A robust auto encoder-gated recurrent unit (AE-GRU) based deep learning approach for short term solar power forecasting
The increasing presence of solar power plants shows its potency as one of the key
renewable energy resource to fulfill energy needs of the community. This increasing …
renewable energy resource to fulfill energy needs of the community. This increasing …
Differential attention net: Multi-directed differential attention based hybrid deep learning model for solar power forecasting
Solar power plants provide a clean alternative to conventional thermal power plants.
However, solar plant dependency on environmental factors threatens existing energy grids …
However, solar plant dependency on environmental factors threatens existing energy grids …
A novel forecasting model for solar power generation by a deep learning framework with data preprocessing and postprocessing
Photovoltaic power has become one of the most popular forms of energy owing to the
growing consideration of environmental factors; however, solar power generation has …
growing consideration of environmental factors; however, solar power generation has …
[PDF][PDF] Deep learning based models for solar energy prediction
I Jebli, FZ Belouadha, MI Kabbaj… - Advances in Science …, 2021 - academia.edu
Solar energy becomes widely used in the global power grid. Therefore, enhancing the
accuracy of solar energy predictions is essential for the efficient planning, managing and …
accuracy of solar energy predictions is essential for the efficient planning, managing and …
Short-term solar PV forecasting using gated recurrent unit with a cascade model
N Sodsong, KM Yu, W Ouyang - 2019 International Conference …, 2019 - ieeexplore.ieee.org
The fluctuation in solar photovoltaic (PV) generation system causes inefficiency in PV power
management. Thus, predicting solar PV power is essential to assist PV system in improving …
management. Thus, predicting solar PV power is essential to assist PV system in improving …
Evaluation of opaque deep-learning solar power forecast models towards power-grid applications
L Cheng, H Zang, Z Wei, F Zhang, G Sun - Renewable Energy, 2022 - Elsevier
Solar photovoltaic power plays a vital role in global renewable energy power generation,
and an accurate solar power forecast can further promote applications in integrated power …
and an accurate solar power forecast can further promote applications in integrated power …
A novel deep learning approach for short term photovoltaic power forecasting based on GRU-CNN model
M Sabri, M El Hassouni - E3S Web of Conferences, 2022 - e3s-conferences.org
The integration of photovoltaic power brings the key to clean energy. However, the
increasing proportion of photovoltaic (PV) energy in power systems due to the random and …
increasing proportion of photovoltaic (PV) energy in power systems due to the random and …
Short-term solar irradiance forecasting based on a hybrid deep learning methodology
K Yan, H Shen, L Wang, H Zhou, M Xu, Y Mo - Information, 2020 - mdpi.com
Accurate prediction of solar irradiance is beneficial in reducing energy waste associated
with photovoltaic power plants, preventing system damage caused by the severe fluctuation …
with photovoltaic power plants, preventing system damage caused by the severe fluctuation …
A review on deep learning models for forecasting time series data of solar irradiance and photovoltaic power
RA Rajagukguk, RAA Ramadhan, HJ Lee - Energies, 2020 - mdpi.com
Presently, deep learning models are an alternative solution for predicting solar energy
because of their accuracy. The present study reviews deep learning models for handling …
because of their accuracy. The present study reviews deep learning models for handling …
Hybrid deep learning models for time series forecasting of solar power
Forecasting solar power production accurately is critical for effectively planning and
managing renewable energy systems. This paper introduces and investigates novel hybrid …
managing renewable energy systems. This paper introduces and investigates novel hybrid …