Optimized Modeling of Transformer in Transient State with Genetic Algorithm | Zendy

Mehdi Bigdeli | Zendy; Ebrahim Rahimpour | Zendy

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Optimized Modeling of Transformer in Transient State with Genetic Algorithm

Author(s) -

Mehdi Bigdeli,

Ebrahim Rahimpour

Publication year - 2012

Publication title -

international journal of energy and engineering

Language(s) - English

Resource type - Journals

eISSN - 2163-1905

pISSN - 2163-1891

DOI - 10.5923/j.ijee.20120203.08

Subject(s) - transformer , matlab , admittance parameters , engineering , electrical impedance , transient (computer programming) , time domain , algorithm , electronic engineering , linear variable differential transformer , genetic algorithm , transient state , voltage , computer science , distribution transformer , electrical engineering , machine learning , computer vision , operating system

In this paper a straightforward model is proposed for transient analysis of transformers. The model is capable of representing the impedance or admittance characteristics of the transformer measured from the terminals under different terminal connections up to approximately 200 kHz. The model is simple, so that the simulation with this model is easy and fast. It is feasible to use the model as a two port element by network analysing. To estimation of model parameters genetic algorithm is used. Outset of all, the required measurements are carried out on the 2500 KVA, 6300/420 V transformer. Thereafter, the model parameters are estimated using genetic algorithm toolbox in MATLAB. The comparison between calculated and measured quantities confirms that the accuracy of the proposed method in the middle transient frequency domain is satisfactory. Finally, one of important application of proposed model in transformers fault detection is discussed.

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