Multi‐Resolution Weather‐Index‐Guided Monthly Hydro‐Wind‐PV Joint Scenario Generation Under Extreme Drought

Reliable hydro‐wind‐PV joint scenarios under extreme drought are essential for assessing renewable power adequacy and operational flexibility in renewable‐dominant power systems. However, existing studies on joint hydro‐wind‐PV modelling often lack detailed weather‐process representation, adequate temporal resolution and consideration of cumulative drought effects, limiting their applicability to monthly scenario generation at hourly resolution during extreme droughts. To address this issue, this study develops a multi‐resolution variable‐alignment conditional diffusion model (TXDM) for monthly hydro‐wind‐PV joint scenario generation under extreme drought conditions. Unlike conventional methods, the proposed framework incorporates multi‐resolution weather indices to characterise drought‐related impacts on monthly hourly renewable power generation. Case studies in Sichuan demonstrate that TXDM improves deterministic and probabilistic accuracy, preserves spatio‐temporal dependence and generates credible few‐shot extreme drought scenarios. The generated scenarios provide reliable high‐resolution inputs for renewable power adequacy assessment, reserve estimation, storage dispatch and hydro‐wind‐PV coordination during extreme droughts.