Hybrid model for short-term wind power forecasting based on singular spectrum analysis and a temporal convolutional attention network with an adaptive receptive field

•A component partitioning mechanism is developed to obtain multiple groups of frequency components.•An improved TCAN model maintains efficient, stable and robust forecasting performance for long time scales.•An adaptive receptive field is integrated into TCAN model to ensure automatic extraction of multiple frequency-domain features.•A novel hybrid model based on SSA and an ARFTCAN is proposed to short-term wind power forecasting.