Chenglian Ma1, Rui Han1, Zhao An2,*, Tianyu Hu2, Meizhu Jin2
Energy Engineering, Vol.121, No.5, pp. 1245-1261, 2024, DOI:10.32604/ee.2024.046644
Abstract Precise forecasting of solar power is crucial for the development of sustainable energy systems. Contemporary forecasting approaches often fail to adequately consider the crucial role of weather factors in photovoltaic (PV) power generation and encounter issues such as gradient explosion or disappearance when dealing with extensive time-series data. To overcome these challenges, this research presents a cutting-edge, multi-stage forecasting method called D-Informer. This method skillfully merges the differential transformation algorithm with the Informer model, leveraging a detailed array of meteorological variables and historical PV power generation records. The D-Informer model exhibits remarkable superiority over competing models across multiple performance metrics,… More >
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