The power output of a wind turbine depends on a variety of factors, including wind speed at different heights, wind direction, temperature and turbine properties. Wind speed and direction, in particular, have complex cycles and fluctuate dramatically, leading to large uncertainties in wind power output. This study uses variational mode decomposition (VMD) to decompose the wind power series and Temporal fusion transformer (TFT) to forecast wind power for the next 1h, 3h and 6h. The experimental results show that VMD outperforms other decomposition algorithms and the TFT model outperforms other decomposition models.