| 基于长短期记忆神经网络的地表太阳辐照度预测 |
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| 引用本文： | 赵书强,尚煜东,杨燕燕,李永华.基于长短期记忆神经网络的地表太阳辐照度预测[J].太阳能学报,2021(3):383-388. |
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| 作者姓名： | 赵书强 尚煜东 杨燕燕 李永华 |
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| 作者单位： | 新能源电力系统国家重点实验室（华北电力大学） |
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| 基金项目： | 国家重点研发计划(2017YFB0902200);国家电网公司科技项目(5228001700CW)。 |
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| 摘 要： | 针对地表太阳辐照度(GHI)短期预测问题,提出一种基于长短期记忆神经网络的短期太阳辐照度预测模型。采用递归结构的训练样本,以保证训练样本内部的时间耦合性。为验证所提模型预测GHI的有效性,采用算例与传统人工神经网络模型预测结果进行对比分析。结果表明:基于长短期记忆神经网络预测模型将均方误差降低88.48%,表明所建模型更适用于GHI预测。
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| 关 键 词： | 太阳辐照度预测 循环神经网络 长短期记忆神经网络 深度学习 |
SHORT-TERM SOLAR IRRADIATION FORECAST BASED ON LSTM NEURAL NETWORK |
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| Zhao Shuqiang,Shang Yudong,Yang Yanyan,Li Yonghua.SHORT-TERM SOLAR IRRADIATION FORECAST BASED ON LSTM NEURAL NETWORK[J].Acta Energiae Solaris Sinica,2021(3):383-388. |
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| Authors: | Zhao Shuqiang Shang Yudong Yang Yanyan Li Yonghua |
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| Affiliation: | (State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources(North China Electric Power University),Baoding 011003,China) |
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| Abstract: | This paper proposed a short-term solar irradiation forecast model based on long/short term memory neural network. The training samples with recursive structure are used to guarantee the time correlation within training sample. A prediction model based on long-short-term memory neural network is established and compared with the traditional prediction model based on artificial neural network. The results shown that compared with the traditional prediction model based on artificial neural network,the prediction model based on long-short-term memory neural network can significantly reduce the mean square error,which indicates that the model is more suitable for GHI prediction. |
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| Keywords: | solar irradiation forecast recurrent neural network long-short-term memory neural network deep learning |
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