Spatio-temporal prediction for distributed PV generation system based on deep learning neural network model

To obtain higher accuracy of PV prediction to enhance PV power generation technology. This paper proposes a spatio-temporal prediction method based on a deep learning neural network model. Firstly, spatio-temporal correlation analysis is performed for 17 PV sites. Secondly, we compare CNN-LSTM with...

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Bibliographic Details
Published in:Frontiers in energy research 2023-06, Vol.11
Main Authors: Dai, Qiangsheng, Huo, Xuesong, Hao, Yuchen, Yu, Ruiji
Format: Article
Language:English
Subjects:
CNN-LSTM
deep learning
distributed PV generation system
PV prediction
spatio-temporal
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Summary:To obtain higher accuracy of PV prediction to enhance PV power generation technology. This paper proposes a spatio-temporal prediction method based on a deep learning neural network model. Firstly, spatio-temporal correlation analysis is performed for 17 PV sites. Secondly, we compare CNN-LSTM with a single CNN or LSTM model trained on the same dataset. From the evaluation indexes such as loss map, regression map, RMSE, and MAE, the CNN-LSTM model that considers the strong correlation of spatio-temporal correlation among the 17 sites has better performance. The results show that our method has higher prediction accuracy.
ISSN:2296-598X
2296-598X
DOI:10.3389/fenrg.2023.1204032