arXiv Open Access 2021

Segmentation Algorithms for Ground-Based Infrared Cloud Images

Guillermo Terrén-Serrano Manel Martínez-Ramón

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Abstrak

The increasing number of Photovoltaic (PV) systems connected to the power grid are vulnerable to the projection of shadows from moving clouds. Global Solar Irradiance (GSI) forecasting allows smart grids to optimize the energy dispatch, preventing energy shortages caused by occlusion of the sun. This investigation compares the performances of machine learning algorithms (not requiring labelled images for training) for real-time segmentation of clouds in images acquired using a ground-based infrared sky imager. Real-time segmentation is utilized to extract cloud features using only the pixels in which clouds are detected.

Topik & Kata Kunci

eess.IV

Penulis (2)

Guillermo Terrén-Serrano

Manel Martínez-Ramón

Format Sitasi

APA MLA BibTeX

Terrén-Serrano, G., Martínez-Ramón, M. (2021). Segmentation Algorithms for Ground-Based Infrared Cloud Images. https://arxiv.org/abs/2102.10151

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Informasi Jurnal

Tahun Terbit: 2021
Bahasa: en
Sumber Database: arXiv
Akses: Open Access ✓