摘要
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。
The output power forecast model of PV plant based on Elman neural network optimized by intelligent water drop （IWD） algorithm was presented. The efficiency of network training could be improved by using IWD algorithm to optimize the weights and thresholds of Elman neural network. The prediction results of Elman neural network model optimized by IWD algorithm, traditional Elman neural network model and BP neural network model were compared with practical output power data of the PV plant, respectively. The results show that Elman neural network model optimized by IWD algorithm has higher forecast precision.
出处
《太阳能学报》
EI
CAS
CSCD
北大核心
2017年第6期1553-1559,共7页
Acta Energiae Solaris Sinica
基金
国家自然科学基金(51407076)
河北省自然科学基金(F2014502050)
