Temperature Analysis in Power Transformer Windings Using Created Artificial Bee Algorithm and Computer Program


Creative Commons License

Zile M.

IEEE Access, cilt.7, ss.60513-60521, 2019 (SCI-Expanded) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 7
  • Basım Tarihi: 2019
  • Doi Numarası: 10.1109/access.2019.2915343
  • Dergi Adı: IEEE Access
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.60513-60521
  • Anahtar Kelimeler: Animal behavior, bee algorithm, power transformers, temperature analysis, transformers
  • Gazi Üniversitesi Adresli: Hayır

Özet

© 2013 IEEE.The transformers used in certain stages of electricity production and distribution are the most important element due to their high costs and long service life. The most important parameter that reduces the useful life of the transformers is the high-temperature level which causes the fastening of the insulation material. The complexity of the temperature analysis in the power transformer windings makes it necessary to use an optimal resolution algorithm. It has been preferred to develop an artificial bee algorithm to solve complex temperature optimization problems in power transformer windings realistically and quickly. In this paper, the power transformer detection panel has been developed. The data required for the algorithm have been obtained by performing experiments in different power transformers. A microcontroller-based data acquisition circuit has been created to monitor the operating conditions of the power transformers. Variables such as the temperature of the environment and the temperature of the transformer have been transferred to the computer by sampling. The analysis of winding temperatures of power transformers has been determined by using the developed Artificial Bee Algorithm and computer program. The generated algorithm has been coded using the C # programming language. The temperature analysis of the power transformer windings has been created using the Microsoft SQL Server 2017 database. The data obtained from experimental studies have been compared with the data obtained from the developed algorithm and computer program. Using the computer program based on this algorithm, the loss, and temperature data of the transformer have been accurately estimated according to the variable states of the load and its harmonic content.