AUTHOR=Dai Qiangsheng , Huo Xuesong , Hao Yuchen , Yu Ruiji 

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

JOURNAL=Frontiers in Energy Research

VOLUME=11

YEAR=2023

URL=https://www.frontiersin.org/journals/energy-research/articles/10.3389/fenrg.2023.1204032

DOI=10.3389/fenrg.2023.1204032

ISSN=2296-598X

ABSTRACT=<p>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.</p>