文件名称:E0210101511
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The paper deals with the steady state analysis of
self-excited induction generator using Genetic Algorithm, Pattern
Search and Quasi-Newton optimization techniques. The
performance of an induction generator, maintaining a constant
terminal voltage is analyzed under resistive loads. Further the
paper deals with effects of various system parameters on the
steady state performance of an induction generator. Simulated
results obtained various optimization techniques are
compared graphically. The comparison of results, had lead to
their comparative importance.-The paper deals with the steady state analysis of
self-excited induction generator using Genetic Algorithm, Pattern
Search and Quasi-Newton optimization techniques. The
performance of an induction generator, maintaining a constant
terminal voltage is analyzed under resistive loads. Further the
paper deals with effects of various system parameters on the
steady state performance of an induction generator. Simulated
results obtained various optimization techniques are
compared graphically. The comparison of results, had lead to
their comparative importance.
self-excited induction generator using Genetic Algorithm, Pattern
Search and Quasi-Newton optimization techniques. The
performance of an induction generator, maintaining a constant
terminal voltage is analyzed under resistive loads. Further the
paper deals with effects of various system parameters on the
steady state performance of an induction generator. Simulated
results obtained various optimization techniques are
compared graphically. The comparison of results, had lead to
their comparative importance.-The paper deals with the steady state analysis of
self-excited induction generator using Genetic Algorithm, Pattern
Search and Quasi-Newton optimization techniques. The
performance of an induction generator, maintaining a constant
terminal voltage is analyzed under resistive loads. Further the
paper deals with effects of various system parameters on the
steady state performance of an induction generator. Simulated
results obtained various optimization techniques are
compared graphically. The comparison of results, had lead to
their comparative importance.
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E0210101511.pdf