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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

A high spatiotemporal resolution and accurate middle-to-long-term prediction data is essential to support China's dual-carbon targets under global warming scenarios. In this study, we simulated hourly solar radiation at a 10 km* 10 km…

Atmospheric and Oceanic Physics · Physics 2025-11-13 Daoming Zhu , Xinghong Cheng , Yanbo Shen , Chunsong Lu , Duanyang Liu , Shuqi Yan , Naifu Shao , Zhongfeng Xu , Jida Peng , Bing Chen

Predicting the intensity and amount of sunlight as a function of location and time is an essential component in identifying promising locations for economical solar farming. Although weather models and irradiance data are relatively…

Applications · Statistics 2019-06-25 Furong Sun , Robert B. Gramacy , Benjamin Haaland , Siyuan Lu , Youngdeok Hwang

As the use of solar power increases, having accurate and timely forecasts will be essential for smooth grid operators. There are many proposed methods for forecasting solar irradiance / solar power production. However, many of these methods…

Machine Learning · Computer Science 2023-07-11 Timothy Cargan , Dario Landa-Silva , Isaac Triguero

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

Power supply from renewable resources is on a global rise where it is forecasted that renewable generation will surpass other types of generation in a foreseeable future. Increased generation from renewable resources, mainly solar and wind,…

Machine Learning · Statistics 2017-06-28 Mohana Alanazi , Mohsen Mahoor , Amin Khodaei

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

Accurate surface solar irradiance (SSI) forecasting is essential for optimizing renewable energy systems, particularly in the context of long-term energy planning on a global scale. This paper presents a pioneering approach to solar…

Atmospheric and Oceanic Physics · Physics 2024-11-14 Alberto Carpentieri , Jussi Leinonen , Jeff Adie , Boris Bonev , Doris Folini , Farah Hariri

Accurate day-ahead forecasts of solar irradiance are required for the large-scale integration of solar photovoltaic (PV) systems into the power grid. However, current forecasting solutions lack the temporal and spatial resolution required…

Machine Learning · Computer Science 2025-11-07 Baptiste Schubnel , Jelena Simeunović , Corentin Tissier , Pierre-Jean Alet , Rafael E. Carrillo

Effective utilization of photovoltaic (PV) plants requires weather variability robust global solar radiation (GSR) forecasting models. Random weather turbulence phenomena coupled with assumptions of clear sky model as suggested by Hottel…

Computer Vision and Pattern Recognition · Computer Science 2017-12-12 Subhadip Dey , Sawon Pratiher , Saon Banerjee , Chanchal Kumar Mukherjee

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

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

The increasing demand for electricity and the need for clean energy sources have increased solar energy use. Accurate forecasts of solar energy are required for easy management of the grid. This paper compares the accuracy of two Gaussian…

Applications · Statistics 2022-12-13 Edina Chandiwana , Caston Sigauke , Alphonce Bere

Renewable energy forecasting is attaining greater importance due to its constant increase in contribution to the electrical power grids. Solar energy is one of the most significant contributors to renewable energy and is dependent on solar…

Machine Learning · Computer Science 2025-10-08 V. Gunasekaran , K. K. Kovi , S. Arja , R. Chimata

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

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

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

The output of solar power generation is significantly dependent on the available solar radiation. Thus, with the proliferation of PV generation in the modern power grid, forecasting of solar irradiance is vital for proper operation of the…

Applications · Statistics 2022-09-05 Kwasi Opoku , Svetlana Lucemo , Qun Zhou Sun , Aleksandar Dimitrovski

Satellite-based solar irradiation forecasting is useful for short-term intra-day time horizons, outperforming numerical weather predictions up to 3-4 hours ahead. The main techniques for solar satellite forecast are based on sophisticated…

Atmospheric and Oceanic Physics · Physics 2020-09-02 Franco Marchesoni-Acland , Rodrigo Alonso Suárez

In this work we analyse a set of benchmark methods for solar irradiance forecasting based on the clear-sky index, namely, persistence, climatology, smart-persistence and convex combination (CC) of persistence and climatology. To assess the…

Data Analysis, Statistics and Probability · Physics 2022-03-29 Rodrigo Alonso-Suárez , Daniel Aicardi , Franco Marchesoni-Acland
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