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Omar A. Helaly et al Int. Journal of Engineering Research and Applications www.ijera.com
ISSN : 2248-9622, Vol. 4, Issue 3( Version 1), March 2014, pp.560-565
www.ijera.com 560 | P a g e
A Reduced High Frequency Transformer Model To Detect The
Partial Discharge Locations
El-Sayed M. El-Refaie, El-Sayed H. Shehab El-Dein, M. K. Abd El-Rahman,
Omar A. Helaly
Helwan University, Egypt
ABSTRACT
Transformer modeling is the first step in improving partial discharge localization techniques. Different
transformer models were used for such purpose. This paper presents a reduced transformer model that can be
accurately used for the purpose of partial discharge localization. The model is investigated in alternative
transient program (ATP) draw for partial discharge localization application. A comparison between different
transformer models is studied, the achieved results of the reduced model demonstrated high efficiency.
Keywords – Reduced Model, Transformer, Partial Discharge Locations, ATP, EMTP.
I. INTRODUCTION
Partial discharge (PD) is considered as
internal fault so, its location recognition is very
important for treating the transformers. In the same
time, it is also considered as a transient action.
Therefore, low frequency transformer model isn’t
valid for such transient studies. To simulate PD
failure in transformers, appropriate model should be
used for such studies. Typically ideal transformer
doesn’t take into consideration the effect of mutual
inductance and the internal structure of the windings.
So high frequency detailed transformer model should
be used to enhance the accuracy of localization.
Different improvements were made to the
transformer modeling in fast transient studies but still
internal faults couldn’t be modeled properly. After
realizing the importance of building a high frequency
detailed transformer model, a lot of researches were
made in the past decades. Different transformer
models were developed for high frequency studies. A
brief literature for some of these models is given in
the next paragraphs.
1.1 HYBRID TRANSFORMER MODEL BASED ON
TRANSFORMER DESIGN DATA
A hybrid transformer model was verified in
ATP draw. The development in the model was
conducted from different points of view. Different
ATP transformer models such as XFRM is developed
and investigated in order to reproduce all kinds of
switching transients. This model consists of
inductance, resistance, capacitance, core area and
length. It is used in fast transient studies but the
transformer is considered as a compact block so that
it can’t be used in simulating internal studies [1].
1.2 IMPROVED HYBRID TRANSFORMER MODEL
Developments to the hybrid transformer
model were made. These developments included core
saturation and losses in the hybrid model. Core losses
were presented by consideration of flux density, core
section voltage and hysteresis core model that
enabled residual flux and self initialization. Also this
model is used in fast transient studies but the
transformer is considered as a compact block so it
can’t be used in simulating internal studies [2].
1.3 ELECTROMAGNETIC TRANSIENT PROGRAM
TRANSFORMER MODEL FOR OVER VOLTAGES
Time domain electromagnetic transient
program (EMTP) transformer model based on model
analysis was proposed [3]. This model was capable of
accurately accounting of the frequency dependent
effects of practical transformers with high
computational efficiency.
Another EMTP model was presented for
calculating over voltages in transformer windings
under very fast transient over voltages [4].
Despite that these two models are
implemented in EMTP program, there are some
drawbacks. The main disadvantage of EMTP
program is the simulation of internal transient studies
with different types of limitations such as the amount
of retrieved data.
1.4 LOW AND MID FREQUENCY TRANSFORMER
MODEL
A new hybrid transformer model for low
and mid frequency transient simulation was
presented. This model takes into consideration the
magnetic saturation of the core, frequency
RESEARCH ARTICLE OPEN ACCESS
Omar A. Helaly et al Int. Journal of Engineering Research and Applications www.ijera.com
ISSN : 2248-9622, Vol. 4, Issue 3( Version 1), March 2014, pp.560-565
www.ijera.com 561 | P a g e
dependency, capacitive coupling,
topologically correctness of core and coil structure.
Its application was mainly at low and mid frequency
behavior such as excitation, inrush, switching
transients and ferro resonance. This model isn’t used
in high frequency studies [5].
1.5 INTERNAL FAULT TRANSFORMER MODEL
This model was built as an accurate model
for simulation of internal faults in transformers [6].
The transformer model was developed in ATP draw.
