Using machine learning in photovoltaics to create smarter and cleaner energy generation systems: A comprehensive review
Photovoltaic (PV) technologies are expected to play an increasingly important role in future
energy production. In parallel, machine learning has gained prominence because of a …
energy production. In parallel, machine learning has gained prominence because of a …
Predicting surface solar radiation using a hybrid radiative Transfer–Machine learning model
Solar radiation is one of the cleanest sources of renewable energy, and it affects the carbon
sink functions of terrestrial ecosystems. Although efforts have been made to establish solar …
sink functions of terrestrial ecosystems. Although efforts have been made to establish solar …
Automated deep CNN-LSTM architecture design for solar irradiance forecasting
SMJ Jalali, S Ahmadian, A Kavousi-Fard… - … on Systems, Man …, 2021 - ieeexplore.ieee.org
Accurate prediction of solar energy is an important issue for photovoltaic power plants to
enable early participation in energy auction industries and cost-effective resource planning …
enable early participation in energy auction industries and cost-effective resource planning …
Hybrid prediction method of solar irradiance applied to short-term photovoltaic energy generation
One of the most promising renewable energy sources used as a solution to supply the
increase in electricity consumption is photovoltaic solar energy. This source has intrinsic and …
increase in electricity consumption is photovoltaic solar energy. This source has intrinsic and …
A taxonomical review on recent artificial intelligence applications to PV integration into power grids
The exponential growth of solar power has been witnessed in the past decade and is
projected by the ambitious policy targets. Nevertheless, the proliferation of solar energy …
projected by the ambitious policy targets. Nevertheless, the proliferation of solar energy …
Solar irradiance forecasting to short-term PV power: Accuracy comparison of ann and LSTM models
VH Wentz, JN Maciel, JJ Gimenez Ledesma… - Energies, 2022 - mdpi.com
The use of renewable energies, such as Photovoltaic (PV) solar power, is necessary to meet
the growing energy consumption. PV solar power generation has intrinsic characteristics …
the growing energy consumption. PV solar power generation has intrinsic characteristics …
Effect of feature selection on the prediction of direct normal irradiance
Solar radiation is capable of producing heat, causing chemical reactions, or generating
electricity. Thus, the amount of solar radiation at different times of the day must be …
electricity. Thus, the amount of solar radiation at different times of the day must be …
Arithmetic optimization with hybrid deep learning algorithm based solar radiation prediction model
Solar radiation affects extreme weather occurrences, as well as on the temperature and
mean sea level. Therefore, precise studies and measurements of geographical and …
mean sea level. Therefore, precise studies and measurements of geographical and …
Forecasting Solar Power Output Generation: A Systematic Review with the Proknow-C
JN Maciel, JJG Ledesma… - IEEE Latin America …, 2021 - ieeexplore.ieee.org
This paper presents a systematic review of the solar output power generation forecasting
using the Proknow-C methodology for the development of a bibliographic portfolio which …
using the Proknow-C methodology for the development of a bibliographic portfolio which …
Prediction of solar irradiance using convolutional neural network and attention mechanism-based long short-term memory network based on similar day analysis and …
X Hou, C Ju, B Wang - Heliyon, 2023 - cell.com
As one of the future's most promising clean energy sources, solar energy is the key to
developing renewable energy. The randomness of solar irradiance can affect the efficiency …
developing renewable energy. The randomness of solar irradiance can affect the efficiency …