Short-term wind speed predicting framework based on EEMD-GA-LSTM method under large scaled wind history-Reference-Cited by-同舟云学术

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Short-term wind speed predicting framework based on EEMD-GA-LSTM method under large scaled wind history

Published:2021-01 Issue: Volume:227 Page:113559
ISSN:0196-8904
Container-title:Energy Conversion and Management
language:en
Short-container-title:Energy Conversion and Management

Author:

Chen Yaoran,Dong Zhikun,Wang Yan,Su Jie,Han Zhaolong^ORCID,Zhou Dai^ORCID,Zhang Kai,Zhao Yongsheng,Bao Yan

Funder

National Natural Science Foundation of China

Shanghai Municipal Education Commission

Shanghai Natural Science Foundation

Shanghai Institutions of Higher Learning

Intergovernmental International S&T Cooperation Projects of Shanghai Municipality

International Cooperation of Shanghai Science and Technology

Shanghai Education Development Foundation and Shanghai Municipal Education Commission

Publisher

Elsevier BV

Subject

Energy Engineering and Power Technology,Fuel Technology,Nuclear Energy and Engineering,Renewable Energy, Sustainability and the Environment

Reference49 articles.

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3. Contribution of Variable Renewable Energy to increase energy security in Latin America: complementarity and climate change impacts on wind solar resources;Viviescas;Renewable Sustainable Energy Rev,2019

4. New perspective on maximum wind energy extraction of variable-speed wind turbines using previewed wind speeds;Song;Energy Convers Manage,2020

5. Application of WRF mesoscale model for prediction of wind energy resources in Tanzania;Kibona;Sci Afr,2020

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