Conference Paper2-08 File1

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ICACCT, Nov 08 th 2008

Intelligent“Transformer Faults monitoring system

"using FLC and ANN techniques.

V. T. Barhate Dr. K. L. Thakre Dr. S.S. Limaye

(Dept. of Electrical Engg.) (Prof. in Electrical Engg.) (Prof & Principal)

S.R.K.N.E.C, Nagpur V.N.I.T., Nagpur S.R. K.N. E.C., Nagpur

[email protected] [email protected]

1.INTRODUCTION Maintaining the health and reliability of the power

transformer has been a concern for many years. For this

reason, maintenance engineers would periodically take

transformers and circuit breakers off-line, in order to assess

whether the equipment is operating normally. With thismethod, there are still catastrophic failures.

Transformer is an indispensable part for any power

system and hence its protection becomes prime necessity

and the selection of the method used for protection becomes

a crush. The universally available protection schemes

sometimes fail for the excitation of the transformer at no

load due to the heavy magnetizing inrush current in the

primary. Hence to avoid the tripping of relay during this

condition, it is necessary to distinguish between themagnetizing inrush current and internal fault current. A

majority of researches are being carried out to build an

algorithm using wavelet transforms and / or Artificial

Neural Networks, Fuzzy Logic Techniques for efficientdiscrimination between magnetizing inrush and internal

faults.

Advanced simulation techniques and recently introduced

artificial neural networks with tremendous training

capability combined with fuzzy logic approaches to power

Transformer protection will provide means to enhance the

classical protection principles and facilitate faster , more

secure and dependable protection for power transformer.

Due to the numerous benefits of digital relaying in terms of

economics, performance, reliability and flexibility,

significant efforts have been made towards the development

of digital relaying algorithms. Numerous algorithms for the

differential protection of power transformers have beenproposed. There are attempts to develop various techniques

to detect a magnetizing inrush current using ANN and

Differential protection using Fuzzy logic. Generally, an

acceptable protection scheme involves features: reliability,

cost, simplicity to use and high speed of operation.

2. OVERVIEW OF PROTECTION SCHEMES The type of protection of the transformers varies depending

on the application and the importance of the transformer.

Transformers are protected primarily against faults

and overloads. The type of protection used should minimize

the time of disconnection for faults within the transformer

and to reduce the risk of catastrophic failure to simplify

eventual repair. Any extended operation of the transformerunder abnormal condition such as faults or overloads

compromises the life of the transformer, which means

adequate protection should be provided for quicker isolation

of the transformer under such conditions. Various schemes

for power transformer protection are:

1. Percentage Differential Protection

2. Over current protection of transformer

3. Over-fluxing protection

4. Hottest-Spot Winding Temperature Protection :

5. Sensitive ground fault protection to limit

transformer damage

2.1 PERCENTAGE DIFFRENETIAL RELAY:

The disadvantage of the current differential protection is

that current Transformers must be identical; otherwise there

will be current flowing through the current relays for faults

outside of the protected zone or even under normal

conditions. Sensitivity to the differential current due to the

current transformer errors is reduced by percentage

differential relays. In percentage differential relays, thecurrent from each current transformer flows through a

restraint coil. The purpose of the restraint coil is to prevent

undesired relay operation due to current transformer errors.

The operating coil current | I1 - I2 | required for tripping is a

percentage of the average current through the restraint coils.

It is given byIdiff > k (I1 + I2)/ 2

Where, k is the proportion of the operating coil current to

the restraint oil. For example if k = 0.1, the operating coil

current must be more than 10% of the average restraint coil

current in order for the relay to operate.




Fig2.1 CIRCUIT FOR THE PERCENTAGE DIFFERENTIAL RELAY

2.2 OPERATING CONDITION As stated above the relay operates when the

differential current exceed some predetermined value. The

driving equation for the relay is as :-

I1 –I2 > B (I1 +I2)/2

Where,

I1= primary current

I2=secondary current

(I1+I2)/2 = restraining current

I1 – I2 = differential current

B= bias2.3 MAGNETIZING INRUSH CURRENT

It is often noticed when switching in a no load transformeran initial current rush greatly in excess of magnetization

current and normal full load current. This may cause

incorrect operation of conventional over current protection

and fuses. Also produced magnetic force may cause

mechanical damage to transformer winding. This is result of

non-linearity of core magnetization curve. No load

transformer switching may create large asymmetric flux and

saturation of winding core of transformer. This saturation

creates high magnitude asymmetrical current with a high

harmonic content and a high direct current component.

