Introduction Transmission Line Impedance Estimation Using SCADA Data Project Background Application to Real SCADA Data University of Alberta researchers: Yang (Frank) Wang Industry collaborators: James Shen Line parameters, i.e. the series resistance, series reactance, and shunt admittance of a line, are critical input data for a wide variety of power system analysis programs. Accuracy of line parameters is essential to ensure adequate analysis and prediction of power system responses. These parameters can also be used to find abnormal operating conditions of conductors. In Alberta, the parameters of a transmission line are calculated based on the structure and material information of the line. It is important to actually measure the line parameters to verify if the calculated parameters have acceptable accuracy. R X G/2 B/2 G/2 B/2 Sending End: V s,rms , P s , Q s I rms Receiving End: V r,rms , P r , Q r S 2 , P 2 , Q 2 S 1 , P 1 , Q 1 Transmission Line Model: Objective: To measure line parameter, i.e. R - line resistance and X – Line reactance, B – shunt capacitance and G – shunt conductance (corona). Available Information: SCADA data, i.e. voltage magnitude (V rms ), active power (P) and reactive power (Q) of two ends. Potential Applications: The proposed method is an online tracking of line impedance, many potential applications can be expected. For example, 1) online condition monitoring of the transmission line, 2) Update the inputs to diverse power system analysis programs and algorithms, such as protective relaying algorithms and power flow analysis, ……. Proposed Algorithm ① The total active power loss of the line equals to the loss on R, which is a function of the current and the loss on G, which is a function of the voltage. (1) ② The total reactive power change of the line equals to the loss on X, which is a function of current and the compensation from B, which is a function of voltage. (2) ③ The current magnitude of "R & X branch" (I rms ) can be calculated by either sending end data or receiving end data (3) Using Equation (1)~(3), transmission line parameter can be solved ! Additionally, a data selection method is further proposed based on to minimize the impact of error in SCADA data. In Equation (1) and (2), s is the coefficient of R and X, which means that the impact of error in SCADA data (V, P, Q) decreases with the increase of . Therefore, we only trust 5% estimation results calculated with largest . 2 2 2 ( ) 2 2 s r rms s r V G V G I R P P 2 2 2 ( ) 2 2 s r rms s r V B V B I X Q Q 2 2 2 2 2 2 2 2 2 2 ( / 2) ( / 2) ( / 2) ( / 2) s s s s r r r r rms s r P V G Q V B P V G Q V B I V V 0 2000 4000 6000 8000 10000 12000 14000 16000 18000 0 100 200 MW summer 0 2000 4000 6000 8000 10000 12000 14000 16000 18000 -50 0 50 MVar 0 2000 4000 6000 8000 10000 12000 14000 16000 18000 240 250 260 kV sending end receiving end 0 2000 4000 6000 8000 10000 12000 14000 16000 18000 -150 -100 -50 MW winter 0 2000 4000 6000 8000 10000 12000 14000 16000 18000 20 40 60 MVar 0 2000 4000 6000 8000 10000 12000 14000 16000 18000 250 255 260 kV sending end receiving end 0 2000 4000 6000 8000 10000 12000 14000 16000 18000 0 100 200 MW fault date 0 2000 4000 6000 8000 10000 12000 14000 16000 18000 -50 0 50 MVar 0 2000 4000 6000 8000 10000 12000 14000 16000 18000 245 250 255 kV sending end receiving end 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 2 4 6 8 10 12 14 I rms (kA) p.u. summer R-est X-est R-ref X-ref 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0 5 10 15 I rms (kA) p.u. winter R-est X-est R-ref X-ref 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 2 4 6 8 10 12 14 I rms (kA) p.u. faultdate R-est X-est R-ref X-ref 925L R X Given value 1.68 9.70 Summer peak 2.14 ±0.27 9.61 ±0.38 Winter peak 1.74 ±0.14 9.78 ±0.31 Fault day Proposed method 1.63 ±0.17 9.57 ±0.30 Relay data using phasor based method 1.70 9.68 0 2000 4000 6000 8000 10000 12000 14000 16000 18000 -300 -200 -100 MW summer 0 2000 4000 6000 8000 10000 12000 14000 16000 18000 0 20 40 MVar 0 2000 4000 6000 8000 10000 12000 14000 16000 18000 250 255 260 kV sending end receiving end 0 2000 4000 6000 8000 10000 12000 14000 16000 18000 -400 -300 -200 MW winter 0 2000 4000 6000 8000 10000 12000 14000 16000 18000 -100 0 100 MVar 0 2000 4000 6000 8000 10000 12000 14000 16000 18000 0 200 400 kV sending end receiving end 0 2000 4000 6000 8000 10000 12000 14000 16000 18000 -200 -100 0 MW fault date 0 2000 4000 6000 8000 10000 12000 14000 16000 18000 -50 0 50 MVar 0 2000 4000 6000 8000 10000 12000 14000 16000 18000 250 255 260 kV sending end receiving end 0.5 1 1.5 0 5 10 15 I rms (kA) p.u. summer R-est X-est R-ref X-ref 0.5 1 1.5 0 5 10 15 I rms (kA) p.u. winter R-est X-est R-ref X-ref 0.5 1 1.5 0 5 10 15 I rms (kA) p.u. faultdate R-est X-est R-ref X-ref rms I rms I rms I rms I Two real transmission lines are tested by the proposed algorithm. For each of line, three different days’ SCADA data are employed for calculation, which are winter peak, summer peak and fault day. Fault day means that there was a line fault happened at that day and we have obtained the corresponding fault recorder data from relays. The fault recorder data can be used to estimate line parameters by using phasor based method. Thus, results obtained from two different methods can be used to crosscheck. Line 1 - 925L Raw SCADA Data Measured Line Impedance Line 2 - 903L Raw SCADA Data Measured Line Impedance Summary 903L R X Given value 1.45 9.08 Summer peak 1.48 ±0.05 9.03 ±0.08 Winter peak 1.17 ±0.05 9.09 ±0.10 Fault day Proposed method 1.45 ±0.06 9.03 ±0.21 Relay data using phasor based method 1.41 8.94