It was based on two different sources of information,
test report data and design information. Test report
data includes short circuit impedance, total losses and
power value. Design information includes
inductance, resistance, capacitance, core area and
length. This kind of modeling is used for the partial
discharge recognition mission not for the protection
studies purpose.
1.6 TRANSFORMER MODEL INCLUDING PARTIAL
DISCHARGE MECHANISMS
Simulation of PD mechanism within a
transformer model was investigated by using some
software such as EMTP [7[. EMTP was used as a tool
to show PD mechanisms. The partial discharge
mechanism is discussed and simulated. The main
problem was the accurate modeling of PD in
localization studies [7].
1.7 HYBRID TRANSFORMER MODEL BASED ON
LUMPED PARAMETERS
A hybrid transformer model was introduced
to simulate the transformer winding transient process.
Calculations of the hybrid transient model parameters
were based on the lumped parameters of the
equivalent transformer model and electromagnetic
rules. Simulation was validated on an interleaved
winding 25 MVA, 66 kV. PD location can be
determined with maximum two discs error [8].
With this model, there is no need for
calculating the winding parameters as they are
already known and should be implemented directly in
the appropriate software.
1.8 DETAILED TRANSFORMER MODEL FOR THE
PURPOSE OF TRANSIENT STUDIES
High frequency transformer model was
presented for transient modeling. This technique was
applied on various winding types in power
transformer such as foil winding and double
layer winding. This model is implemented in
mathematical laboratory (MATLAB) and valid to
MHZ range [9].
High frequency transformer model was
developed using finite element method. The model is
established from construction information and the
approach implements frequency dependent
phenomena on a physical basis. Eddy current effects
are represented accurately even with a relatively
coarse mesh by using a frequency dependent complex
permeability representation for the core and
windings. The model can be employed in EMTP like
programs for a variety of applications, such as
analysis for internal and terminal stresses and
transformer network interaction [10]. This model is
used in this paper as a detailed transformer model.
1.9 REDUCED TRANSFORMER MODEL FOR THE
PURPOSE OF TRANSIENT STUDIES
Other models were presented in reduced
forms. It is sophisticate to use detailed transformer
model in EMTP/ATP draw due to its significant size.
A reduced transformer model was presented and
compared with IEEE model. The main idea of this
model is the elimination of non dominant Eigen
values of the system. This reduced model is
disadvantaged by the high divergence in the values of
the current wave response from the detailed model
values [11].
Also a reduced transformer model is
constructed for system studies from lumped
parameters models [12].
In this paper a new reduced transformer
model is presented for the purpose of partial
discharge localization transient studies. First,
detailed transformer model is simulated in ATP draw
and different PD pulses are injected. Second step is
reducing this model and capturing the current
responses of the transformer windings. Then these
current responses are compared with the current
response in the case of detailed transformer model in
the transient study. Also the efficiency of the reduced
model is demonstrated and compared with the
detailed model ones.
II. TRANSFORMER MODELING
Typically ATP Draw is used in fast
transient’s studies such as PD. The detailed model is
presented in ATP draw as shown in figure (1).
Omar A. Helaly et al Int. Journal of Engineering Research and Applications www.ijera.com
ISSN : 2248-9622, Vol. 4, Issue 3( Version 1), March 2014, pp.560-565
www.ijera.com 562 | P a g e
Fig.1. Detailed Transformer model in ATP Draw
Then the reduced model is formed from the
detailed model as shown in figure (2). This reduced
model neglects the effect of mutual inductance,
mutual capacitance, ground capacitance and core
resistance. But the main mutual inductance between
the primary and secondary sides of the transformer is
taken into consideration.
Fig.2. Reduced transformer modeled in ATP Draw
III. COMPARISON BETWEEN DETAILED
MODEL AND REDUCED MODEL
CURRENT RESPONSES
To validate the reduced transformer model,
comparison must be made. The current response is
chosen as a comparison criterion between the detailed
model and the reduced model. Different PD pulses
are injected in the detailed model and the reduced
model in the same location and the current response
is studied.
IV. CASE STUDY
TRANSFORMER SPECIFICATION
A cast resin dry transformer 10 MVA,
22/3.3 kV is used for testing. The high voltage (HV)
winding includes 6 discs and the low voltage (LV)
winding includes 32 layers. During the modeling
mission, the LV coil is considered as one part
because typically PD doesn’t occur in LV winding.
