Deep learning

Improved satellite-based estimation of direct normal solar irradiance using clearness index with deep learning methods

As the capacity addition of solar energy systems continues to increase, solar resource assessment is necessary in supporting the feasibility study. This can reduce associated risks of solar energy projects and improve their reliability. Considering …

Improved satellite-based intra-day solar forecasting with a chain of deep learning models

Satellite data and satellite-derived irradiance products have been extensively used in solar forecasting to better capture the spatio-temporal variations of solar irradiance. However, the potential advantages of using satellitederived irradiance and …

A review of distributed solar forecasting with remote sensing and deep learning

The rapidly growing capacity of globally distributed solar generation systems (DSGs) has imposed new challenges for solar forecasting research: the need for high-fidelity spatial solar forecasts across utility scale areas with minimized capital, …

Global and direct solar irradiance estimation using deep learning and selected spectral satellite images

To fully exploit the spectral information of modern geostationary satellites, this work proposes a deep learning framework using convolutional neural networks (CNNs) and attention mechanism for 5-min ground-level global horizontal irradiance (GHI) …