Comprehensive Evaluation Of Wind Turbine Operating State Based On Improved Cloud Model

In order to improve the ecological environment and alleviate the shortage of conventional energy supply,more countries are turning to wind energy as a pollution-free energy source.It is particularly important to develop wind power generation technology according to local conditions in China where fuel is insufficient and transportation is inconvenient.However,wind power generation is located in a harsh environment,expensive equipment and difficult maintenance.Under the traditional wind power generation mode,maintenance is carried out after the fan has a problem,which greatly increases the operation and maintenance costs and causes inevitable economic losses.Evaluate the state of the wind turbine in advance,and carry out timely targeted maintenance before irreparable damage to the wind turbine equipment,which not only improves the stability,economy and safety of wind turbine equipment,but also conforms to the current maintenance of wind turbine equipment in wind power generation.Development direction.Therefore,this paper focuses on the comprehensive evaluation of wind turbine operating state.Based on the SCADA operating data of wind turbines,before building the model,select the wind speed-power data that has the most direct influence on the operating efficiency for analysis,and use the combination of the quadrant method and the DBSCAN density clustering method to identify and eliminate abnormal data in sections.Due to the uncertainty in the prediction process of wind turbines,the cloud model is improved on the basis of 3εn criterion,the forward cloud generator algorithm is selected to reflect the digital characteristics of its normal distribution,reduce the influence of human,and get a more accurate cloud model.The dynamic degradation degree is used to replace the traditional degradation degree to express the relationship between the status of the Wind generator set in the actual work and the fault situation,and the combination weighting index weight determination model is adopted,and the weight of each index is comprehensively measured,It directly reflects the objective characteristics of the measured indicators and the interrelationship between the various indicators more accurately.In order to reflect the health of the wind turbine,process the date in advance,reduce the impact of abnormal data,and evaluate the overall running state of the wind turbine.The results show that the improved cloud model can reflect the deterioration of wind turbines in advance,leaving time for the operation and maintenance of wind turbines.