Transmission Lines Positive Sequence Parameters Estimation and Instrument Transformers Calibration Based on PMU Measurement Error Model

TL;DR

This paper presents a novel method for estimating transmission line parameters and calibrating instrument transformers using PMU measurement error models, enhancing accuracy in power system modeling.

Contribution

It introduces a new estimation and calibration methodology based on Least Squares and a PMU error model applicable to transposed and un-transposed lines.

Findings

Effective parameter estimation demonstrated on IEEE 118-bus system

Calibration improves measurement accuracy and system reliability

Method requires only one reference measurement set

Abstract

Phasor Measurement Unit measurement data have been widely used in nowadays power system applications both in steady state and dynamic analysis. The performance of these applications running in utilities' energy management system depends heavily on an accurate positive sequence power system model. However, it is impractical to find this accurate model with transmission line parameters calculated directly with the PMU measurements due to ratio errors brought by instrument transformers and communication errors brought by PMUs. Therefore, a methodology is proposed in this paper to estimate the actual transmission lines parameters throughout the whole system and, at the same time, calibrate the corresponding instrument transformers. A PMU positive sequence measurement error model is proposed targeting at the aforementioned errors, which is applicable to both transposed and un-transposed transmission lines. A single line parameters estimation method is designed based on Least Squares Estimation and this error model. This method requires only one set of reference measurements and the accuracy can be propagated throughout the whole network along with the topology acquired by the introduced Edge-based Breadth-first Search algorithm. The IEEE 118-bus system and the Texas 2000-bus system are used to demonstrate the effectiveness and efficiency of the proposed method. The potential for deployment in reality is also discussed.