The detailed transformer is modeled in ATP draw as
shown in figure (1). The reduced transformer is
modeled in ATP draw as shown in figure (2).
V. RESULTS DISCUSSION
A PD pulse of 2 amperes peak value is
injected in the second disc of both models and the
current responses are compared. The current response
of the detailed transformer model is shown in figure
(3). The magnified current response of the detailed
model is shown in figure (4) and the current response
of the reduced model is shown in figure (5).
Fig.3. Current response of the detailed transformer
model
Omar A. Helaly et al Int. Journal of Engineering Research and Applications www.ijera.com
ISSN : 2248-9622, Vol. 4, Issue 3( Version 1), March 2014, pp.560-565
www.ijera.com 563 | P a g e
Fig.4. Magnified current response of the detailed
transformer model
Fig.5. Current response of the reduced transformer
model
It is recognized from these two figures that
the current responses are very similar. Also we still
can extract various features from the current finger
print that are useful for the purpose of PD locations
detection.
VI. BACK PROPAGATION NEURAL
NETWORK ACCORDING TO
LEVENBERG MARQUARDT ALGORITHM
Different features are extracted from these
waveforms. The extracted features are used for the
purpose of neural network training. The
differentiating feature extracted in the case of
detailed transformer model and in the case of reduced
transformer model has the same value. The neural
network training module used in this paper is back
propagation neural network according to Levenberg
Marquardt algorithm as shown in figure (6).
Typically the efficiency of this type of neural
network is evaluated by the mean square error and
regression between the network output values and the
required target.
Fig.6. Neural network training module
VII. PD LOCATIONS DETECTION
EFFICIENCY IN THE REDUCED
TRANSFORMER MODEL
The neural network reaches 24 iterations and
the mean square error becomes minimum and the
training function stops as shown in figure (7).
Fig.7. Neural network performance evaluation
Omar A. Helaly et al Int. Journal of Engineering Research and Applications www.ijera.com
ISSN : 2248-9622, Vol. 4, Issue 3( Version 1), March 2014, pp.560-565
www.ijera.com 564 | P a g e
The mean square error and the regression
between the network input and network output in the
case of training and validating and testing processes
are illustrated in next table.
Table 1 Training, validation and testing values
Mean Square
Error
Regression
Training 0.453 91.9%
Validation 2.79 78.2%
Testing 0.446 94%
The fitting function of the neural network
process is shown in figure (8).
Fig.8. Neural network fitting function
The regression of the network in case of
training, validating, testing and the integrated
processes is shown in figures (9, 10, 11 and 12)
respectively. In these figures T was referred to the
target output and Y for the calculated output.
Fig.9. Regression of training process
Fig.10. Regression of validating process
Fig.11. Regression of testing process
Fig.12. Regression of integrated processes
Omar A. Helaly et al Int. Journal of Engineering Research and Applications www.ijera.com
ISSN : 2248-9622, Vol. 4, Issue 3( Version 1), March 2014, pp.560-565
www.ijera.com 565 | P a g e
VIII. CONCLUSION
Different models can be used for
transformer studies. Each model has its limitation for
some applications. For partial discharge application,
high frequency model must be used. Detailed
transformer model requires a lot effort and time for
simulation within ATP. This paper presented a
reduced model which can be used for the purpose of
partial discharge application. The reduced model is
proved to be very efficient for this purpose.
In order to facilitate the search approach reduced
transformer models are used and the impact of this
reduction on the neural network performance is
analyzed. Reduced transformer model can be used
with the same accuracy of the detailed transformer
model.
REFERENCES
[1] Hans K. Hoidalen, Bruce A. Mork,
Francisco Gonzalez, Dmitry Ishchenko and
Nicola Chiesa, “Implementation and
verification of the hybrid transformer model
in ATP draw”, International Conference on
Power Systems Transients”, Lyon, France,
4-7 June 2007.
[2] H. K. Hoidalen, N. Chiesa, A. Arendano and
B. A. Mork, “Developments in the hybrid
transformer model core modeling and
optimization”, International Conference on
Power Systems Transients, Delft, The
Netherlands, 14-17 June 2011.
