Online Tracking of Transmission-Line Parameters Using SCADA Data

Abstract

Series impedance and shunt admittance parameters of transmission lines are fundamental data for various online and offline power system studies. This paper shows that the active power, reactive power and voltage magnitude (P, Q, V) data measured at the two ends of a transmission line are sufficient to determine the positive sequence line parameters. The phase angle information is not essential. Since the P, Q and V data are readily available from the supervisory control and data acquisition (SCADA) systems, the proposed method can be easily implemented in existing control centers. Algorithms, characteristics, performances and potential applications of the proposed method are presented in this paper. Simulation study and field test results show that the proposed technique can be a useful addition to the energy management systems (EMS) of utility companies.

Measurement-Based Transmission Line Parameter Estimation With Adaptive Data Selection Scheme

“…Scheme 5 has the same time window as scheme 1, and all data points in the time window are selected. Scheme 6 is the 6-point in 30 minutes scheme of [15] and scheme 7 is the 200-point in 1 day scheme of [12]. It can be seen from TABLE III that the RSD of scheme 1 is much less than that of schemes 2~4.…”

“…Transmission line parameter can be estimated with SCADA or WAMS data. Since SCADA is a basic infrastructure of modern power systems and covers wider areas than WAMS [15], the SCADA data are used in this paper to build the following parameter estimation model.…”

“…In [14], a single point estimation model was proposed to estimate the parameters of long transmission lines. In [15], with field SCADA data, a multi-point parameter estimation model was developed based on the Levenberg-Marquardt algorithm. In [16] and [17], WAMS and SCADA data were incorporated for estimating multi-terminal transmission lines with a nonlinear weighted least square algorithm.…”

“…However, due to measurement error, more data points tend to increase the chance of nonconvergence of estimation [15]. Therefore, it is necessary to select appropriate measured data for estimation.…”

“…In [10], 8 sets of simulated data within 16 minutes were chosen for estimation with even time interval of 2 minutes. In [12] Through extensive tests, a data selection scheme was developed in [15] to show how to select 6 data points from a time window of 30 minutes. The aforementioned data selection schemes in literatures are different which indicates that there is no uniform data selection scheme suitable for all lines.…”