Study of Optimal Excitation of Self-Excited Induction Generators by Genetic Algorithm - Archive ouverte HAL Accéder directement au contenu
Article Dans Une Revue International Journal for Scientific Research & Development Année : 2017

Study of Optimal Excitation of Self-Excited Induction Generators by Genetic Algorithm

Résumé

It has been well established that, Induction Generator (SEIG) is one of the most effective device for generating wind energy followed by wind turbine due to some added advantage of asynchronous properties, rugged design and brush less operation. Wind power is found to be most suitable for small rural areas, where abundant quantity of wind is available. Mathematically it is found that excitation of SEIG is the function of load, motor speed, output frequency and magnetizing reactance. The magnetising reactance can be found out experimentally. In this paper an attempt has been made to focus the optimal value of excitation required for different machines under the variation of the three functional variables within a certain range and keeping the output voltage above a certain level. The main objective of this paper is to study how output voltage and frequency with optimal excitation of the capacitor bank (under variation of the above three variables) vary with the machine ratings. Genetic Algorithm is applied for global search to find the optimal point of excitation of the different machines.
Fichier non déposé

Dates et versions

hal-01639173 , version 1 (20-11-2017)

Identifiants

  • HAL Id : hal-01639173 , version 1

Citer

Raju Basak, Hamed Yahoui, Nicolas Siauve. Study of Optimal Excitation of Self-Excited Induction Generators by Genetic Algorithm. International Journal for Scientific Research & Development , 2017, 4 (12), IJSRDV4I120533 p. 590-593. ⟨hal-01639173⟩
200 Consultations
0 Téléchargements

Partager

Gmail Facebook X LinkedIn More