ZASEY’E DAYALI HARMONİKLİ YÜK VE DENGESİZ BESLEME GERİLİMİ ALTINDA TRANSFORMATÖRÜN İNDİRGENMESİNİN KARŞILAŞTIRILMASI

Endüstri ve dağıtım merkezlerinde yaygın olarak kullanılan dağıtım trafoları, gerilimdengesizliğinden ve harmonik yüklerden en fazla etkilenen elektrik makinalarıdır. Bu durumlar dağıtımtrafoların verimini, nüve kaybı ve bakır kaybı gibi parametreleri üzerinde olumsuz etkisi vardır. Bumakalede, harmonikli yükler ve dengesiz besleme gerilimi koşulları altında Dağıtım Trafosununİndirgenmesi ve kayıplardaki artış incelenmiştir. Transformatörün indirgemesini gerçekleştirmek için kfaktörü ve harmonik kayıp faktörü (HFL) kullanılmıştır. Bu çalışmada dağıtım transformatörününsargılarında ve çekirdeğinde oluşan manyetik akı yoğunluğunu gözlemlemek için üç boyutlu zamanadımlı sonlu elemanlar yönteminden (ZASEY) faydalanılmıştır. Elde edilen sonuçlara göre IEEEstandardının yüksek harmonikli akım (THDI) ve dengesiz koşulları altında transformatörün indirgenmesiiçin yetersiz, ZASEY’nin ise daha uygun doğru bir yöntem olduğu görülmüştür.

Comparison of Derating in Transformerunder Non-Linear Load and Imbalanced Supply Voltage Based on Tsfem

Distribution transformers which are widely used in industry and distribution centers are the most affected by voltage imbalance and harmonic loads. These situations have a negative impact on efficiency , core loss and winding loss of distribution transformers, In this article, derating as well as losses increase of transformer under non-linear loads and imbalanced supply voltage conditions are examined . harmonic loss factor (HFL) and K-factor have been used to perform the transformer derating. In this study, 3D time-step finite element method(TSFEM) used to observe the magnetic flux density formed in the windings and core of the distribution transformer. According to the results obtained, it is seen that the IEEE standard is insufficient for the derating of the transformer under high harmonic current (THDI) and unbalanced conditions and Time Stepping Finite Element Method is a more suitable method.

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