基于风资源电算系统计算的风资源评估参数数据

用于风电场开发前期评估风电场运行期内20/25年风能资源参数水平。基于分16象限相关的方法与再分析数据、周边测风塔同期数据分别相关，完成测风塔数据插补，进一步计算风电场轮毂高度处代表年测风参数，为风能资源评估报告提供数据基础。收集测风塔10min原始数据（含风速SD值），经时矩转化（风速算术平均，风向矢量平均）转化为1h数据并结合数据过程线，完成数据筛洗。基于MERRA2、ERA5再分析数据以及周边测风塔同期有效数据（筛洗后数据），采用分16象限相关方法完成测风塔数据插补得到测风塔测风年平均风速、风功率密度，计算测风年风速威布尔分布c、k值。根据再分析数据分析测风塔代表年，将测风年订正为对风电场运行20/25年具有长期代表性的代表年数据序列。根据测风塔同朝向高度同期有效数据，拟合垂直方向风切变指数；采用测风塔垂直切变指数推算风电场轮毂高度处风速。计算轮毂高度处代表年风速分布的威布尔分布c、k值，以及统计风速、风向、风能分布。基于10min有效数据统计测风塔平均湍流强度以及70%分位数下湍流强度。计算轮毂高度空气密度值，完成测风数据整编。This dataset is employed for the pre-development assessment of wind energy resource parameters throughout the 20/25-year operational lifespan of a wind farm. First, the 16-quadrant correlation method is applied to correlate reanalysis data with contemporaneous data from nearby wind measurement towers, completing the imputation of wind mast data, and further calculating representative annual wind measurement parameters at the hub height of the wind farm to provide a data foundation for wind energy resource assessment reports. Raw 10-minute data from the wind measurement tower (including the standard deviation of wind speed) is collected, then converted into 1-hour data via temporal aggregation (arithmetic mean for wind speed and vector mean for wind direction) combined with data time series profiles to complete data quality control. Based on MERRA2 and ERA5 reanalysis data as well as contemporaneous valid post-screening data from nearby wind measurement towers, the 16-quadrant correlation method is used to perform wind mast data imputation, obtaining the annual average wind speed and wind power density for the measurement year, and calculating the c and k parameters of the wind speed Weibull distribution in the measurement year. The representative year for the wind measurement tower is determined via reanalysis data, and the measurement year is corrected into a representative annual data sequence with long-term representativeness for the 20/25-year operational period of the wind farm. Based on contemporaneous valid data at the same orientation and height of the wind measurement tower, the vertical wind shear exponent is fitted, and the fitted vertical wind shear exponent is used to extrapolate the wind speed at the hub height of the wind farm. The c and k parameters of the Weibull distribution for the representative annual wind speed distribution at the hub height are calculated, along with statistical analyses of wind speed, wind direction, and wind energy distributions. Based on valid 10-minute data, the average turbulence intensity and the turbulence intensity at the 70th percentile of the wind measurement tower are quantified. Finally, the air density at the hub height is calculated, completing the compilation of the wind measurement dataset.