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Estimation of Permanent Magnet Synchronous Generator Performance with Artificial Neural Network Models

Authors: Çetin, Onursal; Dalcalı, Adem; Temurtaş, Feyzullah; Dalcalı, Adem;

Estimation of Permanent Magnet Synchronous Generator Performance with Artificial Neural Network Models

Abstract

The interest in renewable energy sources has grown with the increase of environmental pollution and the decrease of fossil fuels. It is possible to provide energy supply security and diversity by using renewable energy sources. In this regard, wind energy, which is one of the renewable energy sources whose share in energy production increases day by day, emerges as a local and environmentally friendly solution. Many different types of generators are used in wind turbines and these have advantages and disadvantages according to each other. Permanent magnet synchronous generators (PMSG) are preferred because of their advantages such as high efficiency, high power density and being used directly in wind turbines without the need for gear system. In this study, the performance of the 2,5 kW PMSG, with a 14-pole surface placement, internal rotor, suitable for use in wind turbines, has been examined by changing the physical structure of the magnet. For this purpose, performance parameters such as total magnet consumption, efficiency, power loss have been successfully estimated using single and double hidden layered multi layer neural network (MLNN), elman neural network (ENN) and radial basis function neural network (RBFNN).

Çevre kirliliğinin artması ve fosil yakıtların azalması ile yenilenebilir enerji kaynaklarına ilgi artmıştır. Yenilenebilir enerji kaynaklarını kullanarak enerji arz güvenliğini ve çeşitliliğini sağlamak mümkündür. Bu bağlamda, enerji üretiminde payı her geçen gün artan yenilenebilir enerji kaynaklarından biri olan rüzgâr enerjisi, yerel ve çevre dostu bir çözüm olarak ortaya çıkmaktadır. Rüzgâr türbinlerinde birçok farklı tipte jeneratör kullanılmaktadır ve bunlar birbirlerine göre avantaj ve dezavantajlara sahiptir. Sabit mıknatıslı senkron generatörler (SMSG) yüksek verim, yüksek güç yoğunluğu ve dişli sistemine gerek olmadan direkt olarak rüzgâr türbinlerinde kullanılma gibi avantajlarından dolayı tercih edilmektedirler. Bu çalışmada, rüzgâr türbinlerinde kullanıma uygun 14-kutuplu yüzey yerleştirmeli, içten rotorlu, 2,5 kW SMSG’nin performansı mıknatısın fiziksel yapısı değiştirilerek incelenmiştir. Bu amaçla toplam kullanılan mıknatıs miktarı, verim, güç kaybı gibi performans parametreleri tek ve iki gizli katmana sahip çok katmanlı sinir ağı (MLNN), elman sinir ağı (ENN) ve radyal tabanlı fonksiyon sinir ağı (RBFNN) kullanılarak başarılı bir şekilde kestirilmiştir.

Country
Turkey
Related Organizations
Keywords

multilayer neural network, Permanent magnet synchronous generator

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
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