[HTML][HTML] Comparison of machine learning methods for photovoltaic power forecasting based on numerical weather prediction

D Markovics, MJ Mayer - Renewable and Sustainable Energy Reviews, 2022 - Elsevier
The increase of the worldwide installed photovoltaic (PV) capacity and the intermittent
nature of the solar resource highlights the importance of power forecasting for the grid …

[HTML][HTML] A review of green artificial intelligence: Towards a more sustainable future

V Bolón-Canedo, L Morán-Fernández, B Cancela… - Neurocomputing, 2024 - Elsevier
Green artificial intelligence (AI) is more environmentally friendly and inclusive than
conventional AI, as it not only produces accurate results without increasing the …

COA-CNN-LSTM: Coati optimization algorithm-based hybrid deep learning model for PV/wind power forecasting in smart grid applications

M Abou Houran, SMS Bukhari, MH Zafar, M Mansoor… - Applied Energy, 2023 - Elsevier
Power prediction is now a crucial part of contemporary energy management systems, which
is important for the organization and administration of renewable resources. Solar and wind …

Recent advances in machine learning research for nanofluid-based heat transfer in renewable energy system

P Sharma, Z Said, A Kumar, S Nizetic, A Pandey… - Energy & …, 2022 - ACS Publications
Nanofluids have gained significant popularity in the field of sustainable and renewable
energy systems. The heat transfer capacity of the working fluid has a huge impact on the …

A hybrid framework for forecasting power generation of multiple renewable energy sources

J Zheng, J Du, B Wang, JJ Klemeš, Q Liao… - … and Sustainable Energy …, 2023 - Elsevier
The accurate power generation forecast of multiple renewable energy sources is significant
for the power scheduling of renewable energy systems. However, previous studies focused …

CNN-LSTM: An efficient hybrid deep learning architecture for predicting short-term photovoltaic power production

A Agga, A Abbou, M Labbadi, Y El Houm… - Electric Power Systems …, 2022 - Elsevier
Climate change is pushing an increasing number of nations to use green energy resources,
particularly solar power as an applicable substitute to traditional power sources. However …

Aligning artificial intelligence with climate change mitigation

LH Kaack, PL Donti, E Strubell, G Kamiya… - Nature Climate …, 2022 - nature.com
There is great interest in how the growth of artificial intelligence and machine learning may
affect global GHG emissions. However, such emissions impacts remain uncertain, owing in …

[HTML][HTML] Improved solar photovoltaic energy generation forecast using deep learning-based ensemble stacking approach

W Khan, S Walker, W Zeiler - Energy, 2022 - Elsevier
An accurate solar energy forecast is of utmost importance to allow a higher level of
integration of renewable energy into the controls of the existing electricity grid. With the …

A review of very short-term wind and solar power forecasting

R Tawn, J Browell - Renewable and Sustainable Energy Reviews, 2022 - Elsevier
Installed capacities of wind and solar power have grown rapidly over recent years, and the
pool of literature on very short-term (minutes-to hours-ahead) wind and solar forecasting has …

[HTML][HTML] Distributed energy systems: A review of classification, technologies, applications, and policies

TB Nadeem, M Siddiqui, M Khalid, M Asif - Energy Strategy Reviews, 2023 - Elsevier
The sustainable energy transition taking place in the 21st century requires a major
revam** of the energy sector. Improvements are required not only in terms of the …