Determination of the optimal capacitance for the capacitor excited induction generator using the hybrid genetic algorithm

In this thesis, a standalone capacitor-excited induction generator used for low power wind plants under varying load conditions is studied from various aspects.Firstly, renewable energy sources are introduced and the significance of the wind power is explained among those energy sources. Besides, development of wind energy and its potential in Turkey and the world for possible utilization is addressed.Secondly, the capacitor-excited induction generator and its application to wind power systems are examined and ongoing investigations are reported. In addition, examples of some typical applications are given by a literature survey up till now.Thirdly, theoretical background of wind energy, construction of wind turbines and its types, production of maximum power from a typical wind turbine and fundamentals of asynchronous machines are stated in the relevant section respectively. Subsequently, the equivalent circuit of the induction generator and the requirement of a capacitor for the self-excited induction generator and its operation are explained in detail. Furthermore, minimum and maximum capacitances for the induction generator are reported and the significance of the excitation range under various load conditions is pointed out.Finally, steady-state analysis of the induction generator, the experimental setup to determine a relationship between the air-gap voltage and the magnetising reactance and the computational algorithm based on the genetic algorithms and the Newton-Raphson method for finding relevant parameters are denoted.