[HTML][HTML] A survey of artificial intelligence methods for renewable energy forecasting: Methodologies and insights
The efforts to revolutionize electric power generation and produce clean and sustainable
electricity have led to the exploration of renewable energy systems (RES). This form of …
electricity have led to the exploration of renewable energy systems (RES). This form of …
Completed review of various solar power forecasting techniques considering different viewpoints
Solar power has rapidly become an increasingly important energy source in many countries
over recent years; however, the intermittent nature of photovoltaic (PV) power generation …
over recent years; however, the intermittent nature of photovoltaic (PV) power generation …
Time series forecasting for hourly photovoltaic power using conditional generative adversarial network and Bi-LSTM
More and more photovoltaic (PV) power generation is incorporated into the grid. However,
the intermittence and fluctuation of solar energy have brought huge challenges to the safe …
the intermittence and fluctuation of solar energy have brought huge challenges to the safe …
A novel approach based on integration of convolutional neural networks and deep feature selection for short-term solar radiation forecasting
H Acikgoz - Applied Energy, 2022 - Elsevier
In this study, a novel deep solar forecasting approach is proposed based on the complete
ensemble empirical mode decomposition with adaptive noise (CEEMDAN), continuous …
ensemble empirical mode decomposition with adaptive noise (CEEMDAN), continuous …
LOWESS smoothing and Random Forest based GRU model: A short-term photovoltaic power generation forecasting method
Y Dai, Y Wang, M Leng, X Yang, Q Zhou - Energy, 2022 - Elsevier
Accurate prediction of photovoltaic power generation is vital to guarantee smooth operation
of power stations and ensure users' electricity consumption. As a good forecasting tool …
of power stations and ensure users' electricity consumption. As a good forecasting tool …
Computational solar energy–Ensemble learning methods for prediction of solar power generation based on meteorological parameters in Eastern India
The challenges in applications of solar energy lies in its intermittency and dependency on
meteorological parameters such as; solar radiation, ambient temperature, rainfall, wind …
meteorological parameters such as; solar radiation, ambient temperature, rainfall, wind …
Intermittent solar power hybrid forecasting system based on pattern recognition and feature extraction
Y Yu, T Niu, J Wang, H Jiang - Energy Conversion and Management, 2023 - Elsevier
Solar energy, with its abundance and accessibility, occupies an irreplaceable position in the
shift in global energy consumption patterns. The difficulties of managing solar energy on the …
shift in global energy consumption patterns. The difficulties of managing solar energy on the …
[HTML][HTML] Forecasting solar photovoltaic power production: A comprehensive review and innovative data-driven modeling framework
The intermittent and stochastic nature of Renewable Energy Sources (RESs) necessitates
accurate power production prediction for effective scheduling and grid management. This …
accurate power production prediction for effective scheduling and grid management. This …
Privacy-preserving federated learning: Application to behind-the-meter solar photovoltaic generation forecasting
The growing usage of decentralized renewable energy sources has made accurate
estimation of their aggregated generation crucial for maintaining grid flexibility and reliability …
estimation of their aggregated generation crucial for maintaining grid flexibility and reliability …
Artificial neural networks for photovoltaic power forecasting: a review of five promising models
Solar energy is largely dependent on weather conditions, resulting in unpredictable,
fluctuating, and unstable photovoltaic (PV) power outputs. Thus, accurate PV power …
fluctuating, and unstable photovoltaic (PV) power outputs. Thus, accurate PV power …