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提出一种智能水滴(intelligent water drops,IWD)算法优化Elman神经网络的光伏电站输出功率预测模型。利用智能水滴算法对Elman神经网络的权值和阈值进行优化,可提高网络的训练效率。将IWD优化Elman神经网络模型、传统Elman神经网络模型和BP神经网络模型的预测结果分别与光伏电站的实际出力数据进行对比。结果表明,所提出的IWD-Elman神经网络模型具有较高的预测精度。
An intelligent water drops (IWD) algorithm is proposed to optimize the output power forecasting model of photovoltaic power plants based on Elman neural network. The use of intelligent water droplet algorithm to optimize the weights and thresholds of Elman neural network can improve the training efficiency of the network. The predicted results of IWD-optimized Elman neural network model, the traditional Elman neural network model and the BP neural network model are respectively compared with the actual output data of the photovoltaic power station. The results show that the proposed IWD-Elman neural network model has high prediction accuracy.