文章基本信息

标题：Study on the Low Voltage Ride-Through of Doubly-Fed Induction Generator Based on BP Neural Network
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作者：Gu Bo ; Zhang Lingyun ; Li Xiaodan 等
期刊名称：International Journal of Hybrid Information Technology
印刷版ISSN：1738-9968
出版年度：2015
卷号：8
期号：2
页码：179-190
DOI：10.14257/ijhit.2015.8.2.16
出版社：SERSC
摘要：In order to ensure that wind turbines could be online under the condition of power grid transient fault, the technology of low voltage ride-through (LVRT) for wind turbine has become a research focus of experts and scholars at home and abroad. In current wind turbine control strategy, the PI parameters of the control system keep unchanged when the wind turbine is in the process of LVRT, which affects the performance of the control system. Therefore, the adaptive PI parameter adjustment system based on BP neural network is proposed, which realize the adaptive adjustment of PI parameters in the process of LVRT. The simulation model of the LVRT process was built, the simulation results show that this control algorithm can effectively restrain the current oscillation caused by the voltage sag, shorten the fault recovery time of the system, and has a good dynamic performance. Besides, the adaptability and robustness of the system has been increased, which has improved the low voltage ride-through capability of the system.
关键词：doubly-fed induction generator (DFIG); LVRT; PI Control; BP Neural ; Network