风电机组异常风速的识别和修正方法研究

Research on Identification and Correction Methods for Abnormal Wind Speed in Wind Turbines

有效的数据清洗手段可提高风电机组测风资料的质量,而风机数据质量对风资源评估、风功率发电有重要意义。本文提出了风功率区间识别风速、功率的异常值,再基于风机高相关片区修正风速的方法。资料选用2020—2022年内蒙古乌兰察布市北部某风电场的风机测风数据进行分析。结果表明:风功率区间修正后的风机数据完整率提高至90%以上,利用风机高相关片区,修正了部分异常风速。该方法提高了风电场风电机组测风风速的数据质量,实现了风速和功率互相校准,为风电场发电量预测、调控提供基础性支撑数据。

Effective data cleaning methods can improve the quality of wind turbine measurement data.The quality of wind turbine data plays a very important role in wind resource assessment,wind power accurate prediction,and performance diagnosis of wind turbines.There are many uncertainties in the data collection and monitoring systems of different wind turbines for fault diagnosis,which result in uneven quality of wind measurement data for wind turbines.This paper proposes a new method for identifying the probability interval of wind power.This method uses the characteristic changes between wind speed and power to clean and correct the effective data of wind turbine measurement data.It can effectively improve the utilisation rate of wind turbine data.This paper selects wind turbine data from a wind farm in the northern part of Ulanqab,Inner Mongolia Autonomous Region from 2020 to 2022.By sequentially subjecting the data to rationality and validity tests,wind power interval checks,and finally,cleaning and correcting abnormal data,which are carried out by utilising the correlation of the turbine.The final results indicate that:by using the wind power interval method,it is difficult to distinguish abnormal wind speeds.This method can improve data quality and enhance the accuracy of wind speed and power.According to statistics,the data integrity has been significantly improved from 68.7%-92.5%to 90.1%-92.7%.Above all,the data integrity has been significantly improved.This method achieves mutual calibration between wind speed and power through the wind power probability interval recognition method.It provides fundamental support data for predicting and regulating the power generation of wind farms.It provides guidance and a basis for more refined meteorological service products for power and other related sectors.