Application of Artificial Neural Network for Analysis of Self-Excited Induction Generator

• Main Authors: Raja Singh Khela, Raj Kumar Bansal, K. S. Sandhu, Ashok Kumar Goel
• Format: Article
• Language: English
• Published: Postgraduate Office, School of Computer Science, Universidad Nacional de La Plata 2006-10-01
• Series: Journal of Computer Science and Technology
• Subjects: self-excited induction generator; artificial neural networks
• Online Access: https://journal.info.unlp.edu.ar/JCST/article/view/817

It is observed that conventional techniques to analyse the steady state analysis of Self-Excited Induction Generator (SEIG) involve cumbersome mathematical procedures. In this paper an Artificial Intelligence (AI) technique has been used to analyse the behaviour of Self-Excited Induction Generator, which does not require rigorous modelling as required in conventional techniques. Proposed Artificial Neural Network (ANN) model has been implemented to predict the effect of speed, capacitance and load on generated voltage and frequency of SEIG. Experimental data is used for the training of ANN. Results obtained from the trained ANN are found to be in close agreement with the experimental results.