Related papers: Deep Learning Based Reconstruction of Total Solar …
We present a reconstruction of total solar irradiance since 1610 to the present based on variations of the surface distribution of the solar magnetic field. The latter is calculated from the historical record of the Group sunspot number…
Solar radiation prediction is an important challenge for the electrical engineer because it is used to estimate the power developed by commercial photovoltaic modules. This paper deals with the problem of solar radiation prediction based on…
A novel method for real-time solar generation forecast using weather data, while exploiting both spatial and temporal structural dependencies is proposed. The network observed over time is projected to a lower-dimensional representation…
Traditional solar forecasting models are based on several years of site-specific historical irradiance data, often spanning five or more years, which are unavailable for newer photovoltaic farms. As renewable energy is highly intermittent,…
The Sun has long been considered a constant star, to the extent that its total irradiance was termed the solar constant. It required radiometers in space to detect the small variations in solar irradiance on timescales of the solar rotation…
Flares are powerful energy releases occurring in stellar atmospheres. Solar flares, the most intense energy bursts in the solar system, are however hardly noticeable in the total solar luminosity. Consequently, the total amount of energy…
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…
Solar energy has the potential to become the backbone energy source for the world. Utility scale solar power plants (more than 50 MW) could have more than 100K individual solar modules and be spread over more than 200 acres of land.…
The application of machine learning in solar physics has the potential to greatly enhance our understanding of the complex processes that take place in the atmosphere of the Sun. By using techniques such as deep learning, we are now in the…
Variations of the solar UV irradiance are an important driver of chemical and physical processes in the Earth's upper atmosphere and may also influence global climate. Here we reconstruct solar UV irradiance in the range 115-400 nm over the…
The sunspot number (SSN), the total solar irradiance (TSI), a TSI reconstruction, and the solar flare index (SFI), are analyzed for long-range persistence (LRP). Standard Hurst analysis yields $H \approx 0.9$, which suggests strong LRP.…
Foundation models have demonstrated remarkable success across various scientific domains, motivating our exploration of their potential in solar physics. In this paper, we present Solaris, the first foundation model for forecasting the…
In this letter, we explore the relationship between the solar seismic radius and total solar irradiance (TSI) during last two solar cycles using the uninterrupted data from space-borne instruments onboard {\it SoHO} and {\it SDO}. The…
Ground-based solar image restoration is a computationally expensive procedure that involves nonlinear optimization techniques. The presence of atmospheric turbulence produces perturbations in individual images that make it necessary to…
Structures in the solar corona are the main drivers of space weather processes that might directly or indirectly affect the Earth. Thanks to the most recent space-based solar observatories, with capabilities to acquire high-resolution…
Solar forecasting from ground-based sky images has shown great promise in reducing the uncertainty in solar power generation. With more and more sky image datasets open sourced in recent years, the development of accurate and reliable deep…
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…
Non-availability of reliable and sustainable electric power is a major problem in the developing world. Renewable energy sources like solar are not very lucrative in the current stage due to various uncertainties like weather, storage, land…
The Sun is a powerful neutrino source that can be used to study the physical properties of neutrinos and, at the same time, neutrinos are a unique tool to probe the interior of the Sun. For these reasons, solar neutrino physics is both…
Context. Total solar irradiance allows for the use of the Sun as a star for studying observations of stellar light curves from recent space missions. Aims. We aim to study how the mid-range periodicity observed in solar activity indices…