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PROJECT REPORT ON FUZZY CONTROLLER BASED DIFFERENTIAL PROTECTION SCHEME FOR POWER TRANSFORMER

iii CONTENTS Page no.

* ACKNOWLEDGEMENT (i) * CERTIFICATE (ii) * CONTENTS (iii) * ABSTRACT (iv) CHAPTER 1:
1.1 INTRODUCTION. 1.2 MOTIVATION FOR UNDERTAKING THE PROJECT. 1.3 AIMS AND OBJECTIVES OF THE PROJECT.
CHAPTER 2: REVIEW OF LITERATURE.
CHAPTER 3: IMPLEMENTATION OF THE PROJECT. CHAPTER 4: DATA COLLECTION AND ANALYSIS OF THE RESULT. CHAPTER 5: 5.1 DISCUSSION OF THE RESULT AND CONCLUSION. 5.2 DISCUSSION OF THE RESULT AND CONCLUSION.

REFERENC

iv ABSTRACT
The power transformer is an essential component of electrical power system that needs continuous monitoring and effective protection scheme. As, it is very expensive and supplies a large portion of the load in the power system. When protection scheme operates, a large portion of the power system and the load is disconnected and thus reliability of the protection scheme is very much necessary. The most common protection scheme used is the percentage differential logic, that provides discrimination between an internal fault and different operating conditions. Today, the need of the power system is digital and in the presence of the spurious data and noise in the system the protection scheme used may mal operate. Thus, it requires some intelligent technique i.e. fuzzy logic, to deal with the uncertainty and ambiguity in the power system data. This work proposes the development of a new algorithm to improve the differential protection performance by using fuzzy logic. The simulation results are compared with the conventional results.

4
CHAPTER-2

REVIEW OF LITERATURE:

PROTECTION OF POWER TRANSFORMERS:

Large power transformers belong to a class of very expensive and vital components in electric power systems. If a power transformer experiences a fault, it is necessary to take the transformer out of service as soon as possible so that the damage is minimized. The costs associated with repairing a damaged transformer may be very high. The unplanned outage of a power transformer can also cost electric utilities millions of dollars. Consequently, it is of a great importance to minimize the frequency and duration of unwanted outages. Accordingly, high demands are imposed on power transformer protective relays. The requirements include dependability (no missing operations), security (no false trippings), and speed of operation(short fault clearing time).The operating conditions of power transformers do not make, however, the relaying task easy. Protection of large power transformers is perhaps the most challenging problem in the power system relaying area.

5
Problems in differential relaying for power transformer :

Fig-1 Hardware structure of a digital relay for power transformers.
The differential relaying principle is used for protection of medium and large power transformers. This superior approach compares the currents at all the terminals of the protected transformer by computing and monitoring a differential (unbalance) current. The non-zero value of the differential signal indicates an internal fault. However, the transformer operating conditions may introduce problems as presented in Table I. 6
The operating criteria for transformer differential protection used to overcome the reported difficulties can be classified as:
1.The principles broadly used in today’s products.
3.The AI approaches already suggested but not sufficiently investigated.

This classification is reflected in Figure 2.

7
The relaying methods applied in today’s products basically use the current signals and limit the analysis to the fundamental frequency components and higher harmonics of those signals.The advanced numerical principles use more information including voltage signals as well as signal features other than just harmonics.The AI methods tend to utilize all the available information. As shown in the figure, the numerical complexity of an algorithm is the price to pay for processing more information.

Classical restraining criteria:
The Figure 3 presents a simplified flow chart of the logic of a digital differential relay for power transformers.

Fig-3 Simplified flow chart of the logic for digital differential relay for power transformers.

8
Within this frame, the second or higher harmonic are used to prevent false tripping during magnetizing inrush conditions; the fifth harmonic is commonly used to restrain the differential relay during stationary overexcitation conditions; while the biased percentage characteristic is used to prevent false tripping during external faults.However, this traditional approach may not be able to deal with certain problems as revealed in Table 1.

