基于SSA-GPR模型的风电机组运行状态监测OA

In order to improve the power generation efficiency and economic benefits of wind turbines,the online monitoring of the operating status of wind turbines is particularly important.A new method for monitoring the status of wind turbines based on sparrow search algorithm optimized Gaussian process(SSA-GPR)model is proposed.Firstly,the data collected from data collection and monitoring is preprocessed and analyzed.The correlation analysis is used to select the input of the model.A normal regression model using the parameters of the unit under normal operating conditions is established to calculate the reconstruction error in real-time.The unit status is determined by monitoring whether the predicted power residual exceeds the dynamic fault threshold in real-time.Through examples,it is shown that the proposed SSA-GPR model smaller prediction error and can achieve abnormal operation status warning of the unit 120 minutes in advance.