Deep learning models for solar irradiance forecasting: A comprehensive review

P Kumari, D Toshniwal - Journal of Cleaner Production, 2021 - Elsevier
The growing human population in this modern society hugely depends on the energy to
fulfill their day-to-day needs and activities. Renewable energy sources, especially solar …

[HTML][HTML] A review on neural network based models for short term solar irradiance forecasting

AM Assaf, H Haron, HN Abdull Hamed, FA Ghaleb… - Applied Sciences, 2023 - mdpi.com
The accuracy of solar energy forecasting is critical for power system planning, management,
and operation in the global electric energy grid. Therefore, it is crucial to ensure a constant …

Efficient daily solar radiation prediction with deep learning 4-phase convolutional neural network, dual stage stacked regression and support vector machine CNN …

S Ghimire, T Nguyen-Huy, RC Deo… - Sustainable Materials …, 2022 - Elsevier
Optimal utilisation of the sun's freely available energy to generate electricity requires efficient
predictive models of global solar radiation (GSR). These are necessary to provide solar …

[HTML][HTML] Solar irradiance prediction using reinforcement learning pre-trained with limited historical data

BK Jeon, EJ Kim - Energy Reports, 2023 - Elsevier
Accurate day-ahead forecasting of solar irradiance is crucial for maintaining a steady power
supply and minimizing energy losses. To date, various solar irradiance prediction models …

A systematic study on sha** the future of solar prosumage using deep learning

M Dodiya, M Shah - International Journal of Energy and Water Resources, 2021 - Springer
One of the core necessities for development in the modern world is a clear access to energy.
Therefore, places that lack access to energy face serious challenges on their ability to …

The Influence of Air Pollution Concentrations on Solar Irradiance Forecasting Using CNN-LSTM-mRMR Feature Extraction.

RG Birdal - Computers, Materials & Continua, 2024 - search.ebscohost.com
Maintaining a steady power supply requires accurate forecasting of solar irradiance, since
clean energy resources do not provide steady power. The existing forecasting studies have …

Predictive analytics in future power systems: A panorama and state-of-the-art of deep learning applications

S Mishra, A Glaws, P Palanisamy - Optimization, learning, and control for …, 2020 - Springer
The challenges surrounding the optimal operation of power systems are growing in various
dimensions, due in part to increasingly distributed energy resources and a progression …

Intra-hour solar irradiance forecasting: An end-to-end Transformer-based network

K Song, K Wang, S Wang, N Wang… - 2024 39th Youth …, 2024 - ieeexplore.ieee.org
The exponential growth of photovoltaic (PV) power generation prompts accurate PV
forecasting due to the nature of PV power fluctuations. Cloud movements have a significant …

[PDF][PDF] Energy Reports

BK Jeon, EJ Kim - 2023 - researchgate.net
abstract Accurate day-ahead forecasting of solar irradiance is crucial for maintaining a
steady power supply and minimizing energy losses. To date, various solar irradiance …

Classification Machine Learning Applications for Energy Management Systems in Distribution Systems to Diminish CO2 Emissions

JR Lopez, P Ponce, A Molina - What AI Can Do: Strengths and …, 2023 - api.taylorfrancis.com
It is known that the increment of greenhouse gas emissions is one of the main factors behind
the global warming phenomenon. Global warming is a heavy influence to abnormal …