SDWPF dataset

Wind power, while a clean and safe form of renewable energy, presents integration challenges to the grid system due to its variable supply. Consequently, Wind Power Forecasting (WPF) is pivotal for the successful integration and operation of wind energy. Existing publicly available WPF datasets, however, often feature a limited number of wind turbines and typically lack granular details on turbine locations and dynamic contextual information. To address this gap and promote the advancements of WPF research, we introduce a dataset called the Spatial Dynamic Wind Power Forecasting dataset (SDWPF). This dataset comprises data collected over one year from a wind farm housing an array of 134 wind turbines. The SDWPF dataset includes the spatial distribution of the wind turbines and the dynamic context factors for each turbine. Further leveraging the potential of SDWPF, we initiated the ACM KDD Cup 2022, drawing registrations from over 2400 teams globally.