in the whole network [25]. In [23], a simulation of positive‐sequence parameter errors based on Monte Carlo (MC) simulations is presented. A main drawback of this strategy is that performing these simulations for a wide variety of input parameters is computationally and timewise intensive.…”

Section: Introductionmentioning

confidence: 99%

“…Some authors focus on the measurement of positivesequence components, but not on zero-sequence components [20]. A number of studies take the associated measurement errors into account when reconstructing three-phase transmission line parameters using PMU measurements [21][22][23]. PMU measurements were demonstrated to be of use to calibrate instrument transformers when one highly accurate instrument transformer is present and PMU are installed on both sides of a transmission line [24].…”

Section: Introductionmentioning

confidence: 99%

Zero‐Sequence current measurement uncertainty in three‐phase power systems during normal operation

Nauta

Serra

2021

IET Generation Trans & Dist

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Zero‐sequence currents in high‐voltage power systems during normal operation can have a significant influence on nearby infrastructure. It is therefore necessary to gain insight into typical levels of zero‐sequence currents in a variety of operational situations. Measurements can provide this insight. When performing measurements, one needs to know the uncertainty associated with the measurement to draw accurate conclusions. The measurement uncertainty associated with three different practical strategies to measure zero‐sequence currents during normal operation are studied: a direct and indirect measurement strategy using current clamps and oscilloscopes and a measurement strategy using phasor measurement units (PMU). Measurement uncertainty is studied using two methods: by analytical expressions and by Monte Carlo simulations. Both methods give consistent outcomes for the measurement uncertainty and show the same tendencies of the zero‐sequence current measurement uncertainty as a function of the positive‐sequence current. This paper studies measurement strategies with error sources based on realistic measurement devices that could be used in practice. The following outcomes were found: in the direct strategy, the primary current transformers are the largest uncertainty sources; in the indirect strategy, the current clamps are the largest uncertainty sources; in the PMU strategy, the PMU total vector error is the largest uncertainty source.

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Calculating sequence impedances of transmission line using PMU measurements

Cited by 7 publications

References 9 publications

Review of Local Network Impedance Estimation Techniques

Review of Local Network Impedance Estimation Techniques

Online Calibration of Phasor Measurement Unit Using Density-Based Spatial Clustering

Zero‐Sequence current measurement uncertainty in three‐phase power systems during normal operation

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