Deep Learning Approach with Optimizatized Hidden-Layers Topology for Short-Term Wind Power Forecasting

Energy Engineering ◽

10.32604/ee.2020.011619 ◽

2020 ◽

Vol 117 (5) ◽

pp. 279-287

Author(s):

Xing Deng ◽

Haijian Shao

Keyword(s):

Deep Learning ◽

Learning Approach ◽

Wind Power Forecasting ◽

Power Forecasting

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Very short-term spatial and temporal wind power forecasting: A deep learning approach

CSEE Journal of Power and Energy Systems ◽

10.17775/cseejpes.2018.00010 ◽

2019 ◽

Keyword(s):

Deep Learning ◽

Learning Approach ◽

Wind Power Forecasting ◽

Power Forecasting

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Short-Term Wind Power Forecasting Based on the Deep Learning Approach Optimized by the Improved T-distributed Stochastic Neighbor Embedding

10.1007/978-981-16-6554-7_6 ◽

2021 ◽

pp. 53-65

Author(s):

Xing Deng ◽

Feipeng Da ◽

Haijian Shao

Keyword(s):

Deep Learning ◽

Learning Approach ◽

Wind Power Forecasting ◽

Power Forecasting

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A novel deep learning approach for short-term wind power forecasting based on infinite feature selection and recurrent neural network

Journal of Renewable and Sustainable Energy ◽

10.1063/1.5024297 ◽

2018 ◽

Vol 10 (4) ◽

pp. 043303 ◽

Author(s):

Haijian Shao ◽

Xing Deng ◽

Yingtao Jiang

Keyword(s):

Neural Network ◽

Feature Selection ◽

Deep Learning ◽

Recurrent Neural Network ◽

Learning Approach ◽

Wind Power Forecasting ◽

Power Forecasting

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An Ensemble Model for Short-Term Wind Power Forecasting using Deep Learning and Gradient Boosting Algorithms

2020 21st National Power Systems Conference (NPSC) ◽

10.1109/npsc49263.2020.9331902 ◽

2020 ◽

Author(s):

Devesh Kumar ◽

Rishabh Abhinav ◽

Naran Pindoriya

Keyword(s):

Deep Learning ◽

Gradient Boosting ◽

Ensemble Model ◽

Wind Power Forecasting ◽

Boosting Algorithms ◽

Power Forecasting

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Deep Learning Ensemble Based New Approach for Very Short-Term Wind Power Forecasting

2020 IEEE Power & Energy Society General Meeting (PESGM) ◽

10.1109/pesgm41954.2020.9281473 ◽

2020 ◽

Author(s):

Dan A. Rosa de Jesus ◽

Paras Mandal ◽

Yuan-Kang Wu ◽

Tomonobu Senjyu

Keyword(s):

Deep Learning ◽

New Approach ◽

Wind Power Forecasting ◽

Power Forecasting

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Short-Term Wind Power Forecasting Based on CEEMD and Deep Learning Model

10.12677/sg.2021.114028 ◽

2021 ◽

Vol 11 (04) ◽

pp. 297-304

Author(s):

一民帅

Keyword(s):

Deep Learning ◽

Learning Model ◽

Wind Power Forecasting ◽

Deep Learning Model ◽

Power Forecasting

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Hybrid Deep Learning Model for Ultra-Short-Term Wind Power Forecasting

2020 IEEE International Conference on Applied Superconductivity and Electromagnetic Devices (ASEMD) ◽

10.1109/asemd49065.2020.9276090 ◽

2020 ◽

Author(s):

Md Alamgir Hossain ◽

Ripon K. Chakrabortty ◽

Sondoss Elsawah ◽

Michael J. Ryan

Keyword(s):

Deep Learning ◽

Learning Model ◽

Wind Power Forecasting ◽

Deep Learning Model ◽

Power Forecasting

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Short-term wind power forecasting based on Attention Mechanism and Deep Learning

Electric Power Systems Research ◽

10.1016/j.epsr.2022.107776 ◽

2022 ◽

Vol 206 ◽

pp. 107776

Author(s):

Bangru Xiong ◽

Lu Lou ◽

Xinyu Meng ◽

Xin Wang ◽

Hui Ma ◽

...

Keyword(s):

Deep Learning ◽

Attention Mechanism ◽

Wind Power Forecasting ◽

Power Forecasting

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Short-term Wind Power Forecasting with Evolutionary Deep Learning

2019 IEEE 3rd Conference on Energy Internet and Energy System Integration (EI2) ◽

10.1109/ei247390.2019.9062076 ◽

2019 ◽

Author(s):

Lingzhi Yi ◽

Haoyi Sun ◽

Dongzhou Qiu ◽

Zhang Chen ◽

Fengming Chang ◽

...

Keyword(s):

Deep Learning ◽

Wind Power Forecasting ◽

Power Forecasting

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Very-short term wind power forecasting through Adaptive Wavelet Neural Network

2016 Biennial International Conference on Power and Energy Systems: Towards Sustainable Energy (PESTSE) ◽

10.1109/pestse.2016.7516513 ◽

2016 ◽

Author(s):

M. Nandana Jyothi ◽

P.V. Ramana Rao

Keyword(s):

Neural Network ◽

Wavelet Neural Network ◽

Adaptive Wavelet ◽

Wind Power Forecasting ◽

Power Forecasting

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