基于Makkonen结冰增长模型的风力机覆冰预报

Wind Turbine Ice Prediction Based on Makkonen Icing Growth Model

基于Makkonen结冰增长模型,优化相对风速计算方法,引入融冰影响因子,并进行气象因子敏感性测试,建立广西风力机覆冰预报模型。利用欧洲中期天气预报中心(European Centre for Medium-Range Weather Forecasts,ECMWF)模式预报资料和风力机参数驱动该模型,对2019年冬季桂北风电场进行逐日预报。预报结果表明:该模型对气温、降水、风速敏感,在适宜的风速下,温度越低,降水越大,覆冰厚度增长越快;48 h时效内对覆冰过程报出率为100%,覆冰起、止时间预报误差分别为3~5 h、6~12 h;72 h时效内覆冰起始时间预报效果稳定、准确率高,对冬季风电调度和防灾减灾有较好的指导意义。实际应用中,风力机停机时间应适当延迟,覆冰结束时间的预报则需进一步优化融冰条件。

On the basis of Makkonen icing growth model,this paper optimizes the calculation method for relative wind speed and introduces the de-icing influencing factors to carry out the test for sensitivity of meteorological factors and establish a icing forecast model for Guangxi wind turbines.By using the forecast data of European Centre for Medium-Range Weather Forecasts(ECMWF)and the parameters of the wind tubines,this model was driven to forecast icing of the northern Guangxi wind farms day by day in the winter of 2019.The results indicate the model is sensitive to the air temperature,rainfall and wind speed.In a suitable wind speed,the lower the temperature and the greater the rainfall,the faster the icing thickness increases.The forecast rate of icing process within 48 hours is 100%,and the forecast errors of the start and the end time are 3~5 h and 6~12 h respectively.The forecast accuracy of the starting time of icing within 72 hours is high and stable,which has good guiding significance to wind power dispacthing and disaster prevention of the wind farms in winter.In the practice,the time to shutdown the wind turbine should be postponed approriately and it needs to further optimize the de-icing conditions for forecasting icing end time.