...
首页> 外文期刊>International journal of machine learning and cybernetics >Active power and reactive power dispatch of wind farm based on wavelet learning
【24h】

Active power and reactive power dispatch of wind farm based on wavelet learning

机译:基于小波学习的风电场有功,无功调度

获取原文
获取原文并翻译 | 示例

摘要

During normal operation, the doubly-fed induction generator (DFIG) generates certain range of reactive power. The DFIG based wind farm can participate in reactive power control of grid as a reactive power supply. In order to get a more stable input wind speed of the DFIG, wavelet multi-resolution analysis method is used. This paper proposes a kind of power dispatch model which considers a learning mechanism of minimum copper loss of all DFIGs in wind farm as an objective function. An active power and reactive power allocation optimization model is established. This power dispatch model makes the working condition of DFIGs and the PCC running in the optimum state. The active power and reactive power generated by wind farm satisfy the power gird requirements of both active power and reactive power. The advantage of the proposed method is verified by a case study which successfully demonstrates the learning mechanism.
机译:在正常运行期间,双馈感应发电机(DFIG)会生成一定范围的无功功率。基于DFIG的风电场可以作为无功电源参与电网的无功控制。为了使双馈发电机的输入风速更加稳定,采用了小波多分辨率分析方法。本文提出了一种电力调度模型,该模型以风电场中所有双馈双馈最小铜损的学习机制为目标函数。建立了有功功率和无功功率分配的优化模型。该功率分配模型使DFIG和PCC的工作状态处于最佳状态。风电场产生的有功功率和无功功率同时满足有功功率和无功功率的要求。通过案例研究验证了该方法的优势,该案例成功演示了学习机制。

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