...
首页> 外文期刊>Energy >New neural network and fuzzy logic controllers to monitor maximum power for wind energy conversion system
【24h】

New neural network and fuzzy logic controllers to monitor maximum power for wind energy conversion system

机译:新型神经网络和模糊逻辑控制器可监控风能转换系统的最大功率

获取原文
获取原文并翻译 | 示例
           

摘要

This work presents a new control strategy to ensure maximum power point tracking for a DFIG (doubly fed induction generator) based WECS (wind energy conversion system). The proposed strategy uses neural networks and fuzzy logic controllers to control the power transfer between the machine and the grid using the indirect vector control and reactive power control techniques. This transfer is ensured by controlling the rotor via two identical converters. The first converter is connected to the RSC (rotor side) and the second is connected to the GSC (grid side) via a filter. The DC (Direct Current) link voltage is controlled by a fuzzy controller. This control strategy is used to control the rotor side currents and to protect the generator by limiting the output current (or voltage). (C) 2016 Elsevier Ltd. All rights reserved.
机译:这项工作提出了一种新的控制策略,以确保基于DFIG(双馈感应发电机)的WECS(风能转换系统)的最大功率点跟踪。所提出的策略使用神经网络和模糊逻辑控制器,通过间接矢量控制和无功功率控制技术来控制机器与电网之间的功率传输。通过两个相同的变频器控制转子,可以确保这种传递。第一个转换器通过滤波器连接到RSC(转子侧),第二个转换器通过滤波器连接到GSC(电网侧)。直流(直流)链路电压由模糊控制器控制。该控制策略用于控制转子侧电流并通过限制输出电流(或电压)来保护发电机。 (C)2016 Elsevier Ltd.保留所有权利。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号