Please use this identifier to cite or link to this item: http://hdl.handle.net/10266/686
Title: Steady State Analysis of Three-Phase Self-Excited Induction Generator
Authors: Mahley, Satnam
Chauhan, Yogesh Kumar (Guide)
Supervisor: Chauhan, Yogesh Kumar
Keywords: Induction Generator;Genetic Algorithm;SEIG;Steady State Analysis
Issue Date: 24-Sep-2008
Abstract: Use of an induction machine as a generator is becoming popular for the harnessing the renewable energy resources. Reactive power consumption and poor voltage regulation under varying load are the major drawbacks of the induction generator. The analysis of steady state performance is paramount as far as the running conditions of machine are concerned. To study the steady state aspects, we require methods by which the generator performance is predicted by using the induction motor data so that the effect of the basic parameters can be assessed. Having identified these it is essential to estimate correctly the magnetizing characteristics and related air-gap voltage under different flux conditions. Different methods are available to identify the steady state quiescent operating point under saturation for a given set of speed, load and excitation capacitor. These methods determine the saturated magnetizing reactance and per unit frequency. The operating air-gap flux can be then obtained by simulating zero rotor current conditions or a synchronous speed test. For its operation, the induction generator needs a reasonable amount of reactive power which must be fed externally to establish the magnetic field necessary to convert the mechanical power from its shaft into electrical energy. The NR method, a conventional method used for several decades to analyze the steady state performance of SEIG but it has some limitations. The genetic algorithm which is based on natural selection process and survival of fittest theory has several advantages over conventional method. The thesis work presents a steady state analysis of SEIG with a resistive and resistive–inductive load at various power factor using both NR and GA methods. Both simulated and experimental results are compared to examine the performance under various loading conditions. Both NR and GA simulated results are compared and performances with GA results are found to be slightly improving as compared to conventional NR method as far as the voltage regulation and loading is concern.
URI: http://hdl.handle.net/10266/686
Appears in Collections:Masters Theses@EIED

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