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

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....

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Published inApplied sciences Vol. 14; no. 13; p. 5605
Main Authors Travieso-González, Carlos M., Cabrera-Quintero, Fidel, Piñán-Roescher, Alejandro, Celada-Bernal, Sergio
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 01.07.2024
Subjects
all-sky camera
Alternative energy sources
Cameras
Comparative analysis
Electricity distribution
Energy consumption
Energy industry
Energy resources
Forecasting techniques
Industrial plant emissions
nowcasting
Radiation
regression method
Renewable resources
satellite
Satellites
Sensors
Solar energy
solar irradiance
statistical method
Time series
Weather forecasting
Online AccessGet full text
ISSN2076-3417
2076-3417
DOI10.3390/app14135605

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Abstract 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.
AbstractList 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.
Author Travieso-González, Carlos M.
Piñán-Roescher, Alejandro
Celada-Bernal, Sergio
Cabrera-Quintero, Fidel
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  fullname: Celada-Bernal, Sergio
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Snippet The increasing penetration of solar energy into the grid has led to management difficulties that require high accuracy forecasting systems. New techniques and...
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SubjectTerms all-sky camera
Alternative energy sources
Cameras
Comparative analysis
Electricity distribution
Energy consumption
Energy industry
Energy resources
Forecasting techniques
Industrial plant emissions
nowcasting
Radiation
regression method
Renewable resources
satellite
Satellites
Sensors
Solar energy
solar irradiance
statistical method
Time series
Weather forecasting
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Title A Review and Evaluation of the State of Art in Image-Based Solar Energy Forecasting: The Methodology and Technology Used
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