[3] D. J. Wilcox and D. J. Leonard, “A new
transformer EMTP transformer model based
on modal analysis”, International
Conference on Power Systems Transients,
Lisbon, Portugal, 3-7 September 1995.
[4] G. Liang, H. Dong, X. Wang, X. Zhanf, H.
Sun and X. Cui, “High frequency EMTP
model of transformer windings”,
International Zurich Symposium on
Electromagnetic Compatibility, Singapore,
2006, pp. 662-665.
[5] Bruce A. Mork, F. Gonzalez, D. Ishchenko,
D. L. Stuehm and J. Mitra, “Hybrid
transformer model for transient simulation
part 1: development and parameters”, IEEE
transactions on Power Delivery, Volume 22,
No. 1, January 2007.
[6] Arendano, B. A. Mork and H. K. Hoidalen,
“Transformer internal fault modeling in
ATP”, International Conference on Power
Systems Transients, Delft, the Netherland,
14-17 June 2011.
[7] Mehdi Nafar, “Simulation of partial
discharge mechanism using EMTP”,
International Conference on Innovations in
Electrical and Electronics Engineering,
Dubai, UAE, 6-7 October 2012.
[8] Mohammad S. Naderi, M. Vakilian, T. R.
Black Burn, B.T. Phung and Mehdi S.
Naderi, “A hybrid transformer model for
determination of partial discharge location
in transformer winding”, IEEE Dielectric
and Electrical Insulation, Volume 14, Issue
2, 2007, pp.436-443.
[9] K. Pedersen, M. E. Lunow, J. Holbeoll and
M. Henriksen, “Detailed high frequency
models of various winding types in power
transformers”, International Conference on
Power Systems Transients, Montreal,
Canada, 19-23 June 2005.
[10] E. Bjerkan, H. K. Høidalen, “High
Frequency FEM-based Power Transformer
Modeling: Investigation of Internal Stresses
due to Network Initiated Overvoltages”,
International Conference on Power Systems
Transients, Montreal, Canada, June 19-23,
2005.
[11] M.H. Nazemi, A. R. Allami, G. B.
Gharehpetian and M. Shafiee, “A new
approach for derivation of reduced order
model from transformer detailed model”,
18th International Power System
Conference, 20-22 October 2003, Iran.
[12] R.C. Degeneff, P.J. Mc Kenny and M.
Gutierrez, “A Method for Constructing
Reduced Order Transformer Models for
System Studies from Detailed Lumped
Parameter Models”, IEEE Trans. On Power
Delivery, 7(2), April 1992, pp 649-655.

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Cu4301560565

  • 1. Omar A. Helaly et al Int. Journal of Engineering Research and Applications www.ijera.com ISSN : 2248-9622, Vol. 4, Issue 3( Version 1), March 2014, pp.560-565 www.ijera.com 560 | P a g e A Reduced High Frequency Transformer Model To Detect The Partial Discharge Locations El-Sayed M. El-Refaie, El-Sayed H. Shehab El-Dein, M. K. Abd El-Rahman, Omar A. Helaly Helwan University, Egypt ABSTRACT Transformer modeling is the first step in improving partial discharge localization techniques. Different transformer models were used for such purpose. This paper presents a reduced transformer model that can be accurately used for the purpose of partial discharge localization. The model is investigated in alternative transient program (ATP) draw for partial discharge localization application. A comparison between different transformer models is studied, the achieved results of the reduced model demonstrated high efficiency. Keywords – Reduced Model, Transformer, Partial Discharge Locations, ATP, EMTP. I. INTRODUCTION Partial discharge (PD) is considered as internal fault so, its location recognition is very important for treating the transformers. In the same time, it is also considered as a transient action. Therefore, low frequency transformer model isn’t valid for such transient studies. To simulate PD failure in transformers, appropriate model should be used for such studies. Typically ideal transformer doesn’t take into consideration the effect of mutual inductance and the internal structure of the windings. So high frequency detailed transformer model should be used to enhance the accuracy of localization. Different improvements were made to the transformer modeling in fast transient studies but still internal faults couldn’t be modeled properly. After realizing the importance of building a high frequency detailed transformer model, a lot of researches were made in the past decades. Different transformer models were developed for high frequency studies. A brief literature for some of these models is given in the next paragraphs. 1.1 HYBRID TRANSFORMER MODEL BASED ON TRANSFORMER DESIGN DATA A hybrid transformer model was verified in ATP draw. The development in the model was conducted from different points of view. Different ATP transformer models such as XFRM is developed and investigated in order to reproduce all kinds of switching transients. This model consists of inductance, resistance, capacitance, core area and length. It is used in fast transient studies but the transformer is considered as a compact block so that it can’t be used in simulating internal studies [1]. 1.2 IMPROVED HYBRID TRANSFORMER MODEL Developments to the hybrid transformer model were made. These developments included core saturation and losses in the hybrid model. Core losses were presented by consideration of flux density, core section voltage and hysteresis core model that enabled residual flux and self initialization. Also this model is used in fast transient studies but the transformer is considered as a compact block so it can’t be used in simulating internal studies [2]. 