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Most solar applications and systems can be reliably used to generate electricity and power in many homes and offices. Recently, there is an increase in many solar required systems that can be found not only in electricity generation but…

Machine Learning · Computer Science 2021-04-07 Shahriar Rahman , Shazzadur Rahman , A K M Bahalul Haque

Among several heliophysical and geophysical quantities, the accurate evolution of the solar irradiance is fundamental to forecast the evolution of the neutral and ionized components of the Earth's atmosphere.We developed an artificial…

Solar and Stellar Astrophysics · Physics 2011-11-23 Luis Eduardo A. Vieira , Thierry Dudok de Wit , Matthieu Kretzschmar

Considering the grid manager's point of view, needs in terms of prediction of intermittent energy like the photovoltaic resource can be distinguished according to the considered horizon: following days (d+1, d+2 and d+3), next day by hourly…

Atmospheric and Oceanic Physics · Physics 2013-07-24 Cyril Voyant , Christophe Paoli , Marc Muselli , Marie Laure Nivet

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…

Neural and Evolutionary Computing · Computer Science 2013-08-19 Giacomo Capizzi , Christian Napoli , Francesco Bonanno

We propose in this paper an original technique to predict global radiation using a hybrid ARMA/ANN model and data issued from a numerical weather prediction model (ALADIN). We particularly look at the Multi-Layer Perceptron. After…

Neural and Evolutionary Computing · Computer Science 2012-01-10 Cyril Voyant , Marc Muselli , Christophe Paoli , Marie Laure Nivet

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 integration of renewable resources has increased in power generation as a means to reduce the fossil fuel usage and mitigate its adverse effects on the environment. However, renewables like solar energy are stochastic in nature due to…

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

The need to forecast solar irradiation at a specific location over short-time horizons has acquired immense importance. In this paper, we report on analyses results involving statistical and machine learning techniques to predict hourly…

Applications · Statistics 2017-08-29 Alireza Inanlougani , T. Agami Reddy , Srinivas Katiamula

Accurate mechanisms for forecasting solar irradiance and insolation provide important information for the planning of renewable energy and agriculture projects as well as for environmental and socio-economical studies. This research…

Machine Learning · Computer Science 2021-06-15 Laura S. Hoyos-Gómez , Jose F. Ruiz-Muñoz , Belizza J. Ruiz-Mendoza

Ahead-of-time forecasting of incident solar-irradiance on a panel is indicative of expected energy yield and is essential for efficient grid distribution and planning. Traditionally, these forecasts are based on meteorological physics…

Computer Vision and Pattern Recognition · Computer Science 2019-01-16 Talha A. Siddiqui , Samarth Bharadwaj , Shivkumar Kalyanaraman

We discuss a prediction of the solar activity on a short time-scale applying the method based on a combination of a nonlinear mean-field dynamo model and the artificial neural network. The artificial neural network which serves as a…

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

Regional solar power forecasting, which involves predicting the total power generation from all rooftop photovoltaic systems in a region holds significant importance for various stakeholders in the energy sector. However, the vast amount of…

Machine Learning · Computer Science 2024-03-05 Maneesha Perera , Julian De Hoog , Kasun Bandara , Damith Senanayake , Saman Halgamuge

When cloud layers cover photovoltaic (PV) panels, the amount of power the panels produce fluctuates rapidly. Therefore, to maintain enough energy on a power grid to match demand, utilities companies rely on reserve power sources that…

Smooth power generation from solar stations demand accurate, reliable and efficient forecast of solar energy for optimal integration to cater market demand; however, the implicit instability of solar energy production may cause serious…

Atmospheric and Oceanic Physics · Physics 2020-12-02 Farah Shahid , Aneela Zameer , Mudasser Afzal , Muhammad Hassan

The increasing global demand for clean and environmentally friendly energy resources has caused increased interest in harnessing solar power through photovoltaic (PV) systems for smart grids and homes. However, the inherent unpredictability…

Machine Learning · Computer Science 2023-10-24 Saman Soleymani , Shima Mohammadzadeh

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

It is essential to find solar predictive methods to massively insert renewable energies on the electrical distribution grid. The goal of this study is to find the best methodology allowing predicting with high accuracy the hourly global…

Machine Learning · Computer Science 2013-09-20 Cyril Voyant , C. Darras , Marc Muselli , Christophe Paoli , Marie Laure Nivet , Philippe Poggi

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
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