Research Article

Optimal Design of Power Transformer with Advance Core Material using ANSYS Technique

Shabana Urooj
Princess Nourah Bint Abdulrahman University, Saudi Arabia
Tanya Singh
Gautam Buddha University, India
Mohammad Amir
Madan Mohan Malaviya University of Technology, India
* Corresponding author
Mohd Tariq
Aligarh Muslim University, India
DOI icon 10.24018/ejece.2020.4.5.249

Read Counter
1492

Downloads
857

Citations

Share

Article Sidebar

Submitted 2020-09-28
Published 2020-10-30

Read counter = 1492 times

Table of Contents

Article Main Content

Due to indulge behavior of core materials and losses that leads to degradation of transformer efficiency. This research paper evaluating the optimal performance of transformer with designing of a newly core material namely as Mo.Me6. A possibility of increment in the efficiency for designed proposed model of transformer is observable. Also, a comparative analytical study based on the different designs of core type transformer with various core materials. The design and evaluation are performed on the Maxwell ANSYS electronic desktop platform, which provides an optimized design of transformer for practical applications. Whether it is a power transformer having lower frequency applications use in electronic circuits such as rectifying circuits or higher frequency applications power distribution circuit, etc. All transformer designs require performance evaluation in the working field and better efficiency to optimize the overall three-phase type core transformer. In this paper, proposed Mo.Me6 material with improved physical properties have been present of transformer efficiency and optimal design of core. The criteria include the changes in some effective parameters of the core, bringing out advancement in the working efficiency of the transformer. There is an opportunity to have a choice of desired material as designed particularly for the customer need making it will be more reliable and more suitable for various changeable conditions. For more efficient and effective working of transformer, this paper suggests core design with ANSYS techniques to achieve mentioned high efficiency with lower losses.

Keywords: ANSYS (Analysis System), Mo.Me6 (Modified Material of Conductivity 106 Sie/m), Power Transformer.

