Study on the combined method of mathematical statistics and numerical simulation for wind resource assessment

Accurate wind resource assessment is crucial for enhancing the core competitiveness of wind power. This study proposes an advanced assessment method integrating mathematical statistics and numerical simulation to overcome the limitations of conventional methods that focus solely on average wind power density. Firstly, an indicator system encompassing wind resource reserves, temporal volatility, and stability has been established. Secondly, an Analytic Hierarchy Process (AHP)-based multidimensional fusion algorithm has been proposed to quantitatively integrate indicators. Finally, a hybrid assessment methodology that synergistically combines mathematical statistical approaches with numerical simulations has been proposed. Taking four onshore wind farms as examples, the proposed method significantly improves the precision of wind resource assessments and demonstrates strong agreement with operational data, with calculated weighted comprehensive value (WCV) of 0.385, 0.207, 0.945, and 0.517, closely matching the rank of actual capacity factors of 0.217, 0.198, 0.268, and 0.243, respectively. Meanwhile, the proposed method improves site adaptability by an average of 2.8% across the four wind farms compared to conventional approach, providing a theoretical basis for micro-siting, and ultimately improving the adaptability of wind power projects to actual conditions and ensuring the safe and stable operation of the power grid.