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Related papers: A Bayesian Approach to Probabilistic Solar Irradia…

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Solar flares are the most explosive phenomena in the solar system and the main trigger of the events' chain that starts from Coronal Mass Ejections and leads to geomagnetic storms with possible impacts on the infrastructures at Earth.…

Solar and Stellar Astrophysics · Physics 2025-10-03 Chiara Curletto , Paolo Massa , Valeria Tagliafico , Cristina Campi , Federico Benvenuto , Michele Piana , Andrea Tacchino

Photovoltaic (PV) power production increased drastically in Europe throughout the last years. About the 6% of electricity in Italy comes from PV and for an efficient management of the power grid an accurate and reliable forecasting of…

Machine Learning · Computer Science 2014-09-30 Matteo De Felice , Marcello Petitta , Paolo M. Ruti

The solar wind speed at Earth is one of the most important parameters regarding the effects of space weather on society. Thus far, most approaches for predicting the solar wind speed produce a single-value time series without uncertainty,…

Solar and Stellar Astrophysics · Physics 2026-03-13 Daniel E. da Silva , Yash Parlikar , Shaela I. Jones , Charles N. Arge

Solar flares, as one of the most prominent manifestations of solar activity, have a profound impact on both the Earth's space environment and human activities. As a result, accurate solar flare prediction has emerged as a central topic in…

Solar and Stellar Astrophysics · Physics 2026-03-31 Mingfu Shao , Suo Liu , Haiqing Xu , Peng Jia , Hui Wang , Liyue Tong , Yang Bai , Chen Yang , Yuyang Li , Nan Li , Jiaben Lin

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

Accurate forecasting of solar power output is essential for efficient integration of renewable energy into the grid. In this study, an attention-based deep learning model, inspired by transformer architecture, is used for short-term solar…

Machine Learning · Computer Science 2026-04-28 Ankan Basu , Jyotiraditya Roy , Aditya Datta , Prayas Sanyal , Sumanta Banerjee

For a Bayesian, real-time forecasting with the posterior predictive distribution can be challenging for a variety of time series models. First, estimating the parameters of a time series model can be difficult with sample-based approaches…

Applications · Statistics 2022-08-08 Taylor R. Brown

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

In this paper, we demonstrate the importance of embedding temporal information for an accurate prediction of solar irradiance. We have used two sets of models for forecasting solar irradiance. The first one uses only time series data of…

Solar and Stellar Astrophysics · Physics 2021-10-20 T. A. Fathima , Vasudevan Nedumpozhimana , Yee Hui Lee , Soumyabrata Dev

The future energy system will largely depend on volatile renewable energy sources and temperature-dependent loads, which makes the weather a central influencing factor. This article presents a novel approach for simulating weather scenarios…

Systems and Control · Electrical Eng. & Systems 2024-05-31 Jan Peper , David Kröger , Jonathan Kipp , Florian Ziel , Christian Rehtanz

Forecasting load at the feeder level has become increasingly challenging with the penetration of behind-the-meter solar, as this self-generation (also called total generation) is only visible to the utility as aggregated net-load. This work…

Signal Processing · Electrical Eng. & Systems 2024-03-11 Allison M. Campbell , Soumya Kundu , Andrew P. Reiman , Orestis Vasios , Ian Beil , Andy Eiden

As the US rapidly moves towards cleaner energy sources, solar energy is fast becoming the pillar of its renewable energy mix. Even while solar energy is increasingly being used, its variability is a key hindrance to grid stability, storage…

The non-stationarity characteristic of the solar power renders traditional point forecasting methods to be less useful due to large prediction errors. This results in increased uncertainties in the grid operation, thereby negatively…

Machine Learning · Computer Science 2020-09-15 Sakshi Mishra , Praveen Palanisamy

Short-term probabilistic wind power forecasting can provide critical quantified uncertainty information of wind generation for power system operation and control. As the complicated characteristics of wind power prediction error, it would…

Machine Learning · Computer Science 2017-02-14 You Lin , Ming Yang , Can Wan , Jianhui Wang , Yonghua Song

The planning and operation of renewable energy, especially wind power, depend crucially on accurate, timely, and high-resolution weather information. Coarse-grid global numerical weather forecasts are typically downscaled to meet these…

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

The increasing penetration of photovoltaic (PV) generation introduces significant uncertainty into power system operation, necessitating forecasting approaches that extend beyond deterministic point predictions. This paper proposes an…

Machine Learning · Computer Science 2026-02-06 Slawek Smyl , Paweł Pełka , Grzegorz Dudek

Wind energy plays an increasing role in the supply of energy world-wide. The energy output of a wind farm is highly dependent on the weather condition present at the wind farm. If the output can be predicted more accurately, energy…

Artificial Intelligence · Computer Science 2011-09-12 Katya Vladislavleva , Tobias Friedrich , Frank Neumann , Markus Wagner

Due to the rise in the use of renewable energies as an alternative to traditional ones, and especially solar energy, there is increasing interest in studying how to address photovoltaic forecasting in the face of the challenge of…

Computer Vision and Pattern Recognition · Computer Science 2026-02-18 Ines Montoya-Espinagosa , Antonio Agudo

Amongst all the renewable energy resources (RES), solar is the most popular form of energy source and is of particular interest for its widely integration into the power grid. However, due to the intermittent nature of solar source, it is…

Computer Vision and Pattern Recognition · Computer Science 2021-05-10 Ekanki Sharma , Wilfried Elmenreich