SRDM uses a recurrent diffusion approach to upsample climate data temporally, enabling simulation of wind and PV power under SSP126/SSP585 pathways while showing biases from low-resolution inputs.
A multi-scale time -series dataset with benchmark for machine learning in decarbonized energy grids
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.LG 1years
2024 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Quantifying Climate Change Impacts on Renewable Energy Generation: A Super-Resolution Recurrent Diffusion Model
SRDM uses a recurrent diffusion approach to upsample climate data temporally, enabling simulation of wind and PV power under SSP126/SSP585 pathways while showing biases from low-resolution inputs.