A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is
Wind power is a rapidly growing source of clean energy. Accurate short-term forecasting of wind power is essential for reliable energy generation. In this study, we propose a novel wind power forecasting approach using spatiotemporal analysis to enhance forecasting performance. First, the wind power time-series data from the target turbine and adjacent neighboring turbines were utilized to form a graph structure using graph neural networks (GNN). The graph structure was used to compute thedoi:10.3389/fenrg.2022.920407 fatcat:pnzss7y6tbfohhvnafequbk6pa