The reason for this current rush is to be found in

characteristic shape of magnetism curve of transformer coresteel, which is shown in, and from this it will be seen that

the no load current at unsymmetrical core flux is increased

very high as compared with current under symmetrical core

flux. The initial value of this inrush current is principally

determined by the point of voltage wave at which switching

in occurs, but it is also partly dependent on magnitude and

polarity of residual flux, which may be left in the core after

previous switching out. This residual flux is influence by

transformer core material characteristic, core gap factor,

winding capacitance, circuit breaker, chopping

characteristics and other capacitances connected to the

transformer. As shown in Fig, below at the instant of

switching in, if the voltage be zero, the residual flux will bemaximum and the peak transient core flux will be more than

twice of normal condition flux and this produces a high

magnitude and asymmetrical inrush current.

3. BACKGROUND FOR MODEL DESIGN This paper is an attempt to develop a simulation model in

MATLAB using Fuzzy logic and Neural Network Tool Box

along with Power System Equipments using SIMULINK

which would distinguish between the magnetizing inrush

current and internal fault current to avoid the tripping of

relay .There is a provision for detection of other faults by

simply adding Input signals such as signal through

Temperature sensors etc.A Case study of 50 MVA power

transformer from Wardha City 220/66 KV Substation is




considered and all its specifications are simulated in

MATLAB environment.

Block Diagram shown in Fig3.1. exhibits

components used for simulation of Protection of

Transformer under case study. Current transformers on both

sides i.e. primary and secondary CT’s are used to obtainOperating and Restraining currents using circuits for

calculating Average And Difference of primary and

secondary currents. These Operating and Restraining

currents are given as an input to Fuzzy Information System

(FIS) using Fuzzy Logic Tool Box. FIS model represents

membership functions for input and output. Here Inputs are

Operating and Restraining currents with fuzzified state

developed according to operating and non-operating regions

of Characteristics of Differential Relay shown in Fig.3.1

The output of FIS is Trip signal for Circuit Breaker which is

generated by writing several Fuzzy Rules using knowledge

base of Fuzzy Associated Matrix (FAM).

The present scheme not only caters for Differentialprotection of Power Transformer for various internal faults

but also avoids any malfunction of relay due to Magnetizing

Inrush Current which occurs during excitation of

transformer under no load i.e. while putting the Transformer

in service. This is achieved by using Neural Network Tool

Box . The Primary current is taken as sample and Neural

network is trained for pattern recognition algorithms .It

recognizes and identifies the Short circuit current and

magnetizing inrush current using ANN and enables the

Fuzzy Controller only if there is a Short Circuit current

which is generally Sinusoidal in nature. Thus this scheme

avoids the mal operation of Differential Relay by

identifying magnetizing inrush current.The provision of identifying Hottest-Spot Winding

Temperature using suitable sensors and comparator is kept

and FIS can take care of protecting Transformer since

separate membership function is defined to identify actionto be taken for various temperature ranges.

4. IMPLEMENTATION (SIMULINK MODEL)

4.1 Three phase transformer:- MVA Rating : 40 / 50 MVA, 50 Hz

Voltage : 220 / 66 kVCurrent : 131.2 / 437.38A

Make : Crompton Greaves, BombayYear of Manufacture : 1991

Cooling Provided : ONAN : 40MVA

ONAF : 50 MVAGuaranteed Temp

Rise :

Oil : 500C

Winding : 550CConnection Symbol : YN yno

Untanking Mass : 46800 kgTotal Oil : 25900 / 29600 kg

Total Mass : 9700 kg

Heaviest Package : With oil : 79700 kgWithout oil : 59000 kg

HV WT1 CT

Ratio :

/ 1.8, 1.9, 2.1, 7.5VA, Class 5 connect

terminals 1V1S1 & 1V1S3

Circuit breaker : - Initial status = CLOSED

Switching of all phases

External control of switching times

Breaker resistance Ron = .001 Ω

Snubber resistance Rp = 1 MΩ

Snubber capacitance = 1mF

Current transformers: - A two winding saturable

transformer has been used with following specifications. CT ratio (primary)=10.497/1

CT ratio(secondary)=278.24/.577

Nominal power & frequency = 10 VA,50 Hz

Winding 1 parameters = V1(rms)= 1

pu,R1(pu)=.02,L1(pu)=.08pu

Winding 2 parameters=V2

(rms)=10.497pu,R2(pu)=.02,L2(pu)=.08pu

3 phase RLC series load with Yg connection

Phase to phase voltage = 415 V

Active power = 200 KW

Relay Characteristics for operating Current Versus

Restraining current is drawn with reference to chosen

transformer of 50 MVA, CT’s ratio , driving equation I1 –I2 > B (I1 +I2)/2. It is possible to draw the relay characteristics

for different percentage Bias values of B. Here it is drawn

without % Bias. Fuzzy Membership functions for operating

Current and Restraining current are assigned based on this

Characteristic(Fig 4.1). The MATLAB Simulink Model is

as shown in Fig.4.2

5. RESULTS 1. No fault condition : Primary current Approx 173 Amps. And Secondary

current Approx.600Amps is snown in Figure given below:

2. Three phase-to-ground Fault simulated after 20 msec : Fault current at

Primary side approx. 3500 Amps. lasted for 1 Cycle and Circuit Breaker

opened is shown in Figure given below:




3. Waveforms of Differential and Restraining current for Three phase-to-

ground fault and second waveform shows Trip signal (active low) after20 msec. is shown in Figure given below:

4. Line-to-ground fault (in phase A ) Fault current approx. 3400 Amps is

shown in Figure give1n below:

5. External Fault : If the fault is outside the unit protection zone thenDifferential Relay does not operate and Fault currents at primary and

secondary are very large is shown in figure given below:

6. Waveforms of Differential and Restraining current for External fault

and second waveform shows Trip signal is not activated is shown in

figure given below:

6. Magnetizing Inrush current pattern identification is done. first for

Fault current having sinusoidal current waveforms Neural Network givesenable to Fuzzy logic and hence Differential Relay is activated only under

fault condition. And secondly when ever there is non-sinusoidal waveform

the Neural network identifies it as a magnetizing Inrush current andtherefore Neural Network does not give enable signal to fuzzy logic and

there is no mal-operation of Relays is shown in figure given below:

Fig 4.1: Relay Characterstics for operating current Vs Restraining current

REFERENCES

1. V. T. Barhate & Sangeeta H. Deshmukh, “Neruro Fuzzy based

differential protection of transformer”, PECA-IFTOMM 2006,

International Conference 12

th

July 2006. 2. V.T. Barhate & etal., “Fuzzy logic, an alternate tool for protection

against internal faults in transformer”, ICACCT-07,Panipat.

3. S. E. Zocholl, Armando Guzmán, and Daqing Hou, “Transformer

modeling as Applied to Differential Relaying ,” Proceedings of the 22nd

Annual Western Protective Relay Conference, Spokane, WA, Oct, 1996.

4. M.C. Shin, C.W.Park and J.H.Kim, " Fuzzy Logic-Based Relaying for

large Power Transformer Protection, " IEEE Transaction on Power

Delivery, Vol. 18, No. 3, pp. 718-724, July 2003.5. Xu, W., Wang, D., Zhou, Z., and Chen, H. 1997. Fault Diagnosis of

Power Transformers: Application of Fuzzy Set Theory, Expert Systems,

and Artificial Neural Networks. IEEE Proceedings of Science,

Measurement, and Technology, 144(1), pp. 39-44.

6. Khorashadi – Zadeh,H. “Fuzzy – neuro approach to differentialprotection for power transformer” TENCON 2004. IEEE 10 Conference

21-24 Nov 2004, PP 279-282




50MVA, 220 / 6 6kV

Power Transformer

VARIOUS PROTECTION SCHEMES OF POWER TRANSFORMER

[ USING FUZZY CONTROLLER & ARTIFICIAL NEURAL NETWORK ]

Other Faults

Continuous

powergui

S1Rin

Yin

Bin

I2

Rout

Yout

Bout

Secondary CT's

Scope

RMS

RMS2

RMS

RMS1S1Rin

Yin

Bin

I1

Rout

Yout

Bout

Primary CT's

S1Rin

Yin

Bin

Rout

Yout

Bout

Overload ,

Temperature relay

A

B

C

Load

Ip & Is

A

B

C

A

B

C

Internal Fault

Idiff / Ires / Trip

Fuzzy Logic

Controller

p1y1

Fault Monitor

A

B

C

A

B

C

External Fault

0.5437

Display1

1.915e-005

Display

Digital

Output

Digital Output

Standard Dev ices

Parallel Port [378h]

I r e s

I d i f f

I 1 I 2

Diffrential Relay

com

A

B

C

a

b

c

CB

i+

-

A1

A

B

C

a

b

c

A

B

C

3Ph 220kV Bus

Is

Ires

Ires

Idiff

Idiff

Ip

Ip

Trip

Trip

Trip

Trip

Figure 4.2: MATLAB Simulation Model

Magnetizing Inrush Sample

(I1+I2) / 2

RestrainingCurrent

220 / 66 KV

I1

Figure 3.1: Schematic for Transformer protection using Fuzzy-Neuro techniques.

Fault

Simulator

I2

Enable

Temperature

NEURAL

NETWORK

For Pattern

Recognizing of

Magnetizing

Transformer

50 MVA

220 KV

Three

Phase

Source

Bus

Feeder

Circuit

Breaker

I1-I2

Operating

Current Trip

Signal

Output

FUZZY

LOGIC

Controller

Differential

Relay

Characterist

Conference Paper2-08 File1

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