1.3 ELECTROMAGNETIC TRANSIENT PROGRAM TRANSFORMER MODEL FOR OVER VOLTAGES Time domain electromagnetic transient program (EMTP) transformer model based on model analysis was proposed [3]. This model was capable of accurately accounting of the frequency dependent effects of practical transformers with high computational efficiency. Another EMTP model was presented for calculating over voltages in transformer windings under very fast transient over voltages [4]. Despite that these two models are implemented in EMTP program, there are some drawbacks. The main disadvantage of EMTP program is the simulation of internal transient studies with different types of limitations such as the amount of retrieved data. 1.4 LOW AND MID FREQUENCY TRANSFORMER MODEL A new hybrid transformer model for low and mid frequency transient simulation was presented. This model takes into consideration the magnetic saturation of the core, frequency RESEARCH ARTICLE OPEN ACCESS
  • 2. Omar A. Helaly et al Int. Journal of Engineering Research and Applications www.ijera.com ISSN : 2248-9622, Vol. 4, Issue 3( Version 1), March 2014, pp.560-565 www.ijera.com 561 | P a g e dependency, capacitive coupling, topologically correctness of core and coil structure. Its application was mainly at low and mid frequency behavior such as excitation, inrush, switching transients and ferro resonance. This model isn’t used in high frequency studies [5]. 1.5 INTERNAL FAULT TRANSFORMER MODEL This model was built as an accurate model for simulation of internal faults in transformers [6]. The transformer model was developed in ATP draw. It was based on two different sources of information, test report data and design information. Test report data includes short circuit impedance, total losses and power value. Design information includes inductance, resistance, capacitance, core area and length. This kind of modeling is used for the partial discharge recognition mission not for the protection studies purpose. 1.6 TRANSFORMER MODEL INCLUDING PARTIAL DISCHARGE MECHANISMS Simulation of PD mechanism within a transformer model was investigated by using some software such as EMTP [7[. EMTP was used as a tool to show PD mechanisms. The partial discharge mechanism is discussed and simulated. The main problem was the accurate modeling of PD in localization studies [7]. 1.7 HYBRID TRANSFORMER MODEL BASED ON LUMPED PARAMETERS A hybrid transformer model was introduced to simulate the transformer winding transient process. Calculations of the hybrid transient model parameters were based on the lumped parameters of the equivalent transformer model and electromagnetic rules. Simulation was validated on an interleaved winding 25 MVA, 66 kV. PD location can be determined with maximum two discs error [8]. With this model, there is no need for calculating the winding parameters as they are already known and should be implemented directly in the appropriate software. 1.8 DETAILED TRANSFORMER MODEL FOR THE PURPOSE OF TRANSIENT STUDIES High frequency transformer model was presented for transient modeling. This technique was applied on various winding types in power transformer such as foil winding and double layer winding. This model is implemented in mathematical laboratory (MATLAB) and valid to MHZ range [9]. High frequency transformer model was developed using finite element method. The model is established from construction information and the approach implements frequency dependent phenomena on a physical basis. Eddy current effects are represented accurately even with a relatively coarse mesh by using a frequency dependent complex permeability representation for the core and windings. The model can be employed in EMTP like programs for a variety of applications, such as analysis for internal and terminal stresses and transformer network interaction [10]. This model is used in this paper as a detailed transformer model. 1.9 REDUCED TRANSFORMER MODEL FOR THE PURPOSE OF TRANSIENT STUDIES Other models were presented in reduced forms. It is sophisticate to use detailed transformer model in EMTP/ATP draw due to its significant size. A reduced transformer model was presented and compared with IEEE model. The main idea of this model is the elimination of non dominant Eigen values of the system. This reduced model is disadvantaged by the high divergence in the values of the current wave response from the detailed model values [11]. Also a reduced transformer model is constructed for system studies from lumped parameters models [12]. In this paper a new reduced transformer model is presented for the purpose of partial discharge localization transient studies. First, detailed transformer model is simulated in ATP draw and different PD pulses are injected. Second step is reducing this model and capturing the current responses of the transformer windings. Then these current responses are compared with the current response in the case of detailed transformer model in the transient study. Also the efficiency of the reduced model is demonstrated and compared with the detailed model ones. II. TRANSFORMER MODELING Typically ATP Draw is used in fast transient’s studies such as PD. The detailed model is presented in ATP draw as shown in figure (1).
