风电机组中主传动设备运行状态精准监测仿真

Accurate Monitoring and Simulation of Operation Status of Main Transmission Equipment in Wind Turbine

风电机组中主传动设备出现故障或性能下降会直接影响风力发电机组的运行效率和发电能力。为了可以及时发现设备的异常状态或潜在故障,避免影响整个风电场的运行,对风电机组主传动设备运行状态进行监测。采用K-最近邻算法与局部离群因子检测相互结合的方式进行风电机组主传动设备运行工况划分。根据划分结果,使用层次分析法计算各个层次元素对应的相对重要性次序的权重,由此得到运行状态指标,并利用核密度估计技术设定状态指标阈值,通过阈值判断,实现风电机组主传动设备运行状态监测。仿真结果表明,所提方法应用后,风电机组主传动设备运行工况划分准确率为99.95%,G值接近100%,且监测到的风电机组主传动设备健康度与实际健康度拟合度较高。说明所提方法可以精准反映风电机组主传动设备运行状态,具有良好的监测性能。

The failure or performance degradation of the main transmission equipment in the wind turbine will di-rectly affect the operating efficiency and power generation capacity of the wind turbine.In order to find out the abnor-mal state or potential fault of the equipment in time and avoid affecting the operation of the whole wind farm,the oper-ation state of the main drive equipment of the wind turbine is monitored.The combination of the K-nearest neighbor algorithm and local outlier detection is used to divide the operation conditions of the main transmission equipment of wind turbines.According to the division results,the analytic hierarchy process is used to calculate the weight of the relative importance order corresponding to the elements at each level,so as to obtain the operation status indicators.The kernel density estimation technology is used to set the threshold value of the status indicators,and through the threshold judgment,the operation status monitoring of the main transmission equipment of the wind turbine is realized.The simulation results show that after the application of the proposed method,the accuracy of the operation condition division of the main drive equipment of the wind turbine is 99.95%,the G value is close to 100%,and the fitness be-tween the monitored health of the main drive equipment of the wind turbine and the actual health is high.It shows that the proposed method can accurately reflect the operation status of the main transmission equipment of wind turbine,and has good monitoring performance.