1. Presenter: Muhammad Hamza
Roll No.: MS-F-19-008
Course: Power System Transients
Authors: Daniel Barbosa, Ulisses Chemin Netto, Denis V.
Coury & Mário Oleskovicz
Power Transformer Differential Protection
Based
on Clarke’s Transform and Fuzzy Systems
HEAVY INDUSTRY TAXILA EDUCATION CITY (HITEC)
Department of Electrical Engineering
3. Introduction (Abstract)
The power transformer is a piece of electrical equipment that
needs continuous monitoring and fast protection since it is very
expensive and an essential element for a power system to perform
effectively.
The most common protection technique used is the percentage
differential logic, which provides discrimination between an
internal fault and different operating conditions.
Unfortunately, there are some operating conditions of power
transformers that can affect the protection behavior and the power
system stability.
This paper proposes the development of a new algorithm to
improve the differential protection performance by using fuzzy
logic and Clarke’s transform.
4. Introduction (Continued)
The most common protection technique is the percentage
differential logic, which provides discrimination between an
internal fault and an external fault or a normal operating condition.
Differential relays compare the currents from all terminals of the
protected transformer to a predetermined threshold. in the case of
an internal fault, the equipment is disconnected from the power
supply.
Some condition can cause differential currents Like, presence of
magnetizing inrush currents due to energization, over-excitation,
and sympathetic inrush etc.
In order to prevent the relay disoperation in these cases, it is
necessary to differentiate inrush current from fault current.
5. Introduction (Continued)
In order to improve power transformer protection, various methods
were developed for accurate and efficient discrimination of the
situations.
This paper has discussed and implemented the fuzzy logic method
to separate or segregate of the obtained current readings.
The main concept of this particular fuzzy logic implementation is
to gain the current reading using Clark's transformation and
segregate those values in to either of the internal, external or
normal condition category.
6. METHODOLOGY
Figure: 1 is a typical differential relay connection diagram for the
protection of power transformers.
The connection of current transformers (CTs), coupled with the primary
and secondary branches, Np : Ns are shown. is the turn ratio between the
primary and secondary windings of the transformer.
1 : n1 and 1 : n1 are the turn ratios between the branches and CTs,
selected to make Np.n1 : Ns.n2 .
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 respective configuration of transformer primary and secondary coil
are Delta and Star. So, CT’s configuration will be Star and Delta.
8. METHODOLOGY
The proposed algorithm was implemented in the C++ programming
language and it is illustrated in Fig. 2. It uses the standard common format
for transient data exchange (COMTRADE) for power systems in order to
acquire the current signals from a transformer.
After acquiring the data, the signals are processed using Clarke’s
transform and the differential currents are calculated.
These currents are the input of the fuzzy system. If the output of the fuzzy
system is greater than the threshold value of 0.5, the control counter (ctr_
k) is increased by 1.
When this counter has exceeded the threshold 3, the relay sends a trip
signal to the CB. It is important to emphasize that the proposed fuzzy
system computes each differential α-β-γ component independently.
10. METHODOLOGY
Design of fuzzy system
Fuzzification: The fuzzy system applied to the proposed relay uses three
fuzzy inputs: 1) Δα ; 2) Δβ ;and 3) Δγ . These variables are obtained from
Clark’s transform equations. Figs. 3(a)–(c) show the membership
functions of the inputs and the output fuzzy set. For fuzzification of a
defined input variable Δα, a range is set between 0 and 100 and the
membership values range from 0 to 1. The other input variables Δβ and
Δγ are in the range from 0 to 50. The output variable is shown in Fig. 3(d)
ranging from 0 to 1 for two membership functions that determine block or
trip signals. After acquiring the data, the signals are processed using
Clarke’s transform and the differential currents are calculated.
Inference Method: The proposed relay uses 18 rules to discriminate two
operating conditions: steady state or internal faults. For this paper, in
order to perform a mathematical operation, the Mamdani inference
method was chosen. Fig. 4 shows the rules used in the proposed
algorithm.
12. METHODOLOGY
Design of fuzzy system
Defuzzification: The method needed a crisp value for control purposes.
The technique applied a centroid in accordance with:
After defuzzification, the output is compared with threshold value if it
is equal or greater then it then this will initiate the tripping protocol.
15. Result & Discussions
The main purpose of this section is to present some results
regarding the proposed algorithm and comparing them to a
commercial relay.
Various different tests were simulated for distinct operating
conditions of the power transformer in the system.
These simulations were converted into COMTRADE file format
and the files were stored in a database having 690 cases of interest,
including internal faults on both sides of the power transformer,
sympathetic inrush, energization, overexcitation, energization
under fault, and interturn faults.
This database was used to test and validate the proposed algorithm.
However, for brevity, only the 90 most relevant cases were used for
comparison with the commercial relay.
16. Result & Discussions
Fig. (5) shows the three-phase current waveforms in the windings
on both sides of the transformer, the digital channels of the
commercial relay, and the fuzzy output of the proposed algorithm for
energization under fault at 10% of the secondary (wye) winding
from phase A in the TR2E Transformer at 0.349s.
In the figure, a delay in the trip signal by the commercial relay can
be observed, when compared to the proposed algorithm.
The commercial relay took around 235ms to operated while this new
proposed system gave output at 10ms.Which make this system
faster then the current commercial relay protection mechanism.
The analysis of this condition is fundamental to test the algorithm’s
robustness facing practical field situations, taking into account that
the harmonic blocking increases the trip time of the commercial
relay.
17. Result & Discussions
Fig. 6 shows the signals in the case of an internal fault at 0.350 s.
The fault is located within 5% from the neutral of the wye winding
at the high-voltage side of phase A in the TR2E transformer.
Its current waveforms were shown in Fig. 6(a). The misoperation
of the commercial protective relay can be seen in Fig. 6(b) (i.e., the
device did not send the trip signal to the CB). This error could have
been caused by the low differential current observed.
STATISTICAL TESTS FOR THE PROPOSED ALGORITHM AND
THE COMMERCIAL RELAY
18. Result & Discussions
Fig. 5&6: Fault under energization and internal faults at 5% of secondary (P-A)
19. Conclusions
This paper presented a new method for digital protection of power
transformers using Clarke’s transform and fuzzy logic. This technique has
shown some advantages regarding the traditional ones.
The simulation results show that the average operating time for the
proposed technique is shorter than that of the commercial relay used, due
to the fact that this method doesn't use the harmonic components as the
basis of the relay decision.
Great stability of the proposed algorithm for all faults and operation
conditions can be observed, correctly discriminating each one.
The new algorithm improves the coverage of the wye-connected winding
to 95%. This value is greater than what is commonly found in commercial
protective relays. However, to protect the entire winding, it is still
necessary to use the restricted earth-fault protection scheme.
Another important advantage of the algorithm is its simplicity as well as its
computational efficiency, making it suitable for commercial applications.