Deep learning models for solar irradiance forecasting: A comprehensive review

P Kumari, D Toshniwal - Journal of Cleaner Production, 2021 - Elsevier
The growing human population in this modern society hugely depends on the energy to
fulfill their day-to-day needs and activities. Renewable energy sources, especially solar …

A review of deep learning for renewable energy forecasting

H Wang, Z Lei, X Zhang, B Zhou, J Peng - Energy Conversion and …, 2019 - Elsevier
As renewable energy becomes increasingly popular in the global electric energy grid,
improving the accuracy of renewable energy forecasting is critical to power system planning …

A synthesis of feasible control methods for floating offshore wind turbine system dynamics

KA Shah, F Meng, Y Li, R Nagamune, Y Zhou… - … and Sustainable Energy …, 2021 - Elsevier
During the past decade, the development of offshore wind energy has transitioned from near
shore with shallow water to offshore middle-depth water regions. Consequently, the energy …

Key technologies for smart energy systems: Recent developments, challenges, and research opportunities in the context of carbon neutrality

H Zhu, HH Goh, D Zhang, T Ahmad, H Liu… - Journal of Cleaner …, 2022 - Elsevier
Energy crisis and environmental pollution have expedited the transition of the energy
system. Global use of low-carbon energy has increased from 1: 6.16 to 1: 5.37. Smart energy …

Day-ahead electricity price prediction applying hybrid models of LSTM-based deep learning methods and feature selection algorithms under consideration of market …

W Li, DM Becker - Energy, 2021 - Elsevier
The availability of accurate day-ahead electricity price forecasts is pivotal for electricity
market participants. In the context of trade liberalisation and market harmonisation in the …

Dynamic ensemble deep echo state network for significant wave height forecasting

R Gao, R Li, M Hu, PN Suganthan, KF Yuen - Applied Energy, 2023 - Elsevier
Forecasts of the wave heights can assist in the data-driven control of wave energy systems.
However, the dynamic properties and extreme fluctuations of the historical observations …

[HTML][HTML] A review of point absorber wave energy converters

B Guo, T Wang, S Jin, S Duan, K Yang… - Journal of Marine Science …, 2022 - mdpi.com
There are more than thousands of concepts for harvesting wave energy, and wave energy
converters (WECs) are diverse in operating principles, design geometries and deployment …

[HTML][HTML] A review of machine learning and deep learning applications in wave energy forecasting and WEC optimization

A Shadmani, MR Nikoo, AH Gandomi, RQ Wang… - Energy Strategy …, 2023 - Elsevier
Ocean energy technologies are in their developmental stages, like other renewable energy
sources. To be useable in the energy market, most components of wave energy devices …

Review on deep learning research and applications in wind and wave energy

C Gu, H Li - Energies, 2022 - mdpi.com
Wind energy and wave energy are considered to have enormous potential as renewable
energy sources in the energy system to make great contributions in transitioning from fossil …

Wave power forecasting using an effective decomposition-based convolutional Bi-directional model with equilibrium Nelder-Mead optimiser

M Neshat, MM Nezhad, NY Sergiienko, S Mirjalili… - Energy, 2022 - Elsevier
Energy industries and governments consider ocean wave power a promising renewable
energy source for reaching the net-zero plan by 2050 and restricting the rise in global …