Optimization algorithms for steady state analysis of self excited induction generator

Ibrahim Athamnah, Yaser Anagreh, Aysha Anagreh

Abstract


The current publication is directed to evaluate the steady state performance of three-phase self-excited induction generator (SEIG) utilizing particle swarm optimization (PSO), grey wolf optimization (GWO), wale optimization algorithm (WOA), genetic algorithm (GA), and three MATLAB optimization functions (fminimax, fmincon, fminunc). The behavior of the output voltage and frequency under a vast range of variation in the load, rotational speed and excitation capacitance is examined for each optimizer. A comparison made shows that the most accurate results are obtained with GA followed by GWO. Consequently, GA optimizer can be categorized as the best choice to analyze the generator under various conditions.

Keywords


genetic algorithm; grey wolf optimization; MATLAB optimizers; particle swarm optimization; whale optimization algorithm

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DOI: http://doi.org/10.11591/ijece.v13i6.pp6047-6057

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International Journal of Electrical and Computer Engineering (IJECE)
p-ISSN 2088-8708, e-ISSN 2722-2578

This journal is published by the Institute of Advanced Engineering and Science (IAES) in collaboration with Intelektual Pustaka Media Utama (IPMU).