References

  1. H. D. Mehta, R.M.P.: ?A Review on Transformer Design Optimization and Performance Analysis Using Artificial Intelligence Techniques,? Int. J. Sci. Res., 2014.
     Google Scholar
  2. Patel, A., Bapodariya, N., Panchal, H., Smart, N., Bhatt, K.: ?3-Phase Core Type of Transformer and Modification of Symmetrical Star Shaped Core,? International Journal of Advance Engineering and Research Design 324?331, 2017.
     Google Scholar
  3. AC and DC machine, Vol-II, B. L THAREJA, Accessed on October,7 https://www.amieindia.in/downloads/ebooks/electrical2-theraja.pdf (Access on August 2020)
     Google Scholar
  4. Dhonge, D.D., Swami, P.S., Thosar, A.G.: ?Developing Artificial Neural Network ANN Model for Fault Diagnosis of Power Transformer,? International Journal of Scientific and Engineering Research, 1127?1132, 2015.
     Google Scholar
  5. Tripathy, M., Maheshwari, R.P., Verma, H.K.: ?Power transformer differential protection based on optimal probabilistic neural network,? IEEE Trans. Power Deliv. 25, 102?112, 2010.
     Google Scholar
  6. Hsieh, M.F., Hsu, C.H., Fu, C.M., Huang, Y.M.: ?Design of Transformer With High-Permeability Ferromagnetic Core and Strengthened Windings for Short-Circuit Condition,? IEEE Trans. Magn. 51, 2?5, 2015.
     Google Scholar
  7. Suttisinthong, N., Pothisarn, C.: Analysis of Electrical Losses in Transformers using Artificial Neural Networks. II, 12?15, 2014.
     Google Scholar
  8. Anoop, S., Naufal, N.: Monitoring of winding temperature in power transformers - A study. 2017 Int. Conf. Intell. Comput. Instrum. Control Technol. ICICICT, 1334?1337, 2018.
     Google Scholar
  9. Kittan, S., Kornhuber, S., Kastel, P., Nitsche, G., Valtin, G., Weise, M.: ?Review and Implementation of Transformer Health Index Methods in line with the Development of a Condition Assessment Tool,? Int. Conf. Diagnostics Electr. Eng. Diagnostika 2018.
     Google Scholar
  10. Ismagilov, F.R., Vavilov, V.E., Gusakov, D. V.: ?High-Efficiency Transformer-Rectifier Unit: Design and Experimental Studies,? 2019 26th Int. Work. Electr. Drives Improv. Effic. Electr. Drives- IWED - Proc. 1?4, 2019.
     Google Scholar
  11. J. Survilo, "Transformer design according to criteria and load profile", ((IEEE 58th RTUCON), Riga, 2017.
     Google Scholar
  12. Stergiou, C.A., Zaspalis, V.: ?Cobalt-Induced Performance Instabilities of Mn?Zn Ferrite Cores,? IEEE Trans. Magn. 54, 1?8, 2018.
     Google Scholar
  13. Litovets, A. V., Serikov, A. V., Serikov, V.A.: ?Energy efficiency increasing for the power transformer by means of the liquid heating unit.? Int. Conf. Ind. Eng. Appl. Manuf. ICIEAM 2017 - Proc. 1?4, 2017.
     Google Scholar
  14. Suppitaksakul, C., Saelee, V.: ?Application of Artificial Neural Networks for electrical losses estimation in three-phase transformer,? 6th Int. Conf. Electr. Eng. Comput. Telecommun. Inf. Technol. ECTI-CON 2009. 1, 248?251, 2009.
     Google Scholar
  15. Nnachi, G.U., Akumu, A.O., Richards, C.G., Nicolae, D. V.: ?Estimation of no-Load Losses in Distribution Transformer Design Finite Element Analysis Techniques in Transformer Design,? IEEE PES/IAS Power Africa, Power Africa 2018. 527, 527?531, 2018.
     Google Scholar
  16. ANSYS_electronic_software_2020TM_version:https://www.ansys.com/en-in/products/electronics (2020).
     Google Scholar
  17. Isa, M.M., Kadir, M.Z.A.A., Gomes, C., Azis, N., Izadi, M., Alyozbaky, O.S.H.: ?Analysis on magnetic flux density and core loss for hexagonal and butt-lap core joint transformers?? IEEE 2nd Annu. South. Power Electron. Conf. SPEC 2016.
     Google Scholar
  18. W. Sun, L. Yang, J. Hao and F. Zare, "3D Electric Field Simulation of Converter Transformer with Real Insulation Materials Utilized in HVDC Systems," IEEE International Conference on High Voltage Engineering and Application (ICHVE), ATHENS, Greece, pp. 1-4, 2018.
     Google Scholar
  19. Wang, Z., Wu, W.: ?Effect of higher insulation material thermal conductivity on transformer temperature rise,? 34th Electr. Insul. Conf. EIC 2016. 358?361, 2016.
     Google Scholar
  20. Digalovski, M., Najdenkoski, K., Rafajlovski, G.: ?Impact of current high order harmonic to core losses of three-phase distribution transformer,? IEEE EuroCon 2013. 1531?1535, 2013.
     Google Scholar
  21. De Le?n, F., Purushothaman, S., Qaseer, L.: ?Leakage inductance design of toroidal transformers by sector winding,? IEEE Trans. Power Electron. 29, 473?480, 2014.
     Google Scholar
  22. Saad, M., Tenyenhuis, E.: ?On-line gas monitoring for increased transformer protection,? IEEE Electr. Power Energy Conf. EPEC Oct 1?4, 2018.
     Google Scholar
  23. Semiconductor materials standard available online on: https://me-mechanicalengineering.com/comparison-between-conductors-semiconductors-and-insulators (2019).
     Google Scholar
  24. Silva, D.C.L., Sousa, R.H., Lima, F.K.A., Branco, C.G.C.: ?Study of energy efficiency in dry-type transformer under sub- and inter harmonic in the power supply voltage,? In: 2015 IEEE 13th Brazilian Power Electronics Conference and 1st Southern Power Electronics Conference (COBEP/SPEC). pp. 1?6. IEEE (2015).
     Google Scholar
  25. Rahimpour, H., Mitchell, S., Tusek, J.: ?The application of sweep frequency response analysis for the online monitoring of power transformers,? Proc. 2016 Australas. Univ. Power Eng. Conf. AUPEC 2016.
     Google Scholar
  26. Fu Yang, Zhang liang: ?Comprehensive method detecting the status of the transformer based on the artificial intelligence,? 200090, 1638?1643, 2005.
     Google Scholar
  27. Zhang, H., Wang, S., Yuan, D., Tao, X.: ?Double-Ladder Circuit Model of Transformer Winding for Frequency Response Analysis Considering Frequency-Dependent Losses,? IEEE Trans. Magn. 51, 1?4, 2015.
     Google Scholar
  28. Yang, Q.P., Li, M.Q., Mu, X.Y., Wang, J.: ?Application of artificial intelligence (AI) in power transformer fault diagnosis?. 2009 Int. Conf. Artif. Intell. Comput. Intell. AICI 2009. 4, 442?445, 2009.
     Google Scholar
  29. H. A. Illias, K. C. Chan and H. Mokhlis, "Hybrid feature selection?artificial intelligence?gravitational search algorithm technique for automated transformer fault determination based on dissolved gas analysis," in IET Generation, Transmission & Distribution, vol. 14, no. 8, pp. 1575-1582, 24 4, 2020.
     Google Scholar
  30. M. Amir and S. K. Srivastava, "Analysis of MPPT Based Grid Connected Hybrid Renewable Energy System with Battery Backup," 2018 International Conference on Computing, Power and Communication Technologies (GUCON), Greater Noida, Uttar Pradesh, India, 2018, pp. 903-907, doi: 10.1109/GUCON.2018.8674902.
     Google Scholar
  31. M. Amir and Zaheeruddin, "ANN Based Approach for the Estimation and Enhancement of Power Transfer Capability," 2019 International Conference on Power Electronics, Control and Automation (ICPECA), New Delhi, India, 2019, pp. 1-6, doi: 10.1109/ICPECA47973.2019.8975665.
     Google Scholar
  32. X. Zhao et al., "Experimental Evaluation of Transformer Internal Fault Detection Based on V?I Characteristics," in IEEE Transactions on Industrial Electronics, vol. 67, no. 5, pp. 4108-4119, May 2020.
     Google Scholar
  33. L. Zhou, J. Jiang, X. Zhou, Z. Wu, T. Lin and D. Wang, "Detection of transformer winding faults using FRA and image features," in IET Electric Power Applications, vol. 14, no. 6, pp. 972-980, 2020.
     Google Scholar
  34. Amir M., Srivastava S.K. (2019) Analysis of Harmonic Distortion in PV?Wind-Battery Based Hybrid Renewable Energy System for Microgrid Development. In: Mishra S., Sood Y., Tomar A. (eds) Applications of Computing, Automation and Wireless Systems in Electrical Engineering. Lecture Notes in Electrical Engineering, vol 553. Springer, Singapore. https://doi.org/10.1007/978-981-13-6772-4_107.
     Google Scholar