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New diffusion model forecasts solar irradiance by jointly denoising sky images and clear-sky index

Researchers have developed a novel single-stage diffusion model for ultra-short-term solar irradiance forecasting. This new approach jointly denoises future sky images and their corresponding clear-sky index sequences within a single diffusion process. Unlike traditional two-stage methods that forecast frames and then regress irradiance, this model directly predicts irradiance from a denoised preview of future sky conditions, eliminating the need for a separate regression stage. The model demonstrated superior performance on SIRTA data, achieving a pooled RMSE of 104.1 W/m² and a CRPS skill score of +0.34, outperforming twelve baseline configurations and highlighting the benefits of joint training over cascaded approaches. AI

IMPACT This research introduces a more efficient and accurate method for solar irradiance forecasting, potentially improving renewable energy grid management.

RANK_REASON This is a research paper detailing a new model for solar irradiance forecasting. [lever_c_demoted from research: ic=1 ai=0.7]

Read on arXiv cs.LG →

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New diffusion model forecasts solar irradiance by jointly denoising sky images and clear-sky index

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This is a research paper detailing a new model for solar irradiance forecasting. [lever_c_demoted from research: ic=1 ai=0.7]
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COVERAGE [1]

  1. arXiv cs.LG TIER_1 English(EN) · Kanawut Suwandee, Suwichaya Suwanwimolkul ·

    Single-stage joint diffusion of sky images and clear-sky index for ultra-short-term irradiance forecasting: what the frame-to-irradiance stage discards

    arXiv:2610.21795v1 Announce Type: cross Abstract: Sky-image irradiance forecasting is dominated by a two-stage design: a video-prediction model forecasts future sky frames, and a separately trained regressor maps those frames to irradiance. We propose a single-stage alternative t…