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	author = {Asier González-González and Jose Lopez-Guede},
	title = {Longitudinal wind speed time series generation to wind turbine controllers tuning},
	journal = {International Journal of Renewable Energy Development},
	volume = {7},
	number = {3},
	year = {2018},
	keywords = {wind speed; time series; autoregressive models; wind turbine},
	abstract = {Although there are a wide variety of applications that require wind speed time series (WSTS), this paper emphases on WSTS to be used into wind turbine controllers tuning. These simulations involve several WSTS to perform a proper assessment. These WSTS must assure realistic wind speed variations such as wind gusts and include some rare events such as extreme wind situations. The architecture proposed to generate this WSTS is based on autoregressive models with certain post-processing. The methodology used is entirely described by precise notation as well as it is parametrized by means of data gathered from a weather station. Two main different simulations are performed and assessment; the first simulation is fed by weather data with high wind speed and great variability. The second simulation, on the opposite, use calm wind speed as a data source.Article History: Received 1st  June 2018; Received in revised form Sept 6th 2018; Accepted October 10th 2018; Available onlineHow to Cite This Article: González, A.G. and Guede, J.M.L. (2018) Longitudinal Wind Speed Time Series Generated With Autoregressive Methods For Wind Turbine Control.  International Journal of Renewable Energy Development, 7(3), 199-204.},
	issn = {2252-4940},	pages = {199--204}	doi = {10.14710/ijred.7.3.199-204},
	url = {}