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.

RX

G/2 B/2 G/2 B/2

Sending End:

Vs,rms , Ps, Qs Irms

Receiving End:

Vr,rms , Pr, Qr

S2, P2, Q2S1, P1, Q1

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 (Vrms), 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" (Irms) 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 22( )

2 2

s rrms s r

V G V GI R P P

2 22( )

2 2

s rrms s r

V B V BI X Q Q

2 2 2 2 2 2 2 2

2 2

( / 2) ( / 2) ( / 2) ( / 2)s s s s r r r rrms

s r

P V G Q V B P V G Q V BI

V V

0 2000 4000 6000 8000 10000 12000 14000 16000 180000

100

200

MW

summer

0 2000 4000 6000 8000 10000 12000 14000 16000 18000-50

0

50

MV

ar

0 2000 4000 6000 8000 10000 12000 14000 16000 18000240

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 1800020

40

60

MV

ar

0 2000 4000 6000 8000 10000 12000 14000 16000 18000250

255

260

kV

sending end

receiving end

0 2000 4000 6000 8000 10000 12000 14000 16000 180000

100

200

MW

fault date

0 2000 4000 6000 8000 10000 12000 14000 16000 18000-50

0

50

MV

ar

0 2000 4000 6000 8000 10000 12000 14000 16000 18000245

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

Irms

(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 0.80

5

10

15

Irms

(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

Irms

(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 180000

20

40

MV

ar

0 2000 4000 6000 8000 10000 12000 14000 16000 18000250

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

MV

ar

0 2000 4000 6000 8000 10000 12000 14000 16000 180000

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

MV

ar

0 2000 4000 6000 8000 10000 12000 14000 16000 18000250

255

260

kV

sending end

receiving end

0.5 1 1.50

5

10

15

Irms

(kA)

p.u

.

summer

R-est

X-est

R-ref

X-ref

0.5 1 1.50

5

10

15

Irms

(kA)

p.u

.

winter

R-est

X-est

R-ref

X-ref

0.5 1 1.50

5

10

15

Irms

(kA)

p.u

.

faultdate

R-est

X-est

R-ref

X-ref

rmsI

rmsI

rmsI

rmsI

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