干旱区生态环境知识资源中心(Arid): Improving wind speed forecasts from the Weather Research and Forecasting model at a wind farm in the semiarid Coquimbo region in central Chile

Arid

DOI	10.1002/we.2527
	Improving wind speed forecasts from the Weather Research and Forecasting model at a wind farm in the semiarid Coquimbo region in central Chile
	Salfate, Ignacio; Marin, Julio C.; Cuevas, Omar; Montecinos, Sonia
通讯作者	Marin, JC
来源期刊	WIND ENERGY
ISSN	1095-4244
EISSN	1099-1824
出版年	2020
卷号	23 期号:10 页码:1939-1954
英文摘要	Accurate predictions of the wind field are key for better wind power forecasts. Wind speed forecasts from numerical weather models present differences with observations, especially in places with complex topography, such as the north of Chile. The present study has two goals: (a) to find the WRF model boundary layer (PBL) scheme that best reproduces the observations at the Totoral Wind Farm, located in the semiarid Coquimbo region in north-central Chile, and (b) to use an artificial neural network (ANN) to postprocess wind speed forecasts from different model domains to analyze the sensitivity to horizontal resolution. The WRF model was run with three different PBL schemes (MYNN, MYNN3, and QNSE) for 2013. The WRF simulation with the QNSE scheme showed the best agreement with observations at the wind farm, and its outputs were postprocessed using two ANNs with two algorithms: backpropagation (BP) and particle swarm optimization (PSO). These two ANNs were applied to the innermost WRF domains with 3-km (d03) and 1-km (d04) horizontal resolutions. The root-mean-square errors (RMSEs) between raw WRF forecasts and observations for d03 and d04 were 2.7 and 2.4 ms(-1), respectively. When both ANN models (BP and PSO) were applied to Domains d03 and d04, the RMSE decreased to values lower than 1.7 ms(-1), and they showed similar performances, supporting the use of an ANN to postprocess a three-nested WRF domain configuration to provide more accurate forecasts in advance for the region.
英文关键词	ANN postprocessing numerical weather prediction model forecasts PBL parameterizations wind power
类型	Article
语种	英语
收录类别	SCI-E
WOS记录号	WOS:000548109400001
WOS关键词	LOW-LEVEL JETS ; BOUNDARY-LAYER ; WRF MODEL ; RAINFALL VARIABILITY ; POWER PREDICTION ; ATACAMA DESERT ; SIMULATION ; PARAMETERIZATION ; PRECIPITATION ; CIRCULATION
WOS类目	Energy & Fuels ; Engineering, Mechanical
WOS研究方向	Energy & Fuels ; Engineering
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/325027
作者单位	[Salfate, Ignacio; Montecinos, Sonia] Univ La Serena, Dept Fis & Astron, La Serena, Chile; [Marin, Julio C.] Univ Valparaiso, Dept Meteorol, Gran Bretana 644, Valparaiso, Chile; [Cuevas, Omar] Univ Valparaiso, Inst Fis & Astron, Valparaiso, Chile; [Marin, Julio C.; Cuevas, Omar] Univ Valparaiso, Ctr Interdisciplinario Estudios Atmosfer & Astroe, Valparaiso, Chile
推荐引用方式 GB/T 7714	Salfate, Ignacio,Marin, Julio C.,Cuevas, Omar,et al. Improving wind speed forecasts from the Weather Research and Forecasting model at a wind farm in the semiarid Coquimbo region in central Chile[J],2020,23(10):1939-1954.
APA	Salfate, Ignacio,Marin, Julio C.,Cuevas, Omar,&Montecinos, Sonia.(2020).Improving wind speed forecasts from the Weather Research and Forecasting model at a wind farm in the semiarid Coquimbo region in central Chile.WIND ENERGY,23(10),1939-1954.
MLA	Salfate, Ignacio,et al."Improving wind speed forecasts from the Weather Research and Forecasting model at a wind farm in the semiarid Coquimbo region in central Chile".WIND ENERGY 23.10(2020):1939-1954.