基于数据融合的风电变桨系统故障预警研究

随着风电机组装机容量的不断攀升,同时带来并网发电率低、机组故障率高等缺点,导致风电机组整体利用率较低。为此提出一种基于数据融合的风电变桨系统故障预警方法。首先结合SCADA系统中的运行统计信息和历史数据,采用Relief特征参数选择方法筛选出与风电变桨系统故障相关的特征参数;然后采用数据融合的方法,建立基于MSET技术的风电变桨系统故障预测模型,并采用滑动窗口法进行故障预警阈值的确定;最后以上海某风场1.5 MW双馈异步风电机组进行实例分析,结果表明该方法可提前发现风电变桨系统故障征兆,实现对风电变桨系统的早期故障预警。

RESEARCH ON FAULT WARNING OF WIND POWER PITCH SYSTEM BASED ON DATA FUSION

With the increasing installed capacity of wind turbines, the disadvantages of low grid-connected generation rate and high unit failure rate have resulted in low overall utilization rate of wind turbines. For this reason, this paper proposes a wind power pitch system early fault warning method based on data fusion. First, combined with the operating statistics and historical data in the SCADA system, the Relief characteristic parameter selection method is used to screen out the characteristic parameters related to the wind power pitch system failure; then the data fusion method is used to establish the wind power pitch system fault prediction model based on the MSET technology and the sliding window method is used to determine the fault warning threshold. Finally, a 1.5 MW doubly-fed asynchronous wind turbine in a wind farm in Shanghai is taken as an example. The results show that this method can detect the fault signs of the wind power pitch system in advance, and realize the early warning of the wind power pitch system failure.