Artificial intelligence and numerical models in hybrid renewable energy systems with fuel cells: Advances and prospects

A Al-Othman, M Tawalbeh, R Martis, S Dhou… - Energy Conversion and …, 2022 - Elsevier
With the rapid advancement of technology in the energy sector and the demand for
sustainable energy practices, the world is aiming at fostering the hydrogen economy and …

A comprehensive review on deep learning approaches in wind forecasting applications

Z Wu, G Luo, Z Yang, Y Guo, K Li… - CAAI Transactions on …, 2022 - Wiley Online Library
The effective use of wind energy is an essential part of the sustainable development of
human society, in particular, at the recent unprecedented pressure in shaping a low carbon …

Point and interval forecasting of ultra-short-term wind power based on a data-driven method and hybrid deep learning model

D Niu, L Sun, M Yu, K Wang - Energy, 2022 - Elsevier
Accurate and reliable wind power forecasting (WPF) is significant for ensuring power
systems' economic operation and safe dispatching and for reducing the technical and …

A combined forecasting system based on statistical method, artificial neural networks, and deep learning methods for short-term wind speed forecasting

P Jiang, Z Liu, X Niu, L Zhang - Energy, 2021 - Elsevier
Wind speed forecasting is gaining importance as the share of wind energy in electricity
systems increases. Numerous forecasting approaches have been used to predict wind …

Ensemble forecasting system for short-term wind speed forecasting based on optimal sub-model selection and multi-objective version of mayfly optimization algorithm

Z Liu, P Jiang, J Wang, L Zhang - Expert Systems with Applications, 2021 - Elsevier
Wind energy has attracted considerable attention in the past decades as a low-carbon,
environmentally friendly, and efficient renewable energy. However, the irregularity of wind …

A combined forecasting model for time series: Application to short-term wind speed forecasting

Z Liu, P Jiang, L Zhang, X Niu - Applied Energy, 2020 - Elsevier
Wind speed forecasting has been growing in popularity, owing to the increased demand for
wind power electricity generation and developments in wind energy competitiveness. Many …

A new short-term wind speed forecasting method based on fine-tuned LSTM neural network and optimal input sets

G Memarzadeh, F Keynia - Energy Conversion and Management, 2020 - Elsevier
In recent years, clean energies, such as wind power have been developed rapidly.
Especially, wind power generation becomes a significant source of energy in some power …

A novel machine learning-based electricity price forecasting model based on optimal model selection strategy

W Yang, S Sun, Y Hao, S Wang - Energy, 2022 - Elsevier
Current electricity price forecasting models rely on only simple hybridizations of data
preprocessing and optimization methods while ignoring the significance of adaptive data …

Knowledge structure and research progress in wind power generation (WPG) from 2005 to 2020 using CiteSpace based scientometric analysis

A Azam, A Ahmed, H Wang, Y Wang… - Journal of Cleaner …, 2021 - Elsevier
Renewable energy resources have enabled the mitigation of global environmental pollution
and sustainable energy generation. Due to renewability, cleanliness, and vast sustainability …

Ensemble wind speed forecasting with multi-objective Archimedes optimization algorithm and sub-model selection

L Zhang, J Wang, X Niu, Z Liu - Applied Energy, 2021 - Elsevier
Wind energy is becoming increasingly competitive and promising for renewable energy
profiles. Accurate and reliable wind speed prediction is crucial for the effective exploitation of …