The new operating principles have been invented for digital relays. They result in more involved numerical operations rather then just in simple increase of number of functions known from the era of electromechanical relays and bring certain improvements in protective relaying for power transformers as shown in Table II.

9 Artificial Intelligence methods:
The task of protective relaying is, however, to distinguish between internal faults and other conditions (pattern recognition), and consequently, to initiate or deny tripping (decision making). This brings the application of Artificial Intelligence methods as an alternative or improvement to the existing protective relaying functions.

>Fuzzy Logic approach:

The Figure 4 presents a simplified block diagram of a fuzzy logic based differential relay for power transformers.

The relay employs 12 protection criteria to restraint itself from tripping during inrush, overexcitation and external fault conditions.

1
CHAPTER-1

1.1 INTRODUCTION:

Power transformer protective relay should block the tripping during magnetizing inrush and rapidly operate the tripping during internal faults. Recently, the frequency environment of power system has been made more complicated and the quantity of 2nd frequency component in inrush state has been decreased because of the improvement of core steel. And then, traditional approaches will likely be maloperated in the case of magnetizing inrush with low second harmonic component and internal faults with high second harmonic component. The project proposes a new relaying algorithm to enhance the fault detection sensitivities of conventional techniques by using a fuzzy logic approach. The proposed fuzzy based relaying algorithm uses Mamdani Model for fuzzification of the measurand.
The results obtained were compared with the results obtained by the conventional methods and fuzzy logic proved to be more reliable

1.2 MOTIVATION OF UNDERTAKING THE PROJECT:

The data in the field is captured by the Remote Terminal Unit (RTU) and directly communicated to the main processor for further analysis, without pre-processing. Today, the power systems are designed for large capacity and working near the critical point, due to techno-economic reasons. During the communication from the field to the main processor, the data undergoes various stages from field to control centre are:
1. Capturing the data / signal through transducers and sensors.
2. Conditioning of signal.
3. Conversion of signal using analog to digital converter. 2
4. Spurs and tapping in the transmission lines.
5. Transmission of signal to control centre, situated far away from the field, etc.

Under such circumstances, any load variation frequently changes the configuration of the system and add a large amount of noise, uncertainty, and ambiguity in the data acquired by the SCADA system. It is, therefore essential to pre-process the data before converting them into the engineering unit, scaling, storing and display and decisionmaking.Traditional engineering techniques, combined with serial and bi-valiant-logic-based "Hard" computation have been unable to adequately identify and quantify the non-linear- behavior and dynamics of systems. In order to overcome these limitations, soft computing methods are used. The use of hard computation, to model dynamic power system constrains pose difficulty.
In hard computing, the prime concerns are precision, certainty and rigor. In contrast the soft computing does not demand such a high level of precision and certainty.The point of departure in soft computing is reasoning and decision making, should exploit-whenever possible-the tolerance for imprecision and uncertainty.

Artificial Intelligence methods extract specified features of the signals such as magnitudes, active/reactive powers, impedance components, and compare the signals with appropriate pre-set or adaptable thresholds. Based on such comparisons they generate the tripping signal. The task of protective relaying is, however, to distinguish between internal faults and other conditions (pattern recognition), and consequently, to initiate or deny tripping (decision making). This brings the application of Artificial Intelligence methods as an alternative or improvement to the existing protective relaying functions. 3
Fuzzy logic is a powerful tool for non-probabilistic and illdefined structures. It is based on the mechanism of the human brain - Fuzzy theory simulates psychological features of human brain. It provides us linguistic representation such as slow and fast and thus uses truth degree, which are represented as grade of a membership. 1.3 AIMS AND OBJECTIVES: 1.The main aim of our project is to ‘implement a differential protection relaying scheme of a power transformer using fuzzy logic’. 2.The protection scheme distinguishes the internal faults of the transformer with the other faults (over excitation, external, inrush). 3.The results are also obtained considering the effects of the other faults. This project proposes a new relaying algorithm to enhance the fault detection sensitivities of conventional techniques using fuzzy logic.
4. The algorithm provides the means to enhance the classical protection principles and facilitate faster, more secure and dependable protection for power transformers.

