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GateFormer model improves solar irradiance forecasting using sky images

By PulseAugur Editorial · [1 sources] ·

Researchers have developed GateFormer, a novel dual-decoder Vision Transformer (ViT) model designed for intra-hour solar irradiance forecasting using sky images. This model integrates observed global horizontal irradiance (GHI) with visual cloud dynamics, decomposing the forecast into a trajectory prediction and a change prediction. GateFormer demonstrated a 9.6% improvement in RMSE over existing transformer baselines on the NREL-TSI benchmark and achieved the lowest final-horizon RMSE across multiple datasets, outperforming smart persistence by up to 28.86%. The adaptive weighting mechanism and supervised correction further enhanced its accuracy, particularly during positive ramp events. AI

IMPACT This research could lead to more accurate short-term solar power generation forecasts, improving grid stability and renewable energy integration.

RANK_REASON The item describes a new research paper detailing a novel model for solar irradiance prediction. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.LG →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

GateFormer model improves solar irradiance forecasting using sky images

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The item describes a new research paper detailing a novel model for solar irradiance prediction. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.LG TIER_1 English(EN) · David Hamlyn, Sunny Chaudhary, Jonathon Hare, Tasmiat Rahman ·

    GateFormer: Forecast-Space Decomposition for Intra-Hour Solar Irradiance Prediction from Sky Images

    arXiv:2610.30942v1 Announce Type: cross Abstract: Sub-hourly dispatch, balancing, and storage control increasingly depend on forecasts that anticipate rapid variability in solar generation. Accurate sky-image-based irradiance forecasting requires a combination of visual cloud dyn…

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