Multi-scale solar radiation and photovoltaic power forecasting with machine learning algorithms in urban environment: A state-of-the-art review

J Tian, R Ooka, D Lee - Journal of Cleaner Production, 2023 - Elsevier
Solar energy has been rapidly utilized in urban environments owing to its significant
potential to fulfill the energy demand. The precise forecasting of solar energy, including solar …

A state of art review on estimation of solar radiation with various models

AE Gürel, Ü Ağbulut, H Bakır, A Ergün, G Yıldız - Heliyon, 2023 - cell.com
Solar radiation is free, and very useful input for most sectors such as heat, health, tourism,
agriculture, and energy production, and it plays a critical role in the sustainability of …

[HTML][HTML] Application of improved version of multi verse optimizer algorithm for modeling solar radiation

RMA Ikram, HL Dai, AA Ewees, J Shiri, O Kisi… - Energy Reports, 2022 - Elsevier
For better estimation of renewable environmental friendly and carbon-free energy resources,
precise prediction of solar energy is very essential. However, accurate prediction of solar …

Improving the accuracy of daily solar radiation prediction by climatic data using an efficient hybrid deep learning model: Long short-term memory (LSTM) network …

M Alizamir, J Shiri, AF Fard, S Kim, ARD Gorgij… - … Applications of Artificial …, 2023 - Elsevier
Accurate daily solar radiation prediction is a crucial task for the management and generation
of solar energy as one of the alternatives to fossil fuels. In this study, the prediction accuracy …

A novel machine learning approach for solar radiation estimation

H Hissou, S Benkirane, A Guezzaz, M Azrour… - Sustainability, 2023 - mdpi.com
Solar irradiation (Rs) is the electromagnetic radiation energy emitted by the Sun. It plays a
crucial role in sustaining life on Earth by providing light, heat, and energy. Furthermore, it …

[HTML][HTML] Forecasting solar energy production: A comparative study of machine learning algorithms

Y Ledmaoui, A El Maghraoui, M El Aroussi, R Saadane… - Energy Reports, 2023 - Elsevier
The use of solar energy has been rapidly expanding as a clean and renewable energy
source, with the installation of photovoltaic panels on homes, businesses, and large-scale …

An enhanced monthly runoff time series prediction using extreme learning machine optimized by salp swarm algorithm based on time varying filtering based empirical …

W Wang, Q Cheng, K Chau, H Hu, H Zang, D Xu - Journal of Hydrology, 2023 - Elsevier
Reliable runoff prediction plays a significant role in reservoir scheduling, water resources
management, and efficient utilization of water resources. To effectively enhance the …

Improving solar PV prediction performance with RF-CatBoost ensemble: a robust and complementary approach

R Banik, A Biswas - Renewable Energy Focus, 2023 - Elsevier
Although solar energy is renewable, environmental conditions can make it unpredictable,
which makes it difficult to maintain a consistent supply of electricity. Accurate solar forecast …

[HTML][HTML] Optimization and analysis of bioenergy production using machine learning modeling: Multi-layer perceptron, Gaussian processes regression, K-nearest …

H Jin, YG Kim, Z Jin, AA Rushchitc, AS Al-Shati - Energy Reports, 2022 - Elsevier
Since fossil fuels are slowly depleting, bio and renewable energies are now given more
attention. The main purpose of this research is to investigate and optimize the influencing …

Solar flat plate collector's heat transfer enhancement using grooved tube configuration with alumina nanofluids: Prediction of outcomes through artificial neural …

L Chilambarasan, V Thangarasu, P Ramasamy - Energy, 2024 - Elsevier
Solar thermal systems are far more important than solar PV systems in residential and
commercial applications. Improving the efficiency of solar thermal technology is a major …