5. Also it is anticipated that in the near future more measurements will be available to transformer relays owing to both substation integration and novel sensors installed on power transformers.

10 CHAPTER 3: IMPLEMENTATION OF THE PROJECT:
SYSTEM PARAMETERS: The simulated power system consists of a 13.8-kV and a 90-MVA (50 Hz) synchronous generator, 13.8:138-kV/138:13.8-kV and 25-MVA three-phase power transformers.

Fig-5 Differential relay connection diagram.

Operating current(Ips-Iss)= 2.11 A.

Restraining current({Ips+Iss}/2)=3.924 A.

Considering a variation of 5.5%(which includes 2% inrush current variation and 3.5% variation for other factors ) in the nominal value of the operating current.

Set-point= 2.205 A.

Therefore,range of current for which the relay is made to operate is 2.085 A - 2.325 A.

11
Fig. 5 shows a typical differential relay connection diagram for the protection of power transformers. In this figure, the connection of current transformers (CTs), coupled with the primary and secondary branches, are shown. Np:Ns is the turn ratio between the primary and secondary windings of the transformer,1:n1 and 1:n2 are the turn ratios between the branches and CTs, selected to make Npn1 = Nsn2 . In normal conditions and external faults for a single-phase transformer, currents ips and iss (secondary currents of CTs) are equal. However, in the case of internal faults, the difference between these currents becomes significant, causing the differential relay to trip.The differential current (also called operating current),id can be obtained as the sum of currents entering and leaving the protected zone, according to equation: Id =| iss+ips|

and it provides a sensitive measure of the fault current. The restraint current; irt = (ips-iss)/2

should also be considered.The relay sends a trip signal to the circuit breaker (CB) when the differential current is greater than the restraint current.

12

Fig.6. Differential characteristic curve.

Fig.6. shows a differential characteristic including operation and restraint zones, a basic pickup threshold , and an unrestrained instantaneous current high set. As mentioned before, certain phenomena can cause a substantial differential current to flow when there is no fault, and then this false differential current is generally sufficient to cause tripping. However, in these situations, the differential protection should not disconnect the transformer because an internal fault is not present.
Magnetizing currents appear during transformer energization due to its core magnetization and saturation. The slope of the magnetization characteristic in the saturated area determines its magnitude. In modern transformers, large inrush currents can be reached. In transformer energization, as the secondary winding is opened, the differential current can reach sufficiently high values, causing a false relay operation. Some authors have studied the modeling of such a situation, showing the predominance of the second harmonic component. It must be emphasized that inrush currents can take place, even when the transformer is 13 connected to a load. Some other phenomena that cause false differential currents are magnetizing inrush currents during an external fault removal, transformer overexcitation, sympathetic interaction, as well as CT saturation.

Requirement:

For differential protection scheme; firstly we have considered internal faults(i.e. the winding related faults)which solely need to be detected by the relay.
Along with the internal faults, the impact on the nominal current value depending upon the other faults such as over excitation ,inrush and external faults has also been considered.The set-point for the relay is set with the variation of 5.5% on the nominal value of the operating current. The relay send a trip signal to the circuit breaker if the fault current exceeds this limit.

Algorithm of the scheme:

In this technique:
_ The criteria signals such as amplitudes, harmonic contents, etc. are fuzzified in order to account for dynamic errors of the measuring algorithms. Thus, instead of real numbers, the signals are represented by fuzzy numbers. Since the fuzzification process provides a special kind of flexible filtering, faster measuring algorithms that speed up the operation of protective relays may be used.

_ The thresholds for the criteria signals are also represented by fuzzy numbers to account for the lack of precision in dividing the space of the criteria signals between the tripping and blocking regions.

14
_ The fuzzy signals are compared with the fuzzy settings. The comparison result is a fuzzy logic variable between the Boolean absolute levels of truth and false.

