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8/8/2019 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.
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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
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ICACCT, Nov 08 th 2008
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:
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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
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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