Comprehensive evaluation of ARMA–GARCH(-M) approaches for modeling the mean and volatility of wind speed

Accurately modeling the mean and volatility of wind speed can be beneficial to effective wind energy utilization. For this purpose, this paper evaluates the effectiveness of autoregressive moving average–generalized autoregressive conditional heteroscedasticity (ARMA–GARCH) approaches for modeling t...

Celý popis

Uložené v:

Podrobná bibliografia
Vydané v:	Applied energy Ročník 88; číslo 3; s. 724 - 732
Hlavní autori:	Liu, Heping, Erdem, Ergin, Shi, Jing
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Kidlington Elsevier Ltd 01.03.2011 Elsevier
Edícia:	Applied Energy
Predmet:	Applied sciences ARMA Asymmetry Colorado data collection Deterioration Energy Energy utilization Exact sciences and technology Forecasting GARCH GARCH-M heteroskedasticity Mathematical models Natural energy Nonlinearity Trends Volatility Wind energy Wind power generation Wind speed Wind speed Forecasting ARMA GARCH GARCH-M Colorado USA, Colorado GARCH ARMA Wind speed GARCH-M Forecasting
ISSN:	0306-2619, 1872-9118
On-line prístup:	Získať plný text
Tagy:	Pridať tag Žiadne tagy, Buďte prvý, kto otaguje tento záznam!

Abstract	Accurately modeling the mean and volatility of wind speed can be beneficial to effective wind energy utilization. For this purpose, this paper evaluates the effectiveness of autoregressive moving average–generalized autoregressive conditional heteroscedasticity (ARMA–GARCH) approaches for modeling the mean and volatility of wind speed. Five different GARCH approaches are included, and each consists of an original form and a modified form, GARCH-in-mean (GARCH-M). As a result, 10 different model structures are evaluated, based on the 7-year hourly wind speed data collected at four different heights from an observation site in Colorado, USA. Multiple evaluation methods of modeling sufficiency are used. The results show that the ARMA–GARCH(-M) approaches can effectively catch the trend change of the mean and volatility of wind speed. Also, the volatility of wind speed has the nonlinear and asymmetric time-varying feature, and the ARMA–GARCH-M structures can consistently improve the modeling sufficiency of mean wind speed. As the height increases, the explanatory power of all ARMA–GARCH(-M) models slightly deteriorates. On the other hand, no single model structure outperforms the others at all heights, and this confirms that for any wind speed dataset, the potential models should be evaluated to find the most appropriate one for the highest modeling sufficiency.
AbstractList	Accurately modeling the mean and volatility of wind speed can be beneficial to effective wind energy utilization. For this purpose, this paper evaluates the effectiveness of autoregressive moving average–generalized autoregressive conditional heteroscedasticity (ARMA–GARCH) approaches for modeling the mean and volatility of wind speed. Five different GARCH approaches are included, and each consists of an original form and a modified form, GARCH-in-mean (GARCH-M). As a result, 10 different model structures are evaluated, based on the 7-year hourly wind speed data collected at four different heights from an observation site in Colorado, USA. Multiple evaluation methods of modeling sufficiency are used. The results show that the ARMA–GARCH(-M) approaches can effectively catch the trend change of the mean and volatility of wind speed. Also, the volatility of wind speed has the nonlinear and asymmetric time-varying feature, and the ARMA–GARCH-M structures can consistently improve the modeling sufficiency of mean wind speed. As the height increases, the explanatory power of all ARMA–GARCH(-M) models slightly deteriorates. On the other hand, no single model structure outperforms the others at all heights, and this confirms that for any wind speed dataset, the potential models should be evaluated to find the most appropriate one for the highest modeling sufficiency.
