Abstract
The advancement of new technologies has brought many changes in traditional electric power systems, especially in the terms of the new monitoring systems, real time load flow calculations and advanced computer simulations and analysis of electric power systems. For each of these applications, the knowledge of the accurate system components parameters are crucial. However, the parameters of system components are not easily accessible, especially when it comes to transformers parameters. Since it is generally required to disconnect the transformer from the power system in order to measure and calculate the parameters, the transformer off-line time needs to be reduced as much as possible. This paper proposes a method for automated data acquisition based transformer parameters calculation, which reduces the transformer off-line time, and improves power quality. Results conducted on a real power transformer demonstrated that the developed hardware and user interface software are easy to use, with fast and accurate calculation. This paper makes a contribution to the existing body of knowledge by developing and testing an automated method for transformer parameters calculation, whose application represents an improvement when compared to the traditional process of calculating the transformer parameters.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Jadhav, V., Lokhande, S.S., Gohokar, V.N.: Monitoring of transformer parameters using Internet of Things in smart grid. In: International Conference on Computing Communication Control and automation (ICCUBEA), Pune (2016)
Hubana, T., Šarić, M., Avdaković, S.: Approach for identification and classification of HIFs in medium voltage distribution networks. IET Gener. Transm. Distrib. 12(5), 1145–1152 (2018)
Šemić, E., Šarić, M., Hubana, T.: Influence of solar PVDG on electrical energy losses in low voltage distribution network. In: Hadžikadić, M., Avdaković, S. (eds.) Advanced Technologies, Systems, and Applications II, IAT 2017. LNNS, vol 28. Springer, Cham (2018)
Hubana, T., Begić, E., Šarić, M.: Voltage sag propagation caused by faults in medium voltage distribution network. In: Hadžikadić, M., Avdaković, S. (eds.) Advanced Technologies, Systems, and Applications II, IAT 2017. LNNS, vol 28. Springer, Cham (2018)
Mossad, M.I., Azab, M., Abu-Siada, A.: Transformer parameters estimation from nameplate data using evolutionary programming techniques. IEEE Trans. Power Deliv. 29(5), 2118–2123 (2014)
Thilagar, S.H., Rao, G.S.: Parameter estimation of three-winding transformers using genetic algorithm. Eng. Appl. Artif. Intell. 15(5), 429–437 (2002)
Zjang, Y., Zhang, H., Mou, Q., Li, C., Wang, L., Zhang, B.: An improved method of transformer parameter identification based on measurement data. In: 5th International Conference on Electric Utility Deregulation and Restructuring and Power Technologies (DRPT), Changsha (2015)
Zhang, Z., Kang, N., Mousavi, M.J.: Real-time transformer parameter estimation using terminal measurements. In: IEEE Power & Energy Society General Meeting, Denver, 2015 (2015)
Bhowmic, D., Manna, M., Chowdhury, S.K.: Estimation of equivalent circuit parameters of transformer and induction motor from load data. IEEE Trans. Ind. Appl. PP(99), 1 (2018)
Staroszczyk, Z.: Problems with in-service (on-line) power transformer parameters determination - case study. In: 17th International Conference on Harmonics and Quality of Power (ICHQP), Belo Horizonte (2016)
Mašić, Š.: Električni strojevi. Elektrotehniĉki fakultet, Sarajevu (2006)
Mitraković, B.: Ispitivanje električnih mašina. Naučna knjiga, Belgrade (1991)
Velleman: Velleman (2018). https://www.velleman.eu/products/view/?id=351346. Accessed 11 Feb 2018
Measurement Computing: miniLAB 1008 USB-based Analog and Digital I/O Module - Users GUIDE. Measurement Computing Corporation, Norton (2006)
Texas Instruments: LM317 3-Terminal Adjustable Regulator, Dallas (2016)
Microsoft: Visual Studio 6.0 (2018). https://msdn.microsoft.com/en-us/library/ms950418.aspx. Accessed 13 Feb 2018
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this paper
Cite this paper
Begic, E., Hubana, T. (2019). Automated Data Acquisition Based Transformer Parameters Estimation. In: Avdaković, S. (eds) Advanced Technologies, Systems, and Applications III. IAT 2018. Lecture Notes in Networks and Systems, vol 60. Springer, Cham. https://doi.org/10.1007/978-3-030-02577-9_38
Download citation
DOI: https://doi.org/10.1007/978-3-030-02577-9_38
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-02576-2
Online ISBN: 978-3-030-02577-9
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)