A Novel Statistical Method to Temporally Downscale Wind Speed Weibull Distribution Using Scaling Property

To improve our capacity to use available wind speed data, it is necessary to develop a new statistical temporal downscaling method that uses one or a few input variables of any temporal scale for mean wind speed data to obtain wind statistics at finer temporal resolution. In the present study, a nov...
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Autor*in:	Ju-Young Shin [verfasserIn] Changsam Jeong [verfasserIn] Jun-Haeng Heo [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2018

Schlagwörter:	statistical temporal downscaling downscaling wind statistics Weibull distribution wind potential energy Weibull parameter estimation

Übergeordnetes Werk:	In: Energies - MDPI AG, 2008, 11(2018), 3, p 633
Übergeordnetes Werk:	volume:11 ; year:2018 ; number:3, p 633

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.3390/en11030633

Katalog-ID:	DOAJ079303013

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allfieldsSound	10.3390/en11030633 doi (DE-627)DOAJ079303013 (DE-599)DOAJ4caa24ae97084be4b143b26a8bb7e22a DE-627 ger DE-627 rakwb eng Ju-Young Shin verfasserin aut A Novel Statistical Method to Temporally Downscale Wind Speed Weibull Distribution Using Scaling Property 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier To improve our capacity to use available wind speed data, it is necessary to develop a new statistical temporal downscaling method that uses one or a few input variables of any temporal scale for mean wind speed data to obtain wind statistics at finer temporal resolution. In the present study, a novel statistical temporal downscaling method for wind speed statistics and probability distribution is proposed. The proposed method uses the temporal structure to downscale the wind speed statistics to a fine temporal scale without the use of additional variables. The Weibull distribution of the hourly and 10-min mean wind speed data is obtained by the downscaled wind speed statistics. The proposed method provides the downscaled Weibull distribution of fine temporal wind speed data using coarse temporal wind statistics. Particularly, the use of sub-daily mean wind speed data in the downscaling of the wind speed Weibull distribution leads to good estimation precision. The Weibull distribution downscaled by the proposed method successfully reproduces the wind power density based on the wind potential energy estimation. statistical temporal downscaling downscaling wind statistics Weibull distribution wind potential energy Weibull parameter estimation Technology T Changsam Jeong verfasserin aut Jun-Haeng Heo verfasserin aut In Energies MDPI AG, 2008 11(2018), 3, p 633 (DE-627)572083742 (DE-600)2437446-5 19961073 nnns volume:11 year:2018 number:3, p 633 https://doi.org/10.3390/en11030633 kostenfrei https://doaj.org/article/4caa24ae97084be4b143b26a8bb7e22a kostenfrei http://www.mdpi.com/1996-1073/11/3/633 kostenfrei https://doaj.org/toc/1996-1073 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2108 GBV_ILN_2111 GBV_ILN_2119 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 11 2018 3, p 633
language	English
source	In Energies 11(2018), 3, p 633 volume:11 year:2018 number:3, p 633
sourceStr	In Energies 11(2018), 3, p 633 volume:11 year:2018 number:3, p 633
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	statistical temporal downscaling downscaling wind statistics Weibull distribution wind potential energy Weibull parameter estimation Technology T
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container_title	Energies
authorswithroles_txt_mv	Ju-Young Shin @@aut@@ Changsam Jeong @@aut@@ Jun-Haeng Heo @@aut@@
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author	Ju-Young Shin
spellingShingle	Ju-Young Shin misc statistical temporal downscaling misc downscaling wind statistics misc Weibull distribution misc wind potential energy misc Weibull parameter estimation misc Technology misc T A Novel Statistical Method to Temporally Downscale Wind Speed Weibull Distribution Using Scaling Property
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topic_title	A Novel Statistical Method to Temporally Downscale Wind Speed Weibull Distribution Using Scaling Property statistical temporal downscaling downscaling wind statistics Weibull distribution wind potential energy Weibull parameter estimation
topic	misc statistical temporal downscaling misc downscaling wind statistics misc Weibull distribution misc wind potential energy misc Weibull parameter estimation misc Technology misc T
topic_unstemmed	misc statistical temporal downscaling misc downscaling wind statistics misc Weibull distribution misc wind potential energy misc Weibull parameter estimation misc Technology misc T
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title	A Novel Statistical Method to Temporally Downscale Wind Speed Weibull Distribution Using Scaling Property
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title_sort	novel statistical method to temporally downscale wind speed weibull distribution using scaling property
title_auth	A Novel Statistical Method to Temporally Downscale Wind Speed Weibull Distribution Using Scaling Property
abstract	To improve our capacity to use available wind speed data, it is necessary to develop a new statistical temporal downscaling method that uses one or a few input variables of any temporal scale for mean wind speed data to obtain wind statistics at finer temporal resolution. In the present study, a novel statistical temporal downscaling method for wind speed statistics and probability distribution is proposed. The proposed method uses the temporal structure to downscale the wind speed statistics to a fine temporal scale without the use of additional variables. The Weibull distribution of the hourly and 10-min mean wind speed data is obtained by the downscaled wind speed statistics. The proposed method provides the downscaled Weibull distribution of fine temporal wind speed data using coarse temporal wind statistics. Particularly, the use of sub-daily mean wind speed data in the downscaling of the wind speed Weibull distribution leads to good estimation precision. The Weibull distribution downscaled by the proposed method successfully reproduces the wind power density based on the wind potential energy estimation.
abstractGer	To improve our capacity to use available wind speed data, it is necessary to develop a new statistical temporal downscaling method that uses one or a few input variables of any temporal scale for mean wind speed data to obtain wind statistics at finer temporal resolution. In the present study, a novel statistical temporal downscaling method for wind speed statistics and probability distribution is proposed. The proposed method uses the temporal structure to downscale the wind speed statistics to a fine temporal scale without the use of additional variables. The Weibull distribution of the hourly and 10-min mean wind speed data is obtained by the downscaled wind speed statistics. The proposed method provides the downscaled Weibull distribution of fine temporal wind speed data using coarse temporal wind statistics. Particularly, the use of sub-daily mean wind speed data in the downscaling of the wind speed Weibull distribution leads to good estimation precision. The Weibull distribution downscaled by the proposed method successfully reproduces the wind power density based on the wind potential energy estimation.
abstract_unstemmed	To improve our capacity to use available wind speed data, it is necessary to develop a new statistical temporal downscaling method that uses one or a few input variables of any temporal scale for mean wind speed data to obtain wind statistics at finer temporal resolution. In the present study, a novel statistical temporal downscaling method for wind speed statistics and probability distribution is proposed. The proposed method uses the temporal structure to downscale the wind speed statistics to a fine temporal scale without the use of additional variables. The Weibull distribution of the hourly and 10-min mean wind speed data is obtained by the downscaled wind speed statistics. The proposed method provides the downscaled Weibull distribution of fine temporal wind speed data using coarse temporal wind statistics. Particularly, the use of sub-daily mean wind speed data in the downscaling of the wind speed Weibull distribution leads to good estimation precision. The Weibull distribution downscaled by the proposed method successfully reproduces the wind power density based on the wind potential energy estimation.
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title_short	A Novel Statistical Method to Temporally Downscale Wind Speed Weibull Distribution Using Scaling Property
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