Photovoltaic Super-Short Term Power Prediction Based on BP-ANN Generalization Neural Network Technology Research

Xin Xin Shang; Qi Juan Chen; Zi Fen Han; Xiao Dong Qian

doi:10.4028/www.scientific.net/AMR.791-793.1925

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 791-793Photovoltaic Super-Short Term Power Prediction...

Photovoltaic Super-Short Term Power Prediction Based on BP-ANN Generalization Neural Network Technology Research

Abstract:

The research is mainly based on BP-ANN neural network method, through direct and indirect data collection to predict the photovoltaic super-short term power generation, discussed the influence and effection about the generalization of the BP-ANN neural network model ,which is used to predict the photovoltaic super-short term power generation. Combined with the actual operation situation, analyzed and compared the system operation results. The actual results show that measured data has the same trend with the super-short term prediction results, the root mean square error and mean absolute error are small, the prediction accuracy reached 96.71% and has high application value.

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Periodical:

Advanced Materials Research (Volumes 791-793)

Pages:

1925-1928

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.791-793.1925

Citation:

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Online since:

September 2013

Authors:

Xin Xin Shang, Qi Juan Chen, Zi Fen Han, Xiao Dong Qian

Keywords:

BP-ANN Neural Networks, Photovoltaic Power Generation, Photovoltaic Power Prediction Method, Photovoltaic Power Prediction Model

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