A two-layer nonlinear combination method for short-term wind speed prediction based on ELM, ENN, and LSTM
As a typical kind of the Internet of Things, smart grid has attracted a lot of attentions. The
power energy management of smart grid is of great importance for energy distribution …
power energy management of smart grid is of great importance for energy distribution …
Short-term wind speed forecasting via stacked extreme learning machine with generalized correntropy
Recently, wind speed forecasting as an effective computing technique plays an important
role in advancing industry informatics, while dealing with these issues of control and …
role in advancing industry informatics, while dealing with these issues of control and …
A nonlinear hybrid wind speed forecasting model using LSTM network, hysteretic ELM and Differential Evolution algorithm
YL Hu, L Chen - Energy conversion and management, 2018 - Elsevier
Accurate and stable wind speed forecasting is essential for the planning, scheduling and
control of wind energy generation and conversion in wind power industry. In this paper, a …
control of wind energy generation and conversion in wind power industry. In this paper, a …
A novel non-linear combination system for short-term wind speed forecast
J Wang, S Wang, W Yang - Renewable Energy, 2019 - Elsevier
As an important clean energy source, wind power has strong influence on the safe operation
of the power grid. Because its output depends directly on the wind speed, it is of great …
of the power grid. Because its output depends directly on the wind speed, it is of great …
Wind speed forecasting using nonlinear-learning ensemble of deep learning time series prediction and extremal optimization
As an essential issue in wind energy industry, wind speed forecasting plays a vital role in
optimal scheduling and control of wind energy generation and conversion. In this paper, a …
optimal scheduling and control of wind energy generation and conversion. In this paper, a …
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 …
Especially, wind power generation becomes a significant source of energy in some power …
A novel combined forecasting model based on neural networks, deep learning approaches, and multi-objective optimization for short-term wind speed forecasting
J Wang, Y An, Z Li, H Lu - Energy, 2022 - Elsevier
Accurate wind speed prediction has become increasingly important in wind power
generation. However, the lack of efficient data preprocessing techniques and integration …
generation. However, the lack of efficient data preprocessing techniques and integration …
Wind speed prediction using hybrid 1D CNN and BLSTM network
As the world witnesses population increase, the global power demand is increasing and the
need for exploring other alternative clean and self-renewable sources of energy such as …
need for exploring other alternative clean and self-renewable sources of energy such as …
Short-term wind speed prediction based on improved PSO algorithm optimized EM-ELM
Z Tian, Y Ren, G Wang - … Sources, Part A: Recovery, Utilization, and …, 2019 - Taylor & Francis
Short-term wind speed prediction is of importance for power grids. It can mitigate the
disadvantageous impacts of wind farms on power systems and enhance the …
disadvantageous impacts of wind farms on power systems and enhance the …
A self-adaptive hybrid approach for wind speed forecasting
J Wang, J Hu, K Ma, Y Zhang - Renewable Energy, 2015 - Elsevier
Wind power, as a promising renewable energy source, has environmental benefits, as well
as economic and social ones. To evaluate wind energy properly and efficiently, this study …
as economic and social ones. To evaluate wind energy properly and efficiently, this study …