戴锦. 基于改进BP神经网络光伏发电量预测研究[J]. 南昌航空大学学报(自然科学版), 2015, 29(3): 91-97. DOI: 10.3969/j.issn.1001-4926.2015.03.016
引用本文: 戴锦. 基于改进BP神经网络光伏发电量预测研究[J]. 南昌航空大学学报(自然科学版), 2015, 29(3): 91-97. DOI: 10.3969/j.issn.1001-4926.2015.03.016
DAI Jin. Research on Improve the Prediction of BP Neural Net Photovoltaic Power Generation[J]. Journal of nanchang hangkong university(Natural science edition), 2015, 29(3): 91-97. DOI: 10.3969/j.issn.1001-4926.2015.03.016
Citation: DAI Jin. Research on Improve the Prediction of BP Neural Net Photovoltaic Power Generation[J]. Journal of nanchang hangkong university(Natural science edition), 2015, 29(3): 91-97. DOI: 10.3969/j.issn.1001-4926.2015.03.016

基于改进BP神经网络光伏发电量预测研究

Research on Improve the Prediction of BP Neural Net Photovoltaic Power Generation

  • 摘要: 分析了影响光伏电池输出的主要因素,建立基于改进BP神经网络的光伏发电量预测模型。由光伏输出影响因素的分析,利用光照强度及环境温度对改进BP神经网络进行训练,对比了传统数学模型、传统BP模型与改进的BP模型的预测结果,结果表明该模型有较准确的预测能力。

     

    Abstract: The main influence factors of the photovoltaic cell output has been analyzed and the prediction model on improved the photovoltaic power generation of BP neural net was established.Based on the analysis of influence factors, using the light intensity and environment temperature to train improving BP neural network, and the predictive results of the traditional mathematical model, the traditional BP model and the improved BP model were compared.The results show that the model has relatively accurate prediction ability.

     

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