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Reliable forecasting of Global Horizontal Irradiance (GHI) is essential for mitigating the variability of solar energy in power grids. This study presents a comprehensive benchmark of ten deep learning architectures for short-term (1-hour…

Machine Learning · Computer Science 2026-01-01 Tin Hoang

Global horizontal irradiance (GHI) plays a vital role in estimating solar energy resources, which are used to generate sustainable green energy. In order to estimate GHI with high spatial resolution, a quantitative irradiance estimation…

Applications · Statistics 2023-12-04 Longfeng Nie , Yuntian Chen , Dongxiao Zhang , Xinyue Liu , Wentian Yuan

The energy output a photo voltaic(PV) panel is a function of solar irradiation and weather parameters like temperature and wind speed etc. A general measure for solar irradiation called Global Horizontal Irradiance (GHI), customarily…

Machine Learning · Computer Science 2019-05-01 Bhaskar Pratim Mukhoty , Vikas Maurya , Sandeep Kumar Shukla

Ahead-of-time forecasting of the output power of power plants is essential for the stability of the electricity grid and ensuring uninterrupted service. However, forecasting renewable energy sources is difficult due to the chaotic behavior…

Computer Vision and Pattern Recognition · Computer Science 2023-10-27 Anas Al-lahham , Obaidah Theeb , Khaled Elalem , Tariq A. Alshawi , Saleh A. Alshebeili

Gridded global horizontal irradiance (GHI) databases are fundamental for analysing solar energy applications' technical and economic aspects, particularly photovoltaic applications. Today, there exist numerous gridded GHI databases whose…

Applied Physics · Physics 2022-08-12 Sebastian Zainali , Dazhi Yang , Tomas Landelius , Pietro E. Campana

In the present work, we collect solar irradiance and atmospheric condition data from several products, obtained from both numerical models (ERA5 and NORA3) and satellite observations (CMSAF-SARAH3). We then train simple supervised Machine…

Atmospheric and Oceanic Physics · Physics 2025-01-23 J Rabault , ML Sætra , A Dobler , S Eastwood , E Berge

Solar power harbors immense potential in mitigating climate change by substantially reducing CO$_{2}$ emissions. Nonetheless, the inherent variability of solar irradiance poses a significant challenge for seamlessly integrating solar power…

Machine Learning · Computer Science 2023-10-24 Oussama Boussif , Ghait Boukachab , Dan Assouline , Stefano Massaroli , Tianle Yuan , Loubna Benabbou , Yoshua Bengio

Knowing the behavior of solar radiation at a geographic location is essential for the use of energy from the sun using photovoltaic systems; however, the number of stations for measuring meteorological parameters and for determining the…

Machine Learning · Computer Science 2022-04-13 Luis Eduardo Ordoñez Palacios , Víctor Bucheli Guerrero , Hugo Ordoñez

Accurately predicting long-term rainfall is challenging. Global climate indices, such as the El Ni\~no-Southern Oscillation, are standard input features for machine learning. However, a significant gap persists regarding local-scale indices…

Machine Learning · Computer Science 2026-02-20 Kiattikun Chobtham

This study proposes an approximate model to estimate the solar radiation spectrum intensity in Seoul, Republic of Korea, for the year 2024, aiming to analyze optimal conditions related to energy generation. Since the solar radiation…

Signal Processing · Electrical Eng. & Systems 2025-04-14 Jeonggyu Hwang

Solar irradiance is the primary input for all solar energy generation systems. The amount of available solar radiation over time under the local weather conditions helps to decide the optimal location, technology and size of a solar energy…

Atmospheric and Oceanic Physics · Physics 2019-12-17 T. A. Fathima , Vasudevan Nedumpozhimana , Yee Hui Lee , Stefan Winkler , Soumyabrata Dev

Satellite remote sensing has been reported to be a promising approach for the monitoring of atmospheric PM2.5. However, the satellite-based monitoring of ground-level PM2.5 is still challenging. First, the previously used polar-orbiting…

Atmospheric and Oceanic Physics · Physics 2018-05-30 Tongwen Li , Chengyue Zhang , Huanfeng Shen , Qiangqiang Yuan , Liangpei Zhang

This study predicts hourly solar irradiance components, Global Horizontal Irradiance (GHI), Direct Normal Irradiance (DNI), and Diffuse Horizontal Irradiance (DHI) using meteorological data to forecast solar energy output in Ibadan,…

Applications · Statistics 2025-08-12 Obarotu Peter Urhuerhi , Christopher Udomboso , Caston Sigauke

With the increasing penetration of solar power into power systems, forecasting becomes critical in power system operations. In this paper, an hourly-similarity (HS) based method is developed for 1-hour-ahead (1HA) global horizontal…

Machine Learning · Statistics 2018-03-12 Cong Feng , Jie Zhang

Accurate modeling of infrasound transmission loss is essential for evaluating the performance of the International Monitoring System, enabling the effective design and maintenance of infrasound stations to support compliance of the…

Accurate day-ahead solar irradiance forecasting is essential for integrating solar energy into the power grid. However, it remains challenging due to the pronounced diurnal cycle and inherently complex cloud dynamics. Current methods either…

Machine Learning · Computer Science 2026-04-30 Ziqing Ma , Kai Ying , Xinyue Gu , Tian Zhou , Tianyu Zhu , Haifan Zhang , Peisong Niu , Zheng Wang , Cong Bai , Liang Sun

This paper compares different forecasting methods and models to predict average values of solar irradiance with a sampling time of 15 min over a prediction horizon of up to 3 h. The methods considered only require historic solar irradiance…

Applications · Statistics 2019-07-30 Christian A. Hans , Elin Klages

In this paper, we present a method to determine the global horizontal irradiance (GHI) from the power measurements of one or more PV systems, located in the same neighborhood. The method is completely unsupervised and is based on a physical…

Machine Learning · Statistics 2018-02-23 Lorenzo Nespoli , Vasco Medici

For short-term solar irradiance forecasting, the traditional point forecasting methods are rendered less useful due to the non-stationary characteristic of solar power. The amount of operating reserves required to maintain reliable…

Machine Learning · Computer Science 2023-08-02 Sakshi Mishra , Praveen Palanisamy

Due to the increasing integration of solar power into the electrical grid, forecasting short-term solar irradiance has become key for many applications, e.g.~operational planning, power purchases, reserve activation, etc. In this context,…

Machine Learning · Statistics 2019-11-13 Jesus Lago , Karel De Brabandere , Fjo De Ridder , Bart De Schutter
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