遗传算法优化了风能转换系统中双定子感应发电机的PI和模糊逻辑速度矢量控制

F. Ameur, K. Kouzi
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引用次数: 11

摘要

本文对风电转换系统中双定子感应发电机(DSIG)的优化PI常规和PI模糊逻辑速度矢量控制进行了设计和分析。第一步提出了一种面向场的DSIG控制方法。在第二步,为了确保一个最佳工作点和一个最大功率点轨道(MPPT),在不同的风速下,在线提供最大的电力生产,使用传统PI和模糊PI速度调节器。在最后一步,为了改进这两个调节器的设计,采用了遗传算法技术,方便了设计参数的确定,相对于“试错法”减少了时间消耗。仿真结果表明了所提控制算法的有效性和性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Genetic algorithm optimized PI and fuzzy logic speed vector control of Dual Stator Induction Generator in wind energy conversion system
This paper focuses on the design and analysis of optimized PI conventional and PI fuzzy logic speed vector control of Dual Stator Induction Generator (DSIG) in wind energy conversion system. In first step a field-oriented control of a DSIG is presented. In second step, in order to ensure an optimum operating point and a Maximum Power Point Track (MPPT) giving online a maximum production of electric power for different wind speeds, a conventional PI and then a fuzzy PI speed regulators are used. In the final step, to improve the design of these two regulators, the technique of genetic algorithms is used to facilitate the design parameters determination and reduced time consumption comparatively to the “trial-error” method. Simulation results show clearly the effectiveness and the performance of the suggested control algorithm.
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