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Optimization of a small passive wind turbine generator with multiobjective genetic algorithms

机译:多目标遗传算法优化小型被动风力发电机

摘要

In this paper Multiobjective Genetic Algorithms (MOGAs) are used for the design of a small wind turbine generator (WTG) coupled to a DC bus through a diode bridge. The originality of the considered system resides in the suppression of the Maximum Power Point Tracker (MPPT). The poor efficiency of the corresponding passive structure is considerably improved by optimizing the generator characteristics associated with the wind turbine in relation to the wind cycle. The optimized configurations are capable of matching very closely the behavior of active wind turbine systems which operate at optimal wind powers by using a MPPT control device.
机译:在本文中,多目标遗传算法(MOGA)用于设计通过二极管电桥耦合到DC总线的小型风力发电机(WTG)。所考虑系统的独创性在于对最大功率点跟踪器(MPPT)的抑制。通过相对于风循环优化与风力涡轮机相关联的发电机特性,相当大地改善了相应的无源结构的不良效率。优化的配置能够非常紧密地匹配使用MPPT控制设备以最佳风力运行的有源风力涡轮机系统的性能。

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