Author	Erdem, Ergin Liu, Heping Shi, Jing
Author_xml	– sequence: 1 givenname: Heping surname: Liu fullname: Liu, Heping – sequence: 2 givenname: Ergin surname: Erdem fullname: Erdem, Ergin – sequence: 3 givenname: Jing surname: Shi fullname: Shi, Jing email: jing.shi@ndsu.edu
BackLink	http://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=23825413$$DView record in Pascal Francis http://econpapers.repec.org/article/eeeappene/v_3a88_3ay_3a2011_3ai_3a3_3ap_3a724-732.htm$$DView record in RePEc
BookMark	eNqNks9u1DAQxiNUJLaFV4BcEOWQxX8SO5E4sFpBC2qFVOjZcpxx16vETu3sor3xDrwhT8Is23LgQDmMRxr95puR5zvOjnzwkGXPKZlTQsWb9VyP4CHe7OaMYJE0c8LqR9mM1pIVDaX1UTYjnIiCCdo8yY5TWhNCGGVklq2XYRgjrMAnt4Uctrrf6MkFnwebL64uFz-__zhbXC3PT4vL17kexxi0WUHKbYj5EDronb_JpxXkA2ifa9_l29CjQu-m3V7jm8NSGgG6p9ljq_sEz-7ySXb94f3X5Xlx8fns43JxUZiqkVMhGuBtayrRyFbqFkjTUtlaq0tTSl2zrmuBi5YYoRtgUFrSWi0J65q6Krm1_CR7ddDFXW83kCY1uGSg77WHsEmqripJa1pRJE__SVIpJeWi5v-BCsEFZ6wUiH46oBFGMGqMbtBxpwAAvw8PpbaK67rGZ4eBJ6OYHAbHGDEkK5XkTK2mAcVe3s3VyejeRu2NS39EGa9ZVVKO3NsDZ2JIKYJVxk2_DzlF7XpFidqbRa3VvVnU3iyKNArNgu3ir_b7CQ82vjg0Wh2Uvom42_UXBCp0mBCCMiTeHQjAm28dRJWMA2-gcxHMpLrgHhryC6LH6SQ
CODEN	APENDX
CitedBy_id	crossref_primary_10_1186_s40854_023_00500_7 crossref_primary_10_3390_en13071666 crossref_primary_10_1016_j_jclepro_2024_142500 crossref_primary_10_1016_j_rser_2015_10_071 crossref_primary_10_1016_j_jeconom_2020_06_011 crossref_primary_10_1007_s11431_013_5195_4 crossref_primary_10_1016_j_dsp_2016_11_003 crossref_primary_10_1016_j_asoc_2023_110310 crossref_primary_10_1016_j_energy_2014_08_064 crossref_primary_10_1007_s00521_015_2012_y crossref_primary_10_1016_j_renene_2021_01_003 crossref_primary_10_1109_ACCESS_2022_3171610 crossref_primary_10_1016_j_apenergy_2012_11_073 crossref_primary_10_1016_j_ecolind_2017_09_041 crossref_primary_10_1016_j_jweia_2021_104561 crossref_primary_10_1016_j_jweia_2023_105499 crossref_primary_10_1155_2015_785215 crossref_primary_10_1016_j_enconman_2014_12_072 crossref_primary_10_1016_j_energy_2016_05_133 crossref_primary_10_1007_s00521_016_2679_8 crossref_primary_10_1016_j_renene_2025_122775 crossref_primary_10_1155_2015_815253 crossref_primary_10_1061__ASCE_ST_1943_541X_0002211 crossref_primary_10_1016_j_jweia_2021_104565 crossref_primary_10_1017_jfm_2024_85 crossref_primary_10_1016_j_apenergy_2013_05_002 crossref_primary_10_1155_2013_461983 crossref_primary_10_1016_j_renene_2021_11_072 crossref_primary_10_1016_j_esr_2022_100864 crossref_primary_10_1016_j_apenergy_2024_123589 crossref_primary_10_1016_j_apenergy_2016_05_071 crossref_primary_10_1016_j_energy_2015_10_026 crossref_primary_10_3390_en9040261 crossref_primary_10_1016_j_enconman_2017_06_021 crossref_primary_10_1080_15435075_2025_2545497 crossref_primary_10_1016_j_apenergy_2016_02_125 crossref_primary_10_1016_j_enconman_2012_10_016 crossref_primary_10_1080_15435075_2025_2471997 crossref_primary_10_1109_ACCESS_2020_2964896 crossref_primary_10_3390_en81212428 crossref_primary_10_1016_j_enconman_2019_111981 crossref_primary_10_1109_ACCESS_2019_2915582 crossref_primary_10_1016_j_heliyon_2023_e18053 crossref_primary_10_1016_j_energy_2015_11_058 crossref_primary_10_1080_15567036_2021_1922550 