【摘要】 针对现有模型预测准确性与稳定性较低的问题，提出一种以BiLSTM为基础的风电功率预测模型。BiLSTM可以很好的处理风电多变量之间的非线性关系，其次采用改进的PSO优化BiLSTM的超参数，并通过AM训练模型的权重。最后采用内蒙古自治区某风电场的历史数据进行提前0～15 min试验。结果表明，提出的IPSO-BiLSTM-AM模型具有较高的预测精度，可以为风电场电力调度与控制提供科学参考。更多还原

【Abstract】 In view of the low accuracy and stability of existing models,a wind power prediction model based on BiLSTM is proposed.BiLSTM can handle the non-linear relationship among wind power multi-variables well. Secondly,the improved PSO algorithm is used to optimize the hyper parameters of BiLSTM,and the AM is used for training the weight of the model. Finally,a 0～15 minute advance test is carried out with the historical data of a wind farm in Inner Mongolia Autonomous Region. The results show that the proposed IPSO-BiLSTM-AM model has high prediction accuracy,which can provide scientific reference for the power dispatch and control of wind farms.更多还原