[1]刘敬,高志建.应用神经网络法预测光伏系统发电功率[J].控制与信息技术,2010,(03):28-32.[doi:10.13889/j.issn.2095-3631.2010.03.007]
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应用神经网络法预测光伏系统发电功率()
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《控制与信息技术》[ISSN:2095-3631/CN:43-1486/U]

卷:
期数:
2010年03期
页码:
28-32
栏目:
绿色能源与节能
出版日期:
2010-06-05

文章信息/Info

Title:
Application of Neural Network on Generating Power Forecasting for PV System
文章编号:
1671-8410(2010)03-0028-05
作者:
刘敬1高志建2
1.华北电力大学 2.沧州供电公司
关键词:
神经网络光伏系统的功率输出日照预测
Keywords:
neural network(NN) power output for PV system solar quantity estimation
分类号:
TM761+.21
DOI:
10.13889/j.issn.2095-3631.2010.03.007
摘要:
日照的不稳定性导致光伏系统的输出受到影响,为了尽可能准确地预测光伏系统的功率输出,就需要一种估测日照量的方法。文章中提出了一种使用神经网络预测日照量的方法,并通过计算机仿真证实了这种方法的合理性。同时介绍了3种神经网络法:FFNN、RBFNN和RNN,最后还对这3种方法的仿真结果进行了适当的比较。
Abstract:
Output of photo-voltaic (PV) system is influenced by unconstant solar radiation. In order to forecast the power output of PV system as accurately as possible, a method of solar quantity estimation is required. Therefore, it is proposed a method of neural network to estimate solar quantity, and the rationality is confirmed by computer simulations. Then three kinds of neural networks: FFNN, RBFNN and RNN are introduced, and finally the simulation results are properly compared.

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更新日期/Last Update: 2019-04-12