crossref_primary_10_1109_ACCESS_2020_2966275 crossref_primary_10_1016_j_apenergy_2012_04_001 crossref_primary_10_1016_j_enconman_2017_04_064 crossref_primary_10_4236_jmf_2016_62027 crossref_primary_10_3390_su11030650 crossref_primary_10_1016_j_rser_2016_07_028 crossref_primary_10_1016_j_eswa_2022_116509 crossref_primary_10_1371_journal_pone_0116832 crossref_primary_10_1016_j_enconman_2016_08_086 crossref_primary_10_3390_su11030652 crossref_primary_10_1016_j_apenergy_2017_02_037 crossref_primary_10_3390_su8080754 crossref_primary_10_1049_rpg2_12157 crossref_primary_10_1109_TGRS_2024_3369640 crossref_primary_10_1080_15567036_2019_1632980 crossref_primary_10_1016_j_enconman_2022_116221 crossref_primary_10_1109_TSTE_2019_2940590 crossref_primary_10_1016_j_chemosphere_2020_126474 crossref_primary_10_1016_j_ijepes_2013_03_034 crossref_primary_10_1016_j_energy_2018_08_212 crossref_primary_10_1016_j_apenergy_2012_10_006 crossref_primary_10_1016_j_enconman_2016_04_036 crossref_primary_10_1016_j_engappai_2024_108201 crossref_primary_10_1108_IRJMS_11_2024_0140 crossref_primary_10_1016_j_rser_2016_01_103 crossref_primary_10_1016_j_rser_2020_109839 crossref_primary_10_3390_en9080585 crossref_primary_10_3390_en9120989 crossref_primary_10_1109_TITS_2019_2902405 crossref_primary_10_1016_j_jksuci_2020_09_009 crossref_primary_10_1002_we_2354 crossref_primary_10_1016_j_enconman_2016_01_007 crossref_primary_10_1016_j_rser_2016_01_106 crossref_primary_10_4316_AECE_2017_01001 crossref_primary_10_1002_we_2906 crossref_primary_10_1061_JOEEDU_EEENG_7445 crossref_primary_10_1016_j_apenergy_2011_07_044 crossref_primary_10_1016_j_jweia_2017_12_019 crossref_primary_10_3390_app11209441 crossref_primary_10_1016_j_renene_2014_12_074 crossref_primary_10_1080_15435075_2011_647170 crossref_primary_10_1186_s13634_017_0518_4 crossref_primary_10_1016_j_asoc_2022_109010 crossref_primary_10_1016_j_renene_2013_08_011 crossref_primary_10_1016_j_rser_2016_01_114 crossref_primary_10_3390_su10113913 crossref_primary_10_1016_j_enconman_2019_05_020 crossref_primary_10_1155_2017_6856139 crossref_primary_10_3390_app9040699 crossref_primary_10_1016_j_renene_2017_06_095 crossref_primary_10_1016_j_rser_2019_109387 crossref_primary_10_1109_TPWRS_2013_2282366 crossref_primary_10_1016_j_asoc_2018_07_041 crossref_primary_10_4028_www_scientific_net_AMM_448_453_1875 crossref_primary_10_1016_j_renene_2014_03_016 crossref_primary_10_1016_j_enconman_2019_111914 crossref_primary_10_1016_j_apenergy_2011_04_051 crossref_primary_10_1109_TII_2015_2431642 crossref_primary_10_3390_s18010298 crossref_primary_10_1016_j_apenergy_2012_09_055 crossref_primary_10_1016_j_jclepro_2022_131898 crossref_primary_10_3390_math8101795 crossref_primary_10_1016_j_energy_2015_04_075 crossref_primary_10_3390_en11112976 crossref_primary_10_1155_2022_5823656 crossref_primary_10_1016_j_clet_2025_100883 crossref_primary_10_1016_j_future_2024_107565 crossref_primary_10_1155_2014_972580 crossref_primary_10_1002_for_2477 crossref_primary_10_1016_j_asoc_2020_106917 crossref_primary_10_1016_j_energy_2024_130875 crossref_primary_10_1016_j_enconman_2020_113456 crossref_primary_10_1080_13658816_2015_1135928 