Abstract
The degradation process of wind turbines is greatly affected by external factors. Wind turbine maintenance costs are high. The regular maintenance of wind turbines can easily lead to over and insufficient maintenance. To solve the above problems, a stochastic degradation model (SDE, stochastic differential equation) is proposed to simulate the change of the state of the wind turbine. First, the average degradation trend is obtained by analyzing the properties of the stochastic degradation model. Then the average degradation model is used to describe the predictive degradation model. Then analyze the change trend between the actual degradation state and the predicted state of the wind turbine. Secondly, according to the update process theory, the effect of maintenance on the state of wind turbines is comprehensively analyzed to obtain the availability. Then based on the average degradation process, the optimal maintenance period of the wind turbine is obtained. The optimal maintenance time of wind turbines is obtained by optimizing the maintenance cycle through availability constraints. Finally, an onshore wind turbine is used as an example to verification. Based on the historical fault data of wind turbines, the optimized maintenance decision is obtained by analyzing the reliability and maintenance cost of wind turbines under periodic and non-equal cycle conditions. The research results show that maintenance based on this model can effectively improve the performance of wind turbines and reduce maintenance costs.
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