Deep learning based ensemble approach for probabilistic wind power forecasting

Author:

Wang Huai-zhi,Li Gang-qiang,Wang Gui-bin,Peng Jian-chun,Jiang Hui,Liu Yi-tao

Funder

Natural Science Foundation of China

Natural Science Foundation of Guangdong Province

Shenzhen International Cooperation Research Project

Shenzhen University Research and Development Startup Fund

National Basic Research Program

Publisher

Elsevier BV

Subject

Management, Monitoring, Policy and Law,Mechanical Engineering,General Energy,Building and Construction

Reference46 articles.

1. A novel bidirectional mechanism based on time series model for wind power forecasting;Zhao;Appl Energy,2016

2. Integrating large scale wind power into the electricity grid in the Northeast of Brazil;Jong;Energy,2016

3. A mean flow acoustic engine capable of wind energy harvesting;Sun;Energy Convers Manage,2012

4. CFD study on mean flow engine for wind power exploitation;Yu;Energy Convers Manage,2011

5. The Global Wind Energy Council. Global wind energy outlook 2008. The Global Wind Energy Council, Belgium; Oct. 2008. Available: [accessed: Feb. 11, 2009].

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