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 …
Energy consumption and carbon emissions forecasting for industrial processes: Status, challenges and perspectives
Y Hu, Y Man - Renewable and Sustainable Energy Reviews, 2023 - Elsevier
The industrial process consumes substantial energy and emits large amounts of carbon
dioxide. With the help of accurate energy consumption and carbon emissions forecasting …
dioxide. With the help of accurate energy consumption and carbon emissions forecasting …
A survey of ensemble learning: Concepts, algorithms, applications, and prospects
Ensemble learning techniques have achieved state-of-the-art performance in diverse
machine learning applications by combining the predictions from two or more base models …
machine learning applications by combining the predictions from two or more base models …
Wind power forecasting considering data privacy protection: A federated deep reinforcement learning approach
In a modern power system with an increasing proportion of renewable energy, wind power
prediction is crucial to the arrangement of power grid dispatching plans due to the volatility …
prediction is crucial to the arrangement of power grid dispatching plans due to the volatility …
Real-time optimal energy management of microgrid with uncertainties based on deep reinforcement learning
C Guo, X Wang, Y Zheng, F Zhang - Energy, 2022 - Elsevier
Microgrid (MG) is an effective way to integrate renewable energy into power system at the
consumer side. In the MG, the energy management system (EMS) is necessary to be …
consumer side. In the MG, the energy management system (EMS) is necessary to be …
Multi-step-ahead wind speed forecasting based on a hybrid decomposition method and temporal convolutional networks
Recently, the boom in wind power industry has called for the accurate and stable wind
speed forecasting, on which reliable wind power generation systems depend heavily. Due to …
speed forecasting, on which reliable wind power generation systems depend heavily. Due to …
Ensemble forecasting system for short-term wind speed forecasting based on optimal sub-model selection and multi-objective version of mayfly optimization algorithm
Z Liu, P Jiang, J Wang, L Zhang - Expert Systems with Applications, 2021 - Elsevier
Wind energy has attracted considerable attention in the past decades as a low-carbon,
environmentally friendly, and efficient renewable energy. However, the irregularity of wind …
environmentally friendly, and efficient renewable energy. However, the irregularity of wind …
A combined short-term wind speed forecasting model based on CNN–RNN and linear regression optimization considering error
J Duan, M Chang, X Chen, W Wang, H Zuo, Y Bai… - Renewable Energy, 2022 - Elsevier
Wind speed forecasting is the key to wind power conversion and management in smart
grids. In this paper, a new hybrid model is proposed, which is composed of empirical mode …
grids. In this paper, a new hybrid model is proposed, which is composed of empirical mode …
A multi-factor driven spatiotemporal wind power prediction model based on ensemble deep graph attention reinforcement learning networks
Y Chengqing, Y Guangxi, Y Chengming, Z Yu, M Xiwei - Energy, 2023 - Elsevier
Spatiotemporal wind power prediction technology could provide technical support for wind
farm energy regulation and dynamic planning. In the paper, a novel ensemble deep graph …
farm energy regulation and dynamic planning. In the paper, a novel ensemble deep graph …
Applications of reinforcement learning for building energy efficiency control: A review
Q Fu, Z Han, J Chen, Y Lu, H Wu, Y Wang - Journal of Building Engineering, 2022 - Elsevier
The wide variety of smart devices equipped in modern intelligent buildings and the
increasing comfort requirements of occupants for the environment make the control of …
increasing comfort requirements of occupants for the environment make the control of …