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 …
25 years of particle swarm optimization: Flourishing voyage of two decades
From the past few decades many nature inspired algorithms have been developed and
gaining more popularity because of their effectiveness in solving problems of distinct …
gaining more popularity because of their effectiveness in solving problems of distinct …
Decomposition-based hybrid wind speed forecasting model using deep bidirectional LSTM networks
KU Jaseena, BC Kovoor - Energy Conversion and Management, 2021 - Elsevier
The goal of sustainable development can be attained by the efficient management of
renewable energy resources. Wind energy is attracting attention worldwide due to its …
renewable energy resources. Wind energy is attracting attention worldwide due to its …
A combined forecasting system based on statistical method, artificial neural networks, and deep learning methods for short-term wind speed forecasting
Wind speed forecasting is gaining importance as the share of wind energy in electricity
systems increases. Numerous forecasting approaches have been used to predict wind …
systems increases. Numerous forecasting approaches have been used to predict wind …
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 …
A review on multi-objective optimization framework in wind energy forecasting techniques and applications
Wind energy is renewable and clean energy. To improve the utilization efficiency of the wind
energy, studies on wind energy forecasting have gradually been developed in recent years …
energy, studies on wind energy forecasting have gradually been developed in recent years …
A new hybrid ensemble deep reinforcement learning model for wind speed short term forecasting
Wind speed forecasting is a promising solution to improve the efficiency of energy utilization.
In this study, a novel hybrid wind speed forecasting model is proposed. The whole modeling …
In this study, a novel hybrid wind speed forecasting model is proposed. The whole modeling …
A comprehensive wind speed prediction system based on Monte Carlo and artificial intelligence algorithms
Y Zhang, Y Zhao, X Shen, J Zhang - Applied Energy, 2022 - Elsevier
Wind energy has strong volatility and intermittent. Accurate wind speed prediction can not
only improve the safety of the system, but also optimize dispatch and reduce economic …
only improve the safety of the system, but also optimize dispatch and reduce economic …
Effective wind power prediction using novel deep learning network: Stacked independently recurrent autoencoder
Accurate wind power prediction can improve the safety and reliability of power grid
operation. In this study, a novel deep learning network stacked by independent recurrent …
operation. In this study, a novel deep learning network stacked by independent recurrent …
Artificial intelligence based hybrid forecasting approaches for wind power generation: Progress, challenges and prospects
Globally, wind energy is growing rapidly and has received huge consideration to fulfill global
energy requirements. An accurate wind power forecasting is crucial to achieve a stable and …
energy requirements. An accurate wind power forecasting is crucial to achieve a stable and …