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 …
A review on renewable energy and electricity requirement forecasting models for smart grid and buildings
The benefits of renewable energy are that it is sustainable and is low in environmental
pollution. Growing load requirement, global warming, and energy crisis need energy …
pollution. Growing load requirement, global warming, and energy crisis need energy …
State of the art of machine learning models in energy systems, a systematic review
Machine learning (ML) models have been widely used in the modeling, design and
prediction in energy systems. During the past two decades, there has been a dramatic …
prediction in energy systems. During the past two decades, there has been a dramatic …
Fuzzy neural networks and neuro-fuzzy networks: A review the main techniques and applications used in the literature
PV de Campos Souza - Applied soft computing, 2020 - Elsevier
This paper presents a review of the central theories involved in hybrid models based on
fuzzy systems and artificial neural networks, mainly focused on supervised methods for …
fuzzy systems and artificial neural networks, mainly focused on supervised methods for …
A survey of machine learning models in renewable energy predictions
The use of renewable energy to reduce the effects of climate change and global warming
has become an increasing trend. In order to improve the prediction ability of renewable …
has become an increasing trend. In order to improve the prediction ability of renewable …
Dual stream network with attention mechanism for photovoltaic power forecasting
The operations of renewable power generation systems highly depend on precise
Photovoltaic (PV) power forecasting, providing significant economic, and environmental …
Photovoltaic (PV) power forecasting, providing significant economic, and environmental …
A review on resilience studies in active distribution systems
The world has been experiencing natural disasters and man-made attacks on power system
networks over the past few decades. These occurrences directly affect electricity …
networks over the past few decades. These occurrences directly affect electricity …
Deep belief network based k-means cluster approach for short-term wind power forecasting
K Wang, X Qi, H Liu, J Song - Energy, 2018 - Elsevier
Wind energy is the intermittent energy and its output has great volatility. How to accurately
predict wind power output is a problem that many researchers have been paying attention to …
predict wind power output is a problem that many researchers have been paying attention to …
Wind power generation: A review and a research agenda
SA Vargas, GRT Esteves, PM Maçaira… - Journal of Cleaner …, 2019 - Elsevier
The use of renewable energy resources, especially wind power, is receiving strong attention
from governments and private institutions, since it is considered one of the best and most …
from governments and private institutions, since it is considered one of the best and most …
Ensemble empirical mode decomposition based adaptive wavelet neural network method for wind speed prediction
Wind energy is one of the emerging sustainable sources of electricity. Wind is intermittent in
nature. The typical grid operation of wind energy is complex. The significance of wind …
nature. The typical grid operation of wind energy is complex. The significance of wind …