Prediction of energy photovoltaic power generation based on artificial intelligence algorithm.

Zhang, Shuhua; Wang, Jinsong; Liu, Haibo; Tong, Jie; Sun, Zheng

The key to the coordination of photovoltaic power generation and conventional energy power load lies in the accurate prediction of photovoltaic power generation. At present, prediction models have problems with accuracy and system operation stability. Based on the neural network algorithm, this research carries the prediction of energy photovoltaic power generation and establishes a BP neural network prediction model and a wavelet neural network prediction model. Moreover, this research studies the influence of various factors on the prediction t of photovoltaic power generation, and analyzes the relationship between the various factors. In addition, in this study, a comparative test is constructed to analyze the model performance, and a statistical graph is drawn to take a visual comparison of performance. The research shows that the model proposed in this paper has certain effects and has certain advantages in the prediction of photovoltaic power generation.

PHOTOVOLTAIC power generation; ARTIFICIAL intelligence; ARTIFICIAL neural networks; GRAPHIC methods in statistics; PREDICTION models; FORECASTING

Neural Computing & Applications, 2021, Vol 33, Issue 3, p821

0941-0643

Academic Journal

10.1007/s00521-020-05249-z