A seminar presentation on ONLINE TRACKING OF TRANSMISSION LINE PARAMETERS USING SCADA DATA

By:A.YUVA KISHORE15121D0701

Under the guidance ofMr.G.RAVINDRA, M.Tech,Assistant Professor.

DEPARTMENT OF ELECTRICAL AND ELECTRONICS ENGINEERING

SREE VIDYANIKETHAN ENGINEERING COLLEGE

RANGAMPET, TIRUPATI ,INDIA– 517 1022015 - 2017

Index:1.Introduction2.Methods of Tracking the line parameters3.Formulation of proposed method4.Study of results5.Conclusion6.References

1.INTRODUCTION

Transmission line parameters(T.L parameters): Series Resistance(R) SeriesReactance(X)Shunt susceptance(B) Shunt conductance(G)

Need for accurate T.L parameters:Prerequisites for operation,control and planning

of modern power systemsPower system analysis such as power flow

calculation, short circuit calculation, relay settings, fault locating

For system simulation studies like Transient stability,State estimation ..etc

Variation of T.L Parameters: Due to different operating and external

conditions the T.L parameters will changes

The dc resistance of line changes significantly with the temperature

  Where R2, R1 = resistances at temperatures T2

and T1 α = temperature coefficient

Skin effectChanges in Capacitance of line due to “Sag”External factors

R2 = R1[1 + α(T2-T1)]

2.METHODS OF TRACKING THE LINE PARAMETERS

Classical methods(off-line methods) : T.L parameters are conventionally calculated using

factors of conductor type, conductor geometry, assumed ambient conditions.

These methods doesn’t reflects the changes in parameters due to varying operating and ambient conditions and also required more wiring & meters

Online methods:The Synchronized phasor measurement

technology(PMU) opens a path for online parameter identification.PMU computes voltage and current phasors and equips the measurements

…….continued

A distributed line model has been applied for estimating transmission line positive sequence parameters based on non-linear estimation theory

Some online parameter estimation methods using PMU technology: Transmission line parameter identification using PMU

measurements Online optimal transmission line parameter

estimation for relaying applications Online estimation of transmission line parameters,

temperature and sag using PMU measurements

Drawback:For a transmission line PMUs are to be installed at sending and recieving ends.In practical modelling, it is not possible for all the lines

Alternatives:Method of live line measuring the inductance

parameters of transmission lines based on GPS technology

Parameter estimation of multi-terminal transmission lines using joint PMU and SCADA data

New approach: Makes Phasor data is not essential for line parameter

estimation P,Q and │V│ data measured from the both ends of

line are sufficient, which are provided by Supervisory-control-and-data-acquisation (SCADA) systems

Thus phase-angle(δ) information is redundant SCADA provides P,Q and│V│ data in (4 to 10) seconds

continously

Functional units of SCADA

3.FORMULATION OF PROPOSED METHOD

Conditions: Fully transposed Per phase quantities Line to neutral voltages

Pi-model

From the above model ,the line current (IL) is caluculated as follows

OR

Active power loss due to R,G

Reactive power loss due to X,G

𝐼𝐿=√(𝑃𝑟−

│𝑉 𝑟❑│2𝐺2 )+(𝑄𝑟+

│𝑉 𝑟❑│2𝐵2

)

│𝑉 𝑟│

+()

+()

(a) Method based on neglecting the shunt conductance:

number of equations = 3 number of unknowns = 4 (R,X,G,B)

Neglect the parameter shunt conductance(G) from all equations(b) Single-point method:

Consider wave propagation equation of transmission line

Where f = fundemental frequency l = length of transmission line

Numerical solution: Levenberg- Marquadt algorithm (LM

algorithm)

Combines the advantages of Gradient-Descent method and Gauss-Newton method i.e.,gaurantee and faster convergence respectively

Better solution is obtained even initial guess is far off final valueThe solution procedure is as follows:

An objective function F(Z) is formulated as a sum of squares of the estimation error

