以欧洲Lillgrund海上风电场为例,建立基于Larsen尾流模型及线性叠加模型的风电场输出功率及发电量计算模型;考虑风电机组偏航偏差等风向不确定性的影响,建立基于高斯平均方法的风电场计算功率修正模型;结合风电场实测数据及发电量计算收敛过程分析,研究了修正模型对风电场功率及发电量计算的影响.结果表明,所建立的尾流作用下的风电场功率计算模型能够较好地反应实际风电场的尾流影响特征,高斯平均修正方法进一步提高了尾流作用下风电场功率计算精度,并提高了发电量计算的收敛速度.在风电场年发电量计算中考虑风向不确定性的影响,对于提高模型评估与验证的准确性具有重要意义.%The Lillgrund offshore wind farm is taken as a toy example. Larsen wake model and linear wake summation method are adopted to establish wind farm power and AEP calculation models. Considering about the yaw misalignment of reference wind turbine, the post-processing model based on gaussian averaging (GA) is proposed for wind power correction. Based on the analysis of measured data and convergence process of AEP calculations, the effects of GA model on wind power and AEP calculations are discussed. Analysis shows, the established wind power calculation model can well reflect the wake characteristics in a real wind farm. Besides, GA corrections can not only improve the precision of the calculated wind farm output power, but also speed up the convergence of AEP calculation process. Taking wind direction uncertainty into consideration is an excellent way to improve the accuracy of wake model evaluations and validations.
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