Research of a novel short-term wind forecasting system based on multi-objective Aquila optimizer for point and interval forecast

•An advanced forecasting system is proposed for short-term wind speed prediction.•The data pre-processing technique can extract effective information from the raw sequences and eliminate the volatility and uncertainty of the data.•Choose the appropriate benchmark models in different situations based on optimal benchmark model selection strategy.•A multi-objective optimizer is applied to find the optimal weights and a theoretical proof indicates that the weights assigned by this optimizer are Pareto optimal solutions.•Our proposed forecasting system can quantify the uncertainty of the wind speed sequences. Facing the increasing depletion of traditional energy resources and the worsening environmental issues, wind energy sources have been widely considered. As an essential renewable energy resource, wind energy features abundant deposits, extensive distribution, non-pollution, etc. In recent years, wind power generation occupies a non-negligible position in the electric power industry. Stable and reliable power system operation demands accurate wind speed prediction (WSP), but the inherent randomness of wind speed sequences complicates their fluctuations and causes them to be uncontrollable. In this paper, an innovative WSP system is proposed, which combines data pre-processing technique, benchmark model selection, an advanced optimizer for point forecast and interval forecast. Furthermore, this paper theoretically demonstrates that the weights allocated by this optimizer are Pareto optimal solutions. Six interval data from two sites in China are utilized to validate the forecasting performance of our developed model. The experimental results indicate that the developed model can achieve superior accuracy compared to the tested models in all cases for point forecast, and also obtains the forecasting interval with high coverage and low width error, which is an extremely crucial instruction to guarantee the security and stability of the power system.