Where ε is estimation error Z is set of unknown parameters i.e., Z = [R,X,G,B]

=

To find the solution ‘Z’ ,F(Z) is minimized. LM algorithm solves Z iteratively by using the

following two equations

¿𝒁 𝒌+𝟏=𝒁𝒌+∆ 𝒁𝒌

Where = Gradient of Z i.e., ΔZk is incremental/decremental value of Z k is the iteration number is the constant and known as damping parameterThe solution converges in five to six iterations

[𝛛𝐅𝛛𝐑

𝛛𝐅𝛛 𝐗

𝛛𝐅𝛛𝐆

𝛛𝐅𝛛𝐁 ]  

𝑻

(C).Multiple point method:

Multiple points are selected optimally 6 pointsRewriting the above equations for multiple point form

where i = 1, 2 , …..6

And the objective function is

=

() =

+()=

𝑭 (𝒁 )=∑𝒊=𝟏

𝟔(𝜺¿¿𝟏 𝒊¿¿𝟐+𝜺𝟐 𝒊

𝟐+𝜺𝟑 𝒊𝟐)¿¿

4.STUDY OF RESULTS(a) Impact of corona loss:

Corona loss(in kW / km)

Method R X B

0 Single-point 0.80% 0.90% 0.38%Multiple-point 0.24% 0.27% 0.14%Method neglect G

0.23% 0.27% 0.14%

5 Single-point 0.80% 0.90% 0.38%Multiple-point 0.25% 0.27% 0.14%Method neglect G

17.55% 24.60% 12.79%

10 Single-point 0.80% 0.90% 0.38%Multiple-point 0.24% 0.27% 0.14%Method neglect G

35.33% 49.33% 25.43%

(b) Impact of unbalance:

Method R X BSingle-point method

0.27% 0.24% 0.97%

Multiple-point method

0.84% 0.64% 0.12%

Method neglect G 1.11% 1.06% 0.20%(c) Impact of measurement errors:

Method R X BSingle-point method

2.35% 0.67% 0.5%

Multiple-point method

3.24% 1.16% 0.34%

Method neglect G 12.11% 13.86% 11.60%

5.APPLICATIONS

1. Validate the database results2. Support state Estimator3. Estimation of Corona Loss

6.CONCLUSION

Importance of knowledge of T.L.parametersBeyond conventional methods, Three

methods namely Method neglecting ‘G’, Single-point method and Multiple-point method are proposed

P,Q,V data from SCADA are enoughMethod neglecting ‘G’ gives large errorsSingle point method - faster response Multiple point method - slow response

REFERENCES:[1] Yang Wang, Wilsun Xu, James Shen, “Online Tracking of Transmission-Line

Parameters Using SCADA Data”, IEEE Trans. Power Del, vol. 31, no. 2,pp.674-682, April 2016

 [2] S. S. Mousavi-Seyedi, F. Aminifar, and S. Afsharnia, “Parameter estimation

of multiterminal transmission lines using joint PMU and SCADA data,” IEEE Trans. Power Del., vol. 30, no. 3, pp. 1077–1085,Jun. 2015.

 [3] D. Shi, D. J. Tylavsky, K. M. Koellner, N. Logic, and D. E.

Wheeler“Transmission line parameter identification using PMU measurements,”Eur. Trans. Elect. Power, vol. 21, no. 4, pp. 1574–1588, May2011.

 [4] P. Kundur, “Power System Stability and Control”. New York, USA:McGraw-

Hill, 1994.[5] J. J. Grainger and W. D. Stevenson, Power System Analysis. NewYork, USA:

McGraw-Hill, 1994. [6]Minis Thomas,John Douglas,Mc.Donald,”Power system SCADA & smart

grids”,USA:CRC Press,2015 [7]Valentina Cecchi “Temperature dependent Transmission line model for

Electrical power system and thir impacts on system studies”,Ph.D thesis submitted to faculty of Drexel university

 

Queries please….

THANK YOU……..