A Method Based on Numerical Wind Field and Extreme Learning Machine for Typhoon Wind Speed Prediction of Wind Farm

Typhoon wind speed prediction is of great significance for it can help prevent wind farms from damages caused by frequent typhoon disasters in coastal areas. However, most researches on wind forecast are either for meteorological application or for normal weather. Therefore, this paper proposes a sy...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Hong Xu, Wan-Yu Wang
Formato:	article
Lenguaje:	EN
Publicado:	Hindawi Limited 2021
Materias:	Engineering (General). Civil engineering (General) TA1-2040 Mathematics QA1-939
Acceso en línea:	https://doaj.org/article/31995c4a3c0c4dcca07dc16457fb322e
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:31995c4a3c0c4dcca07dc16457fb322e
record_format	dspace
spelling	oai:doaj.org-article:31995c4a3c0c4dcca07dc16457fb322e2021-11-29T00:55:51ZA Method Based on Numerical Wind Field and Extreme Learning Machine for Typhoon Wind Speed Prediction of Wind Farm1563-514710.1155/2021/7147973https://doaj.org/article/31995c4a3c0c4dcca07dc16457fb322e2021-01-01T00:00:00Zhttp://dx.doi.org/10.1155/2021/7147973https://doaj.org/toc/1563-5147Typhoon wind speed prediction is of great significance for it can help prevent wind farms from damages caused by frequent typhoon disasters in coastal areas. However, most researches on wind forecast are either for meteorological application or for normal weather. Therefore, this paper proposes a systematic method based on numerical wind field and extreme learning machine for typhoon wind speed prediction of wind farms. The proposed method mainly consists of three parts, IGA-YanMeng typhoon numerical simulation model, typhoon status prediction model, and wind speed simulation model based on an extreme learning machine. The IGA-YanMeng typhoon numerical simulation model can greatly enrich typhoon wind speed data according to historical typhoon parameters. The typhoon status prediction model can predict the status of typhoons studied in the next few hours. And wind speed simulation model simulates the average wind speed magnitude/direction at 10 m height of each turbine in the farm according to the predicted status. The end of this paper presents a case study on a wind farm located in Guangdong province that suffered from the super typhoon Mangkhut landed in 2018. The results verified the feasibility and effectiveness of the proposed method.Hong XuWan-Yu WangHindawi LimitedarticleEngineering (General). Civil engineering (General)TA1-2040MathematicsQA1-939ENMathematical Problems in Engineering, Vol 2021 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Engineering (General). Civil engineering (General) TA1-2040 Mathematics QA1-939
spellingShingle	Engineering (General). Civil engineering (General) TA1-2040 Mathematics QA1-939 Hong Xu Wan-Yu Wang A Method Based on Numerical Wind Field and Extreme Learning Machine for Typhoon Wind Speed Prediction of Wind Farm
description	Typhoon wind speed prediction is of great significance for it can help prevent wind farms from damages caused by frequent typhoon disasters in coastal areas. However, most researches on wind forecast are either for meteorological application or for normal weather. Therefore, this paper proposes a systematic method based on numerical wind field and extreme learning machine for typhoon wind speed prediction of wind farms. The proposed method mainly consists of three parts, IGA-YanMeng typhoon numerical simulation model, typhoon status prediction model, and wind speed simulation model based on an extreme learning machine. The IGA-YanMeng typhoon numerical simulation model can greatly enrich typhoon wind speed data according to historical typhoon parameters. The typhoon status prediction model can predict the status of typhoons studied in the next few hours. And wind speed simulation model simulates the average wind speed magnitude/direction at 10 m height of each turbine in the farm according to the predicted status. The end of this paper presents a case study on a wind farm located in Guangdong province that suffered from the super typhoon Mangkhut landed in 2018. The results verified the feasibility and effectiveness of the proposed method.
format	article
author	Hong Xu Wan-Yu Wang
author_facet	Hong Xu Wan-Yu Wang
author_sort	Hong Xu
title	A Method Based on Numerical Wind Field and Extreme Learning Machine for Typhoon Wind Speed Prediction of Wind Farm
title_short	A Method Based on Numerical Wind Field and Extreme Learning Machine for Typhoon Wind Speed Prediction of Wind Farm
title_full	A Method Based on Numerical Wind Field and Extreme Learning Machine for Typhoon Wind Speed Prediction of Wind Farm
title_fullStr	A Method Based on Numerical Wind Field and Extreme Learning Machine for Typhoon Wind Speed Prediction of Wind Farm
title_full_unstemmed	A Method Based on Numerical Wind Field and Extreme Learning Machine for Typhoon Wind Speed Prediction of Wind Farm
title_sort	method based on numerical wind field and extreme learning machine for typhoon wind speed prediction of wind farm
publisher	Hindawi Limited
publishDate	2021
url	https://doaj.org/article/31995c4a3c0c4dcca07dc16457fb322e
work_keys_str_mv	AT hongxu amethodbasedonnumericalwindfieldandextremelearningmachinefortyphoonwindspeedpredictionofwindfarm AT wanyuwang amethodbasedonnumericalwindfieldandextremelearningmachinefortyphoonwindspeedpredictionofwindfarm AT hongxu methodbasedonnumericalwindfieldandextremelearningmachinefortyphoonwindspeedpredictionofwindfarm AT wanyuwang methodbasedonnumericalwindfieldandextremelearningmachinefortyphoonwindspeedpredictionofwindfarm
_version_	1718407760399302656

A Method Based on Numerical Wind Field and Extreme Learning Machine for Typhoon Wind Speed Prediction of Wind Farm

Ejemplares similares