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EMD-based gray combined forecasting model - Application to long-term forecasting of wind power generation
Wind power is the most promising renewable energy source after hydropower because of its mature technology and low price, and has great potential for carbon emission reduction. Long-term forecasts of its power generation can help power companies to develop operational plans, grid configuration and p...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10366421/ https://www.ncbi.nlm.nih.gov/pubmed/37496909 http://dx.doi.org/10.1016/j.heliyon.2023.e18053 |
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author | Ran, Minghao Huang, Jindi Qian, Wuyong Zou, Tingting Ji, Chunyi |
author_facet | Ran, Minghao Huang, Jindi Qian, Wuyong Zou, Tingting Ji, Chunyi |
author_sort | Ran, Minghao |
collection | PubMed |
description | Wind power is the most promising renewable energy source after hydropower because of its mature technology and low price, and has great potential for carbon emission reduction. Long-term forecasts of its power generation can help power companies to develop operational plans, grid configuration and power dispatch, and can also provide a basis for the government to formulate energy and environmental policies. However, due to the characteristics of China's monsoon climate and wind power industry development, wind power generation data are characterized by nonlinear cycles and small data volume, which makes accurate prediction more difficult. To this end, this paper develops a new prediction model and applies it to the long-term prediction of wind power generation in China, and proposes some targeted policy recommendations based on the prediction results to promote the development of China's wind power industry. |
format | Online Article Text |
id | pubmed-10366421 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-103664212023-07-26 EMD-based gray combined forecasting model - Application to long-term forecasting of wind power generation Ran, Minghao Huang, Jindi Qian, Wuyong Zou, Tingting Ji, Chunyi Heliyon Research Article Wind power is the most promising renewable energy source after hydropower because of its mature technology and low price, and has great potential for carbon emission reduction. Long-term forecasts of its power generation can help power companies to develop operational plans, grid configuration and power dispatch, and can also provide a basis for the government to formulate energy and environmental policies. However, due to the characteristics of China's monsoon climate and wind power industry development, wind power generation data are characterized by nonlinear cycles and small data volume, which makes accurate prediction more difficult. To this end, this paper develops a new prediction model and applies it to the long-term prediction of wind power generation in China, and proposes some targeted policy recommendations based on the prediction results to promote the development of China's wind power industry. Elsevier 2023-07-07 /pmc/articles/PMC10366421/ /pubmed/37496909 http://dx.doi.org/10.1016/j.heliyon.2023.e18053 Text en © 2023 The Authors. Published by Elsevier Ltd. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Research Article Ran, Minghao Huang, Jindi Qian, Wuyong Zou, Tingting Ji, Chunyi EMD-based gray combined forecasting model - Application to long-term forecasting of wind power generation |
title | EMD-based gray combined forecasting model - Application to long-term forecasting of wind power generation |
title_full | EMD-based gray combined forecasting model - Application to long-term forecasting of wind power generation |
title_fullStr | EMD-based gray combined forecasting model - Application to long-term forecasting of wind power generation |
title_full_unstemmed | EMD-based gray combined forecasting model - Application to long-term forecasting of wind power generation |
title_short | EMD-based gray combined forecasting model - Application to long-term forecasting of wind power generation |
title_sort | emd-based gray combined forecasting model - application to long-term forecasting of wind power generation |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10366421/ https://www.ncbi.nlm.nih.gov/pubmed/37496909 http://dx.doi.org/10.1016/j.heliyon.2023.e18053 |
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