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 …

Forecasting renewable energy generation with machine learning and deep learning: Current advances and future prospects

NE Benti, MD Chaka, AG Semie - Sustainability, 2023 - mdpi.com
This article presents a review of current advances and prospects in the field of forecasting
renewable energy generation using machine learning (ML) and deep learning (DL) …

A novel bio-inspired optimization algorithm design for wind power engineering applications time-series forecasting

FK Karim, DS Khafaga, MM Eid, SK Towfek… - Biomimetics, 2023 - mdpi.com
Wind patterns can change due to climate change, causing more storms, hurricanes, and
quiet spells. These changes can dramatically affect wind power system performance and …

Application of hybrid model based on empirical mode decomposition, novel recurrent neural networks and the ARIMA to wind speed prediction

MD Liu, L Ding, YL Bai - Energy Conversion and Management, 2021 - Elsevier
Wind speed is the key factor of wind power generation. With the increase of the proportion of
wind power generation in total power generation, the accurate prediction of wind speeds …

[HTML][HTML] Optimized ensemble model for wind power forecasting using hybrid whale and dipper-throated optimization algorithms

AA Alhussan, AK Farhan, AA Abdelhamid… - Frontiers in Energy …, 2023 - frontiersin.org
Introduction: Power generated by the wind is a viable renewable energy option. Forecasting
wind power generation is particularly important for easing supply and demand imbalances …

Integrated framework of extreme learning machine (ELM) based on improved atom search optimization for short-term wind speed prediction

L Hua, C Zhang, T Peng, C Ji, MS Nazir - Energy Conversion and …, 2022 - Elsevier
Wind energy plays an important role in terms of renewable energy. Accurate and reliable
wind speed prediction is essential for effective use of wind energy. However, the uncertainty …

Machine-learning predictions of solubility and residual trapping indexes of carbon dioxide from global geological storage sites

S Davoodi, HV Thanh, DA Wood, M Mehrad… - Expert Systems with …, 2023 - Elsevier
Ongoing anthropogenic carbon dioxide (CO 2) emissions to the atmosphere cause severe
air pollution that leads to complex changes in the climate, which pose threats to human life …

A novel decomposition-ensemble prediction model for ultra-short-term wind speed

Z Tian, H Chen - Energy Conversion and Management, 2021 - Elsevier
Accurate ultra-short-term wind speed prediction is of great significance to the power
generation efficiency of wind farms, and also has a good application prospect in the field of …

Multi-step short-term wind speed forecasting based on multi-stage decomposition coupled with stacking-ensemble learning approach

RG da Silva, SR Moreno, MHDM Ribeiro… - International Journal of …, 2022 - Elsevier
Wind energy is an emerging source of renewable energy in Brazil. Nevertheless, it already
accounts for 17% of the National Interconnected Network. Due to the great intricacy of wind …

Hybridization of hybrid structures for time series forecasting: A review

Z Hajirahimi, M Khashei - Artificial Intelligence Review, 2023 - Springer
Achieving the desired accuracy in time series forecasting has become a binding domain,
and developing a forecasting framework with a high degree of accuracy is one of the most …