Correlation aware multi-step ahead wind speed forecasting with heteroscedastic multi-kernel learning

•A novel multi-step ahead wind speed forecasting method is designed based on multi-kernel learning.•The method considers the task correlation and the heteroscedasticity of forecasting errors.•The optimization is solved within the framework of variational Bayesian.•The proposed model is tested comprehensively in different wind farms and different seasons.