A review of wind speed and wind power forecasting with deep neural networks
The use of wind power, a pollution-free and renewable form of energy, to generate electricity
has attracted increasing attention. However, intermittent electricity generation resulting from …
has attracted increasing attention. However, intermittent electricity generation resulting from …
A review and evaluation of the state-of-the-art in PV solar power forecasting: Techniques and optimization
Integration of photovoltaics into power grids is difficult as solar energy is highly dependent
on climate and geography; often fluctuating erratically. This causes penetrations and voltage …
on climate and geography; often fluctuating erratically. This causes penetrations and voltage …
A review of deep learning with special emphasis on architectures, applications and recent trends
Deep learning (DL) has solved a problem that a few years ago was thought to be intractable—
the automatic recognition of patterns in spatial and temporal data with an accuracy superior …
the automatic recognition of patterns in spatial and temporal data with an accuracy superior …
Review of meta-heuristic algorithms for wind power prediction: Methodologies, applications and challenges
The integration of large-scale wind power introduces issues in modern power systems
operations due to its strong randomness and volatility. These issues can be resolved via …
operations due to its strong randomness and volatility. These issues can be resolved via …
Wind power forecasting using attention-based gated recurrent unit network
Wind power forecasting (WPF) plays an increasingly essential role in power system
operations. So far, most forecasting models have focused on a single-step-ahead WPF, and …
operations. So far, most forecasting models have focused on a single-step-ahead WPF, and …
A review and discussion of decomposition-based hybrid models for wind energy forecasting applications
With the continuous growth of wind power integration into the electrical grid, accurate wind
power forecasting is an important component in management and operation of power …
power forecasting is an important component in management and operation of power …
A review on the selected applications of forecasting models in renewable power systems
This paper presents a literature review on the selected applications of renewable resource
and power forecasting models to facilitate the optimal integration of renewable energy (RE) …
and power forecasting models to facilitate the optimal integration of renewable energy (RE) …
Wind power prediction using deep neural network based meta regression and transfer learning
An innovative short term wind power prediction system is proposed which exploits the
learning ability of deep neural network based ensemble technique and the concept of …
learning ability of deep neural network based ensemble technique and the concept of …
Hour-ahead wind power forecast based on random forests
Due to its chaotic nature, the wind behavior is difficult to forecast. Predicting wind power is a
real challenge for dispatchers who need to estimate renewable generation in advance to …
real challenge for dispatchers who need to estimate renewable generation in advance to …
A new wind power prediction method based on ridgelet transforms, hybrid feature selection and closed-loop forecasting
H Leng, X Li, J Zhu, H Tang, Z Zhang… - Advanced Engineering …, 2018 - Elsevier
To reduce network integration and boost energy trading, wind power forecasting can play an
important role in power systems. Furthermore, the uncertain and nonconvex behavior of …
important role in power systems. Furthermore, the uncertain and nonconvex behavior of …