Machine learning approaches to predict electricity production from renewable energy sources
Bearing in mind European Green Deal assumptions regarding a significant reduction of
green house emissions, electricity generation from Renewable Energy Sources (RES) is …
green house emissions, electricity generation from Renewable Energy Sources (RES) is …
A day-ahead photovoltaic power prediction via transfer learning and deep neural networks
Climate change and global warming drive many governments and scientists to investigate
new renewable and green energy sources. Special attention is on solar panel technology …
new renewable and green energy sources. Special attention is on solar panel technology …
Machine learning for performance prediction in smart buildings: Photovoltaic self-consumption and life cycle cost optimization
The application of Photovoltaic (PV) system in buildings is growing rapidly in response to the
need for clean energy sources and building decarbonization targets. Nonetheless …
need for clean energy sources and building decarbonization targets. Nonetheless …
Application of deep learning to the prediction of solar irradiance through missing data
R Girimurugan, P Selvaraju… - International Journal …, 2023 - Wiley Online Library
The task of predicting solar irradiance is critical in the development of renewable energy
sources. This research is aimed at predicting the photovoltaic plant's irradiance or power …
sources. This research is aimed at predicting the photovoltaic plant's irradiance or power …
Short-term solar irradiance forecasting in streaming with deep learning
Solar energy is one of the most common and promising sources of renewable energy. In
photovoltaic (PV) systems, operators can benefit from future solar irradiance predictions for …
photovoltaic (PV) systems, operators can benefit from future solar irradiance predictions for …
Photovoltaic power prediction for solar micro-grid optimal control
In a solar micro-grid, a hybrid renewable energy system generates electricity for a building's
onsite use. The battery storage and the main power grid connection are used to facilitate the …
onsite use. The battery storage and the main power grid connection are used to facilitate the …
Research on a novel photovoltaic power forecasting model based on parallel long and short-term time series network
G Li, C Ding, N Zhao, J Wei, Y Guo, C Meng, K Huang… - Energy, 2024 - Elsevier
Under the background of the global pursuit of carbon neutrality, the trend of photovoltaic
power generation replacing traditional thermal power generation is increasingly apparent …
power generation replacing traditional thermal power generation is increasingly apparent …
Short-term photovoltaic power production forecasting based on novel hybrid data-driven models
M Alrashidi, S Rahman - Journal of Big Data, 2023 - Springer
The uncertainty associated with photovoltaic (PV) systems is one of the core obstacles that
hinder their seamless integration into power systems. The fluctuation, which is influenced by …
hinder their seamless integration into power systems. The fluctuation, which is influenced by …
A Quasi oppositional smell agent optimization and its levy flight variant: A PV/Wind/battery system optimization application
In this study, two novel algorithms are developed: the quasi-oppositional smell agent
optimization (QOBL-SAO) and its levy flight variation (LFQOBL-SAO), and their performance …
optimization (QOBL-SAO) and its levy flight variation (LFQOBL-SAO), and their performance …
A short-term forecasting method for photovoltaic power generation based on the TCN-ECANet-GRU hybrid model
X Xiang, X Li, Y Zhang, J Hu - Scientific Reports, 2024 - nature.com
Due to the uncertainty of weather conditions and the nonlinearity of high-dimensional data,
as well as the need for a continuous and stable power supply to the power system …
as well as the need for a continuous and stable power supply to the power system …