As the penetration of solar energy generation into power systems keeps rising, intra-hour
solar forecasting (IHSF) is becoming increasingly important for the secure and economical …

Sky-image-based solar forecasting using deep learning has been recognized as a
promising approach in reducing the uncertainty in solar power generation. However, one of …

Semantic segmentation of ground-based all-sky images (ASIs) can provide high-resolution
cloud coverage information of distinct cloud types, applicable for meteorology-, climatology …

Cloud detection is a necessary phase in satellite images processing to retrieve the
atmospheric and lithospheric parameters. Currently, some cloud detection methods based …

With the inherent volatility of solar radiation, accurate short-term prediction of solar
irradiance is essential to cost-efficiently stabilise and operate power grids. Cloud is the …

Sky image-based solar forecasting using deep learning has been recognized as a
promising approach in reducing the uncertainty of solar power generation. However, a major …

This article introduces a review on implementations of various methods to perform cloud
detection and its related applications such as detection of cloud shadow, types of cloud and …

The whole-sky imager has been increasingly used for ground-based cloud automatic
observation. Many approaches based on image processing have been applied to detect or …

The increasing penetration of photovoltaic systems in the power grid makes it vulnerable to
cloud shadow projection. Real-time cloud segmentation in ground-based infrared images is …

A methodology, aimed to be fully operational, for automatic cloud classification based on the
synergetic use of a sky camera and a ceilometer is presented. The random forest machine …