EGU25-14067, updated on 15 Mar 2025
https://doi.org/10.5194/egusphere-egu25-14067
EGU General Assembly 2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
AI-Driven Power Forecasting for Renewable Energy: A Multi-Terrain Analysis from Shandong Province Wind Farms
Guiting Song, Veeranjaneyulu Chinta, and Kailong Wu
Guiting Song et al.
  • Ningbo Institute of Digital Twin, Eastern Institute of Technology, Ningbo, China (w18725561413l@163.com)

How to cite: Song, G., Chinta, V., and Wu, K.: AI-Driven Power Forecasting for Renewable Energy: A Multi-Terrain Analysis from Shandong Province Wind Farms, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-14067, https://doi.org/10.5194/egusphere-egu25-14067, 2025.

This abstract has been withdrawn on 25 Jul 2025.