CAJ | 학술논문

采用概率分布拟合和基于遗传算法的 BP 神经网络的预测建模对风电功率波动特性进行定量分析。首先，针对风电功率实测数据建立了概率分布拟合模型并分析了拟合结果；其次，建立了基于不同时间间隔历史实测数据的BP神经网络预测模型，数据检验表明该模型对于峰值有很理想的预测精度且整体精度较高。
채용개솔분포의합화기우유전산법적 BP 신경망락적예측건모대풍전공솔파동특성진행정량분석。수선，침대풍전공솔실측수거건립료개솔분포의합모형병분석료의합결과；기차，건립료기우불동시간간격역사실측수거적BP신경망락예측모형，수거검험표명해모형대우봉치유흔이상적예측정도차정체정도교고。
The fluctuation of wind power is analyzed by probability distribution fitting and forecasting model of BP neural networkbased to quantitative. Firstly, the distribution fitting probability model is established according to the measured data of wind power;secondly, BP neural network prediction model for different time intervals of history data is established;the existing data test show that the model for the peak has a very good prediction and the overall prediction accuracy is higher. The obtained results have certain guiding significance to create balance mechanism of wind power effectively.