Abstract

This paper presents a framework for estimating transmission line positive sequence parameters, temperature, and sag utilizing on-line voltage and current phasors measured by Phasor Measurement Units. Transmission line parameters, temperature, and sag are vital inputs to various power system analyses and applications, such as the power flow analysis, the protective relaying application, and the dynamic thermal rating application. In this study, different types of transmission line topology are classified and modeled to facilitate the development of corresponding algorithms. All models are based on distributed parameters, so it automatically considers the shunt capacitance effect of long lines. It is assumed that the line is transposed. The proposed least squares based algorithms harness the non-linear optimal estimation theory and are capable of detecting and identifying bad data, minimizing the impact of measurement errors and thus significantly improving the estimation accuracy. The line temperature and sag are calculated according to the obtained parameter estimates. Numerical case studies based on simulated data are presented.

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