A review of deep learning for renewable energy forecasting
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 …
improving the accuracy of renewable energy forecasting is critical to power system planning …
Deep learning models for solar irradiance forecasting: A comprehensive review
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 …
fulfill their day-to-day needs and activities. Renewable energy sources, especially solar …
A synthesis of feasible control methods for floating offshore wind turbine system dynamics
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 …
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
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 …
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 …
market participants. In the context of trade liberalisation and market harmonisation in the …
Dynamic ensemble deep echo state network for significant wave height forecasting
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 …
However, the dynamic properties and extreme fluctuations of the historical observations …
[HTML][HTML] A review of machine learning and deep learning applications in wave energy forecasting and WEC optimization
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 …
sources. To be useable in the energy market, most components of wave energy devices …
[HTML][HTML] A review of point absorber wave energy converters
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 …
converters (WECs) are diverse in operating principles, design geometries and deployment …
Review on deep learning research and applications in wind and wave energy
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 …
energy sources in the energy system to make great contributions in transitioning from fossil …
[HTML][HTML] Applications of machine learning to water resources management: A review of present status and future opportunities
Water is the most valuable natural resource on earth that plays a critical role in the socio-
economic development of humans worldwide. Water is used for various purposes, including …
economic development of humans worldwide. Water is used for various purposes, including …