一种自主学习建立模型库的光伏功率预测方法
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摘要
为了保障电力系统的稳定运行和合理的调度分配,提高预测系统的预测精度,提出一种自主学习建立气象模型库的光伏功率预测方法。介绍该方法的实现过程,并通过实例分析该方法的预测结果。
In order to ensure the stable operation of power system and reasonable dispatch and distribution,aphotovoltaic power prediction method based on self-learning and building meteorological model library was proposed.The implementation process of the method was introduced,and the prediction results of the method were analyzed by an example.
In order to ensure the stable operation of power system and reasonable dispatch and distribution,aphotovoltaic power prediction method based on self-learning and building meteorological model library was proposed.The implementation process of the method was introduced,and the prediction results of the method were analyzed by an example.
引文
[1]龚莺飞,鲁宗相,乔颖,等.光伏功率预测技术[J].电力系统自动化,2016(04):140-151.
[2]2016年光伏发电统计信息[EB/OL].[2017-02-04].http://www.nea.gov.cn/2017-02/04/c_136030860.htm.
[3]吕双辉,蔡声霞,王守相.分布式光伏-储能系统的经济性评估及发展建议[J].中国电力,2015(02):139-144.
[4]YONA A,SENJYU T,FUNABASHI T,et al.Application of neural network to one-day-ahead 24hours generating power forecasting for photovoltaic system[J].Intelligent Systems Applications to Power Systems,2007:1-6.
[5]Jianhong Xie.Time Series Prediction Based on Recurrent LSSVM with Mixed Kernel[J].Asia-Pacific Conference on Information Processing.2009(01):113-116.
[6]刘瑞叶,黄磊.基于动态神经网络的风电场输出功率预测[J].电力系统自动化,2012(11):19-22.
[7]朱永强,田军.最小二乘支持向量机在光伏功率预测中的应用[J].电网技术,2011(07):54-59.
[8]刘长良,吴家佳.基于核极端学习机的短期风电功率预测研究[J].热能动力工程,2017(01):95-100.
[9]Almonacid F,P.J.Pérez-Higueras,EduardoF.Fernández,et al.A methodology based on dynamic artificial neural network for short-term forecasting of the power output of a PV generator[J].Energy Conversion and Management,2014,85(9):389-398.
[2]2016年光伏发电统计信息[EB/OL].[2017-02-04].http://www.nea.gov.cn/2017-02/04/c_136030860.htm.
[3]吕双辉,蔡声霞,王守相.分布式光伏-储能系统的经济性评估及发展建议[J].中国电力,2015(02):139-144.
[4]YONA A,SENJYU T,FUNABASHI T,et al.Application of neural network to one-day-ahead 24hours generating power forecasting for photovoltaic system[J].Intelligent Systems Applications to Power Systems,2007:1-6.
[5]Jianhong Xie.Time Series Prediction Based on Recurrent LSSVM with Mixed Kernel[J].Asia-Pacific Conference on Information Processing.2009(01):113-116.
[6]刘瑞叶,黄磊.基于动态神经网络的风电场输出功率预测[J].电力系统自动化,2012(11):19-22.
[7]朱永强,田军.最小二乘支持向量机在光伏功率预测中的应用[J].电网技术,2011(07):54-59.
[8]刘长良,吴家佳.基于核极端学习机的短期风电功率预测研究[J].热能动力工程,2017(01):95-100.
[9]Almonacid F,P.J.Pérez-Higueras,EduardoF.Fernández,et al.A methodology based on dynamic artificial neural network for short-term forecasting of the power output of a PV generator[J].Energy Conversion and Management,2014,85(9):389-398.