_ Several relaying criteria are used in parallel. The criteria are aggregated by means of formal multicriteria decision-making algorithms that allow the criteria to be assigned a weight according to the reasoning ability.
_ The tripping decision depends on the multi-criteria evaluation of the status of a protected element (sound vs. faulty). Additional decision factors may include the amount of available information, or the expected costs of relay misoperation.

Fig 7

15
Fig 7 shows the possible configuration for the various effects of other factors in the operating current apart from the internal faults.
The internal fault parameter is ANDed with the result of these factors to generate the tripping signal.
Firstly the membership functions are defined for the various inputs (i.e. the various fault currents) depending on which the UNIVERSE OF DISCOURSE is plotted (using MAMDANI MODEL) and then the RULE BASE is obtained for the same.
The RULE BASE results into RULE VIEW which can be tuned to adjust the ‘TRIPPING POINT’.And then the SURFACE VIEW is obtained which shows the membership functions.

The fuzzified values is obtained in the tabular form using RELATIONAL MATRIX(using min function).

The results obtained after fuzzification are further defuzzified(using centroid method) to give a numeric value which is finally compared with the set values to generate the tripping signal.

16
CHAPTER-4:

DATA COLLECTION AND ANALYSIS OF THE RESULT:

INTERNAL FAULT PARAMETERS:

INPUT:

Membership
Function.

fffghj fu

Internal fault Current

OUTPUT:

OUTPUT
Membership Function

17
RULE BASE:

RULE VIEW:

18
SURFACE VIEW:

M.F.

O/P

COMBINED EFFECT OF OTHER PARAMETERS BASED ON THE LOGIC GATE(Fig 7):

a).INRUSH OR OVEREXCITATION FAULTS:

RULE VIEW:

19
Input1=Inrush current.
Input 2=Overexcitation current.
SURFACE VIEW:

b).INRUSH OR EXTERNAL FAULTS:

RULE VIEW:

Input1=Inrush Fault.
Input2=External Fault. 20
SURFACE VIEW:

c).OVEREXCITATION OR EXTERNAL FAULT:

RULE VIEW:

Input1=Overexcitation Fault.
Input2=External Fault.

21
SURFACE VIEW:

COMBINED EFFECT OF INTERNAL FAULT ANT OTHER FAULTS:

INPUT 1: Member function output of OR gates.

22
INPUT 2: INTERNAL CURRENT

OUTPUT:

23
FINAL RULE VIEW:

FINAL SURFACE VIEW:

24
CHAPTER- 5:

5.1 DISCUSSION OF THE RESULT AND CONCLUSION:

This fuzzy logic based relay for the differential protection of power transformer is made to operate at a flexible range of current parameters making the use of fuzzy logic membership functions. The relay is tuned and the results are verified at various operating parameters.
The relay generates a tripping signal to the circuit breaker when the fault current values exceed the operating range with this algorithm.

5.2 SCOPE FOR FUTURE WORK:

1. This algorithm can be applied for other types of protection scheme.

2. Membership functions can be formed using other types of waveforms also.

3. Hardware implementation of this algorithm is feasible.

4. Can be applied for embedded technologies.

25
REFERENCES:

* Fuzzy Logic-Based Relaying for Large Power Transformer Protection by Myong-Chul Shin,Member,IEEE, Chul-Won Park, and Jong-Hyung-kim. (IEEE Published Paper)

* Article on Improved power transformer protection using numerical relays by Bogdan Kasztenny* and Mladen Kezunovic Texas A&M University, USA.

* Article on Internal Fault Classification in Transformer Windings using Combination of Discrete Wavelet Transforms and Back-propagation Neural Networks by Atthapol Ngaopitakkul and Anantawat Kunakorn. * IEEE Published Paper Tuned Fuzzy Controller Based Over Current Protection Scheme by V.K.Chandna, Member, IEEE, P. Kumar, Member, IEEE, Mini S. Thomas, Senior Member, IEEE, Rajveer Singh.

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