An overview of deterministic and probabilistic forecasting methods of wind energy
Summary: In recent years, a variety of wind forecasting models have been developed, prompting necessity to review the abundant methods to gain insights of the state-of-the-art development status. However, existing literature reviews only focus on a subclass of methods, such as multi-objective optimi...
Main Authors: | , , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
Elsevier
2023-01-01
|
Series: | iScience |
Subjects: | |
Online Access: | http://www.sciencedirect.com/science/article/pii/S2589004222020776 |
_version_ | 1797946155394400256 |
---|---|
author | Yuying Xie Chaoshun Li Mengying Li Fangjie Liu Meruyert Taukenova |
author_facet | Yuying Xie Chaoshun Li Mengying Li Fangjie Liu Meruyert Taukenova |
author_sort | Yuying Xie |
collection | DOAJ |
description | Summary: In recent years, a variety of wind forecasting models have been developed, prompting necessity to review the abundant methods to gain insights of the state-of-the-art development status. However, existing literature reviews only focus on a subclass of methods, such as multi-objective optimization and machine learning methods while lacking the full particulars of wind forecasting field. Furthermore, the classification of wind forecasting methods is unclear and incomplete, especially considering the rapid development of this field. Therefore, this article aims to provide a systematic review of the existing deterministic and probabilistic wind forecasting methods, from the perspectives of data source, model evaluation framework, technical background, theoretical basis, and model performance. It is expected that this work will provide junior researchers with broad and detailed information on wind forecasting for their future development of more accurate and practical wind forecasting models. |
first_indexed | 2024-04-10T21:06:24Z |
format | Article |
id | doaj.art-596545ca1fc34f199d928967412fb989 |
institution | Directory Open Access Journal |
issn | 2589-0042 |
language | English |
last_indexed | 2024-04-10T21:06:24Z |
publishDate | 2023-01-01 |
publisher | Elsevier |
record_format | Article |
series | iScience |
spelling | doaj.art-596545ca1fc34f199d928967412fb9892023-01-22T04:41:06ZengElsevieriScience2589-00422023-01-01261105804An overview of deterministic and probabilistic forecasting methods of wind energyYuying Xie0Chaoshun Li1Mengying Li2Fangjie Liu3Meruyert Taukenova4China-EU Institute for Clean and Renewable Energy, Huazhong University of Science and Technology, Wuhan 430074, China; Department of Mechanical Engineering and Research Institute for Smart Energy, the Hong Kong Polytechnic University, Kowloon, Hong Kong SAR, ChinaSchool of Civil and Hydraulic Engineering, Huazhong University of Science and Technology, Wuhan 430074, China; China-EU Institute for Clean and Renewable Energy, Huazhong University of Science and Technology, Wuhan 430074, China; Corresponding authorDepartment of Mechanical Engineering and Research Institute for Smart Energy, the Hong Kong Polytechnic University, Kowloon, Hong Kong SAR, ChinaChina-EU Institute for Clean and Renewable Energy, Huazhong University of Science and Technology, Wuhan 430074, ChinaChina-EU Institute for Clean and Renewable Energy, Huazhong University of Science and Technology, Wuhan 430074, ChinaSummary: In recent years, a variety of wind forecasting models have been developed, prompting necessity to review the abundant methods to gain insights of the state-of-the-art development status. However, existing literature reviews only focus on a subclass of methods, such as multi-objective optimization and machine learning methods while lacking the full particulars of wind forecasting field. Furthermore, the classification of wind forecasting methods is unclear and incomplete, especially considering the rapid development of this field. Therefore, this article aims to provide a systematic review of the existing deterministic and probabilistic wind forecasting methods, from the perspectives of data source, model evaluation framework, technical background, theoretical basis, and model performance. It is expected that this work will provide junior researchers with broad and detailed information on wind forecasting for their future development of more accurate and practical wind forecasting models.http://www.sciencedirect.com/science/article/pii/S2589004222020776Energy modelingenergy engineeringenergy systems |
spellingShingle | Yuying Xie Chaoshun Li Mengying Li Fangjie Liu Meruyert Taukenova An overview of deterministic and probabilistic forecasting methods of wind energy iScience Energy modeling energy engineering energy systems |
title | An overview of deterministic and probabilistic forecasting methods of wind energy |
title_full | An overview of deterministic and probabilistic forecasting methods of wind energy |
title_fullStr | An overview of deterministic and probabilistic forecasting methods of wind energy |
title_full_unstemmed | An overview of deterministic and probabilistic forecasting methods of wind energy |
title_short | An overview of deterministic and probabilistic forecasting methods of wind energy |
title_sort | overview of deterministic and probabilistic forecasting methods of wind energy |
topic | Energy modeling energy engineering energy systems |
url | http://www.sciencedirect.com/science/article/pii/S2589004222020776 |
work_keys_str_mv | AT yuyingxie anoverviewofdeterministicandprobabilisticforecastingmethodsofwindenergy AT chaoshunli anoverviewofdeterministicandprobabilisticforecastingmethodsofwindenergy AT mengyingli anoverviewofdeterministicandprobabilisticforecastingmethodsofwindenergy AT fangjieliu anoverviewofdeterministicandprobabilisticforecastingmethodsofwindenergy AT meruyerttaukenova anoverviewofdeterministicandprobabilisticforecastingmethodsofwindenergy AT yuyingxie overviewofdeterministicandprobabilisticforecastingmethodsofwindenergy AT chaoshunli overviewofdeterministicandprobabilisticforecastingmethodsofwindenergy AT mengyingli overviewofdeterministicandprobabilisticforecastingmethodsofwindenergy AT fangjieliu overviewofdeterministicandprobabilisticforecastingmethodsofwindenergy AT meruyerttaukenova overviewofdeterministicandprobabilisticforecastingmethodsofwindenergy |