A comprehensive review on optimization of hybrid renewable energy systems using various optimization techniques

M Thirunavukkarasu, Y Sawle, H Lala - Renewable and Sustainable …, 2023 - Elsevier
The increasing energy prices and pollutants from fossil fuels that threaten the climate, there
is a growing preference for renewable energy. The implementation of hybrid renewable …

Machine learning and deep learning in energy systems: A review

MM Forootan, I Larki, R Zahedi, A Ahmadi - Sustainability, 2022 - mdpi.com
With population increases and a vital need for energy, energy systems play an important
and decisive role in all of the sectors of society. To accelerate the process and improve the …

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 …

An integrated framework of Bi-directional long-short term memory (BiLSTM) based on sine cosine algorithm for hourly solar radiation forecasting

T Peng, C Zhang, J Zhou, MS Nazir - Energy, 2021 - Elsevier
Accurate and reliable solar radiation forecasting is of great significance for the management
and utilization of solar energy. This study proposes a deep learning model based on Bi …

A review on global solar radiation prediction with machine learning models in a comprehensive perspective

Y Zhou, Y Liu, D Wang, X Liu, Y Wang - Energy Conversion and …, 2021 - Elsevier
Global solar radiation information is the basis for many solar energy utilizations as well as
for economic and environmental considerations. However, because solar-radiation …

Advanced ensemble model for solar radiation forecasting using sine cosine algorithm and newton's laws

ESM El-Kenawy, S Mirjalili, SSM Ghoneim… - IEEE …, 2021 - ieeexplore.ieee.org
As research in alternate energy sources is growing, solar radiation is catching the eyes of
the research community immensely. Since solar energy generation depends on …

A survey of machine learning models in renewable energy predictions

JP Lai, YM Chang, CH Chen, PF Pai - Applied Sciences, 2020 - mdpi.com
The use of renewable energy to reduce the effects of climate change and global warming
has become an increasing trend. In order to improve the prediction ability of renewable …

[HTML][HTML] Improving the thermal efficiency of a solar flat plate collector using MWCNT-Fe3O4/water hybrid nanofluids and ensemble machine learning

Z Said, P Sharma, LS Sundar, C Li, DC Tran… - Case Studies in Thermal …, 2022 - Elsevier
The thermal performance of a flat plate solar collector using MWCNT+ Fe 3 O 4/Water hybrid
nanofluids was examined in this research. The flat plate solar collector was tested using …

Light Gradient Boosting Machine: An efficient soft computing model for estimating daily reference evapotranspiration with local and external meteorological data

J Fan, X Ma, L Wu, F Zhang, X Yu, W Zeng - Agricultural water management, 2019 - Elsevier
Accurate estimation of reference evapotranspiration (ETo) is required in many fields, eg
irrigation scheduling design, agricultural water management, crop growth modeling and …

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 …