Research on Photovoltaic Power Prediction Model Based on Transformer-BiLSTM

Photovoltaic power prediction is an important means to improve the operational efficiency and stability of power systems. In this paper, we propose a photovoltaic power prediction model based on Transformer and bidirectional long short-term memory network (BiLSTM), namely Transformer-BiLSTM. The proposed model integrates the advantages of Transformer in capturing long-range dependencies and complex feature interactions, as well as the bidirectional information processing capability of BiLSTM in handling time series data. Experimental results demonstrate that, the proposed model achieves significant improvements in both prediction accuracy and stability, providing a new solution for precise photovoltaic power prediction.