  • 3. Omar A. Helaly et al Int. Journal of Engineering Research and Applications www.ijera.com ISSN : 2248-9622, Vol. 4, Issue 3( Version 1), March 2014, pp.560-565 www.ijera.com 562 | P a g e Fig.1. Detailed Transformer model in ATP Draw Then the reduced model is formed from the detailed model as shown in figure (2). This reduced model neglects the effect of mutual inductance, mutual capacitance, ground capacitance and core resistance. But the main mutual inductance between the primary and secondary sides of the transformer is taken into consideration. Fig.2. Reduced transformer modeled in ATP Draw III. COMPARISON BETWEEN DETAILED MODEL AND REDUCED MODEL CURRENT RESPONSES To validate the reduced transformer model, comparison must be made. The current response is chosen as a comparison criterion between the detailed model and the reduced model. Different PD pulses are injected in the detailed model and the reduced model in the same location and the current response is studied. IV. CASE STUDY TRANSFORMER SPECIFICATION A cast resin dry transformer 10 MVA, 22/3.3 kV is used for testing. The high voltage (HV) winding includes 6 discs and the low voltage (LV) winding includes 32 layers. During the modeling mission, the LV coil is considered as one part because typically PD doesn’t occur in LV winding. The detailed transformer is modeled in ATP draw as shown in figure (1). The reduced transformer is modeled in ATP draw as shown in figure (2). V. RESULTS DISCUSSION A PD pulse of 2 amperes peak value is injected in the second disc of both models and the current responses are compared. The current response of the detailed transformer model is shown in figure (3). The magnified current response of the detailed model is shown in figure (4) and the current response of the reduced model is shown in figure (5). Fig.3. Current response of the detailed transformer model
  • 4. Omar A. Helaly et al Int. Journal of Engineering Research and Applications www.ijera.com ISSN : 2248-9622, Vol. 4, Issue 3( Version 1), March 2014, pp.560-565 www.ijera.com 563 | P a g e Fig.4. Magnified current response of the detailed transformer model Fig.5. Current response of the reduced transformer model It is recognized from these two figures that the current responses are very similar. Also we still can extract various features from the current finger print that are useful for the purpose of PD locations detection. VI. BACK PROPAGATION NEURAL NETWORK ACCORDING TO LEVENBERG MARQUARDT ALGORITHM Different features are extracted from these waveforms. The extracted features are used for the purpose of neural network training. The differentiating feature extracted in the case of detailed transformer model and in the case of reduced transformer model has the same value. The neural network training module used in this paper is back propagation neural network according to Levenberg Marquardt algorithm as shown in figure (6). Typically the efficiency of this type of neural network is evaluated by the mean square error and regression between the network output values and the required target. Fig.6. Neural network training module VII. PD LOCATIONS DETECTION EFFICIENCY IN THE REDUCED TRANSFORMER MODEL The neural network reaches 24 iterations and the mean square error becomes minimum and the training function stops as shown in figure (7). Fig.7. Neural network performance evaluation
  • 5. Omar A. Helaly et al Int. Journal of Engineering Research and Applications www.ijera.com ISSN : 2248-9622, Vol. 4, Issue 3( Version 1), March 2014, pp.560-565 www.ijera.com 564 | P a g e The mean square error and the regression between the network input and network output in the case of training and validating and testing processes are illustrated in next table. Table 1 Training, validation and testing values Mean Square Error Regression Training 0.453 91.9% Validation 2.79 78.2% Testing 0.446 94% The fitting function of the neural network process is shown in figure (8). Fig.8. Neural network fitting function The regression of the network in case of training, validating, testing and the integrated processes is shown in figures (9, 10, 11 and 12) respectively. In these figures T was referred to the target output and Y for the calculated output. Fig.9. Regression of training process Fig.10. Regression of validating process Fig.11. Regression of testing process Fig.12. Regression of integrated processes