crossref_primary_10_1016_j_apenergy_2017_01_043 crossref_primary_10_3390_en14092352 crossref_primary_10_3390_en10111903 crossref_primary_10_1080_02664763_2013_839634 crossref_primary_10_1177_00368504221132144 crossref_primary_10_3390_en9020109 crossref_primary_10_1155_2015_740490 crossref_primary_10_3390_app10041295 crossref_primary_10_1016_j_oceaneng_2021_110308 crossref_primary_10_1016_j_jweia_2024_105898 crossref_primary_10_1109_TSTE_2015_2441747 crossref_primary_10_1016_j_enconman_2025_119752 crossref_primary_10_1002_tee_22853 crossref_primary_10_1155_2015_464153 crossref_primary_10_1049_iet_rpg_2018_5203 crossref_primary_10_1109_TSIPN_2023_3304142 crossref_primary_10_1016_j_seta_2021_101780 crossref_primary_10_3390_en7074185 crossref_primary_10_1016_j_renene_2021_03_020 crossref_primary_10_1007_s40565_018_0471_8 crossref_primary_10_1016_j_enconman_2020_113076 crossref_primary_10_1016_j_energy_2021_120057 crossref_primary_10_1016_j_apenergy_2013_02_002 crossref_primary_10_1016_j_matpr_2020_12_1090 crossref_primary_10_1016_j_apenergy_2018_08_114 crossref_primary_10_1016_j_enpol_2016_04_027 crossref_primary_10_3390_en8076585 crossref_primary_10_1093_erae_jbu006
Cites_doi	10.1002/env.714 10.2307/1912773 10.1257/.41.2.478 10.1016/j.solener.2004.09.013 10.1016/j.jweia.2006.06.001 10.1016/0304-4076(86)90063-1 10.1016/j.renene.2006.10.005 10.1080/15567240701232162 10.2307/2938260 10.1080/07350015.1992.10509902 10.1016/S0960-1481(99)00125-1 10.2307/1913829 10.1016/0038-092X(95)00103-X 10.1080/15567030802462267 10.1111/j.1540-6261.1993.tb05127.x 10.2307/2298081 10.1002/env.754 10.1214/aos/1176345144 10.1111/j.1540-6261.1993.tb05128.x 10.1214/aos/1176344136 10.1016/j.jweia.2008.03.013 10.1016/j.renene.2010.06.049 10.1007/BF00863788 10.1093/biomet/65.2.297 10.1016/j.apenergy.2009.12.013 10.1111/j.1467-8454.1978.tb00635.x 10.1016/S0038-092X(98)00032-2 10.1016/j.rser.2008.02.002 10.1257/jep.15.4.157 10.1080/15567030801911223 10.1002/jae.693
ContentType	Journal Article
Copyright	2010 Elsevier Ltd 2015 INIST-CNRS
Copyright_xml	– notice: 2010 Elsevier Ltd – notice: 2015 INIST-CNRS
DBID	FBQ AAYXX CITATION IQODW DKI X2L 7S9 L.6 7SU 7TA 8FD C1K FR3 JG9 7ST SOI
DOI	10.1016/j.apenergy.2010.09.028
DatabaseName	AGRIS CrossRef Pascal-Francis RePEc IDEAS RePEc AGRICOLA AGRICOLA - Academic Environmental Engineering Abstracts Materials Business File Technology Research Database Environmental Sciences and Pollution Management Engineering Research Database Materials Research Database Environment Abstracts Environment Abstracts
DatabaseTitle	CrossRef AGRICOLA AGRICOLA - Academic Materials Research Database Engineering Research Database Technology Research Database Materials Business File Environmental Engineering Abstracts Environmental Sciences and Pollution Management Environment Abstracts
DatabaseTitleList	Environment Abstracts Materials Research Database AGRICOLA
DeliveryMethod	fulltext_linktorsrc
Discipline	Engineering Environmental Sciences Applied Sciences
EISSN	1872-9118
EndPage	732
ExternalDocumentID	eeeappene_v_3a88_3ay_3a2011_3ai_3a3_3ap_3a724_732_htm 23825413 10_1016_j_apenergy_2010_09_028 US201500066612 S0306261910003934
