Resolving the Full Radiant Spectrum: Solving the Shortwave Imaging Problem for Enhanced Radiant Energy Analysis

Merchant, Coleman; Meggers, Forrest

doi:10.1109/metrolivenv54405.2022.9826940

2022 IEEE International Workshop on Metrology for Living Environment (MetroLivEn) 2022

DOI: 10.1109/metrolivenv54405.2022.9826940

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Resolving the Full Radiant Spectrum: Solving the Shortwave Imaging Problem for Enhanced Radiant Energy Analysis

Coleman Merchant

Forrest Meggers

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2024

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A Review and Evaluation of the State of Art in Image-Based Solar Energy Forecasting: The Methodology and Technology Used

Travieso-González,

Cabrera-Quintero,

Piñán-Roescher

et al. 2024

Applied Sciences

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The increasing penetration of solar energy into the grid has led to management difficulties that require high accuracy forecasting systems. New techniques and approaches are emerging worldwide every year to improve the accuracy of solar power forecasting models and reduce uncertainty in predictions. This article aims to evaluate and compare various solar power forecasting methods based on their characteristics and performance using imagery. To achieve this goal, this article presents an updated analysis of diverse research, which is classified in terms of the technologies and methodologies applied. This analysis distinguishes studies that use ground-based sensor measurements, satellite data processing, or all-sky camera images, as well as statistical regression approaches, artificial intelligence, numerical models, image processing, or a combination of these technologies and methods. Key findings include the superior accuracy of hybrid models that integrate multiple data sources and methodologies, and the promising potential of all-sky camera systems for very short-term forecasting due to their ability to capture rapid changes in cloud cover. Additionally, the evaluation of different error metrics highlights the importance of selecting appropriate benchmarks, such as the smart persistence model, to enhance forecast reliability. This review underscores the need for continued innovation and integration of advanced technologies to meet the challenges of solar energy forecasting.

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A Review and Evaluation of the State of Art in Image-Based Solar Energy Forecasting: The Methodology and Technology Used

Travieso-González,

Cabrera-Quintero,

Piñán-Roescher

et al. 2024

Applied Sciences

View full text Add to dashboard Cite

show abstract

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Resolving the Full Radiant Spectrum: Solving the Shortwave Imaging Problem for Enhanced Radiant Energy Analysis

Cited by 1 publication

References 4 publications

A Review and Evaluation of the State of Art in Image-Based Solar Energy Forecasting: The Methodology and Technology Used

A Review and Evaluation of the State of Art in Image-Based Solar Energy Forecasting: The Methodology and Technology Used

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