  • 6. Omar A. Helaly et al Int. Journal of Engineering Research and Applications www.ijera.com ISSN : 2248-9622, Vol. 4, Issue 3( Version 1), March 2014, pp.560-565 www.ijera.com 565 | P a g e VIII. CONCLUSION Different models can be used for transformer studies. Each model has its limitation for some applications. For partial discharge application, high frequency model must be used. Detailed transformer model requires a lot effort and time for simulation within ATP. This paper presented a reduced model which can be used for the purpose of partial discharge application. The reduced model is proved to be very efficient for this purpose. In order to facilitate the search approach reduced transformer models are used and the impact of this reduction on the neural network performance is analyzed. Reduced transformer model can be used with the same accuracy of the detailed transformer model. REFERENCES [1] Hans K. Hoidalen, Bruce A. Mork, Francisco Gonzalez, Dmitry Ishchenko and Nicola Chiesa, “Implementation and verification of the hybrid transformer model in ATP draw”, International Conference on Power Systems Transients”, Lyon, France, 4-7 June 2007. [2] H. K. Hoidalen, N. Chiesa, A. Arendano and B. A. Mork, “Developments in the hybrid transformer model core modeling and optimization”, International Conference on Power Systems Transients, Delft, The Netherlands, 14-17 June 2011. [3] D. J. Wilcox and D. J. Leonard, “A new transformer EMTP transformer model based on modal analysis”, International Conference on Power Systems Transients, Lisbon, Portugal, 3-7 September 1995. [4] G. Liang, H. Dong, X. Wang, X. Zhanf, H. Sun and X. Cui, “High frequency EMTP model of transformer windings”, International Zurich Symposium on Electromagnetic Compatibility, Singapore, 2006, pp. 662-665. [5] Bruce A. Mork, F. Gonzalez, D. Ishchenko, D. L. Stuehm and J. Mitra, “Hybrid transformer model for transient simulation part 1: development and parameters”, IEEE transactions on Power Delivery, Volume 22, No. 1, January 2007. [6] Arendano, B. A. Mork and H. K. Hoidalen, “Transformer internal fault modeling in ATP”, International Conference on Power Systems Transients, Delft, the Netherland, 14-17 June 2011. [7] Mehdi Nafar, “Simulation of partial discharge mechanism using EMTP”, International Conference on Innovations in Electrical and Electronics Engineering, Dubai, UAE, 6-7 October 2012. [8] Mohammad S. Naderi, M. Vakilian, T. R. Black Burn, B.T. Phung and Mehdi S. Naderi, “A hybrid transformer model for determination of partial discharge location in transformer winding”, IEEE Dielectric and Electrical Insulation, Volume 14, Issue 2, 2007, pp.436-443. [9] K. Pedersen, M. E. Lunow, J. Holbeoll and M. Henriksen, “Detailed high frequency models of various winding types in power transformers”, International Conference on Power Systems Transients, Montreal, Canada, 19-23 June 2005. [10] E. Bjerkan, H. K. Høidalen, “High Frequency FEM-based Power Transformer Modeling: Investigation of Internal Stresses due to Network Initiated Overvoltages”, International Conference on Power Systems Transients, Montreal, Canada, June 19-23, 2005. [11] M.H. Nazemi, A. R. Allami, G. B. Gharehpetian and M. Shafiee, “A new approach for derivation of reduced order model from transformer detailed model”, 18th International Power System Conference, 20-22 October 2003, Iran. [12] R.C. Degeneff, P.J. Mc Kenny and M. Gutierrez, “A Method for Constructing Reduced Order Transformer Models for System Studies from Detailed Lumped Parameter Models”, IEEE Trans. On Power Delivery, 7(2), April 1992, pp 649-655.