Abstract: The proportion of wind power generation in China's energy mix has increased yearly. Accurate and comprehensive assessment of wind resources is a prerequisite for improving wind power output and consumption capacity. A high-resolution gridded wind resource dataset based on the spatial interpolation method can effectively provide an assessment of wind resources in a wide range, gridded, and refined way. To improve the accuracy of the wind resource dataset, this paper proposes an improved K-means++ Adaptive Inverse Distance Weighted interpolation method (K-means++ AIDW). Adopting this method, the wind measurement data derived from 109 nation-level meteorological observation stations in Shandong province across the whole year of 2022 are processed and interpolated on every constructed grid point in the constructed grid with a spatial resolution of 9km×9km, hour by hour, to obtain a high-resolution gridded wind resource dataset. According to statistical comparison between interpolation and original observation, we found that the K-Means++AIDW interpolation method proposed in this paper outputs an MAE decreased by 5.4% compared with that of the traditional Inverse Distance Weighting (IDW), decreased by 7.8% compared with Kriging interpolation; as well as an RMSE decreased by 5.9% compared with that of the traditional IDW, decreased by 8.1% compared with Kriging interpolation, which shows its advantage in overall error control. Compared with ERA5 (Fifth Generation of European Centre for Medium-range Weather Forecasts Atmospheric Reanalysis of the Global Climate) with spatial resolution of 0.25°×0.25°, The K-Means++AIDW interpolation dataset's MAE and RMSE decreased by 11.95% and 10.07% respectively on average, which verifies the accuracy and effectiveness of the interpolation method designed in this paper and the accuracy and reliability of the generated high-resolution gridded dataset. It can be used as a reliable data basis for evaluating the wind energy resource potential of Shandong Province and provide accurate data support for wind farm site selection and wind energy resource management.