Research on time series based deep learning photovoltaic power generation model
The research focuses on the application of time series based deep learning in photovoltaic power generation models.Build an integrated GRU(Gated Recurrent Unit)network prediction model by collecting real-time power data and meteorological information from four different photovoltaic base stations.The model aims to process time series data and accurately predict photovoltaic power generation.The study also explores the impact of dataset size and model structure on prediction accuracy,confirming the potential and effectiveness of deep learning in photovoltaic power generation prediction.The experimental results show that the model performs well on both training and testing sets,especially surpassing traditional methods in terms of generalization ability.
time seriesdeep learningphotovoltaic power generation model
NETL
NSTL
万方数据
