Genetic algorithm–based calculation of the excitation capacitance of a self-excited induction generator for stable voltage operation over load and speed variations

被引：2

作者：

Tahir A. ^{[1
]}

Rajab Z. ^{[1
]}

Hammoda A. ^{[1
]}

Greibea S. ^{[1
]}

Alakeili L. ^{[1
]}

Elshaibani D. ^{[1
]}

Mohamed F. ^{[2
]}

机构：

[1] Department of Electrical and Electronics Engineering, University of Benghazi, Benghazi

[2] Authority of Natural Science Research and Technology, Tripoli

来源：

Wind Engineering | 2017年 / 41卷 / 06期

关键词：

Excitation capacitance; genetic algorithms; induction machines; optimization techniques; self-excited induction generator; wind power generation;

D O I：

10.1177/0309524X17721998

中图分类号：

学科分类号：

摘要：

In order to provide the reactive power demand of a self-excited induction generator which is required to achieve a voltage build-up, a three-phase capacitor bank is connected between the generator terminals. As loading increases, the operating point on the magnetizing curve moves toward the linear region which may lead to the collapse of the generated voltage. In this article, genetic algorithms are used to evaluate the value of the excitation capacitance that makes the machine operate in the saturation region which ensures a stable generated voltage. To verify the effectiveness of this method, a laboratory machine which has a relatively high stator and rotor resistances and leakage reactance is considered. The values of the excitation capacitances predicted by the genetic algorithms are applied to the machine Simulink-based model. The results obtained by the simulation are compared with experimental results which show a good agreement. © 2017, © The Author(s) 2017.

引用

页码：421 / 430

页数：9

共 18 条

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