GeographicLocations	Colorado USA, Colorado
GeographicLocations_xml	– name: Colorado – name: USA, Colorado
GroupedDBID	--K --M .~1 0R~ 1B1 1~. 1~5 23M 4.4 457 4G. 5GY 5VS 7-5 71M 8P~ 9JN AABNK AACTN AAEDT AAEDW AAHCO AAIAV AAIKJ AAKOC AALRI AAOAW AAQFI AAQXK AARJD AAXUO AAYOK ABEFU ABFNM ABJNI ABMAC ABTAH ABXDB ABYKQ ACDAQ ACGFS ACNNM ACRLP ADBBV ADEZE ADMUD ADTZH AEBSH AECPX AEKER AENEX AFKWA AFTJW AGHFR AGUBO AGYEJ AHHHB AHIDL AHJVU AIEXJ AIKHN AITUG AJBFU AJOXV ALMA_UNASSIGNED_HOLDINGS AMFUW AMRAJ ASPBG AVWKF AXJTR AZFZN BELTK BJAXD BKOJK BLXMC CS3 EBS EFJIC EFLBG EJD EO8 EO9 EP2 EP3 FDB FEDTE FGOYB FIRID FNPLU FYGXN G-2 G-Q GBLVA HVGLF HZ~ IHE J1W JARJE JJJVA KOM LY6 M41 MO0 N9A O-L O9- OAUVE OZT P-8 P-9 P2P PC. Q38 R2- RIG ROL RPZ SAC SDF SDG SES SEW SPC SPCBC SSR SST SSZ T5K TN5 WUQ ZY4 ~02 ~G- ABPIF ABPTK FBQ 9DU AAHBH AATTM AAXKI AAYWO AAYXX ABWVN ACLOT ACRPL ACVFH ADCNI ADNMO AEIPS AEUPX AFJKZ AFPUW AGQPQ AIGII AIIUN AKBMS AKRWK AKYEP ANKPU APXCP CITATION EFKBS ~HD AFXIZ AGCQF AGRNS BNPGV IQODW SSH 02 0R 1 8P AAPBV ADALY DKI G- HZ IPNFZ K M X2L 7S9 L.6 7SU 7TA 8FD C1K FR3 JG9 7ST SOI
ID	FETCH-LOGICAL-c597t-69e3bbc5697b7abe09b17bffa4c47a82ddbe36b0c6a9e2e4f0bfa702d98543ff3
ISICitedReferencesCount	172
ISICitedReferencesURI	http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000285217400017&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
ISSN	0306-2619
IngestDate	Tue Oct 07 09:08:16 EDT 2025 Tue Oct 07 09:41:25 EDT 2025 Sun Nov 09 11:55:15 EST 2025 Thu Dec 16 09:11:49 EST 2021 Mon Jul 21 09:16:04 EDT 2025 Sat Nov 29 07:18:06 EST 2025 Tue Nov 18 21:22:08 EST 2025 Wed Dec 27 19:11:15 EST 2023 Fri Feb 23 02:30:27 EST 2024
IsPeerReviewed	true
IsScholarly	true
Issue	3
Keywords	GARCH ARMA Wind speed GARCH-M Forecasting
Language	English
License	CC BY 4.0
LinkModel	OpenURL
MergedId	FETCHMERGED-LOGICAL-c597t-69e3bbc5697b7abe09b17bffa4c47a82ddbe36b0c6a9e2e4f0bfa702d98543ff3
Notes	http://dx.doi.org/10.1016/j.apenergy.2010.09.028 ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23
PQID	1663632246
PQPubID	23462
PageCount	9
ParticipantIDs	proquest_miscellaneous_855718151 proquest_miscellaneous_1777136831 proquest_miscellaneous_1663632246 repec_primary_eeeappene_v_3a88_3ay_3a2011_3ai_3a3_3ap_3a724_732_htm pascalfrancis_primary_23825413 crossref_citationtrail_10_1016_j_apenergy_2010_09_028 crossref_primary_10_1016_j_apenergy_2010_09_028 fao_agris_US201500066612 elsevier_sciencedirect_doi_10_1016_j_apenergy_2010_09_028
PublicationCentury	2000
PublicationDate	2011-03-01
PublicationDateYYYYMMDD	2011-03-01
PublicationDate_xml	– month: 03 year: 2011 text: 2011-03-01 day: 01
PublicationDecade	2010
PublicationPlace	Kidlington
PublicationPlace_xml	– name: Kidlington
PublicationSeriesTitle	Applied Energy
PublicationTitle	Applied energy
PublicationYear	2011
Publisher	Elsevier Ltd Elsevier
Publisher_xml	– name: Elsevier Ltd – name: Elsevier
References	Kariniotakis G, Stavrakakis G, Nogaret E. A fuzzy logic and neural network based wind power model. In: Proceedings of the european wind energy conference, Goteborg, Sweden; 1996. p. 596–9. Ewing, Kruse, Schroeder, Smith (b0060) 2007; 95 Ljung, Box (b0185) 1978; 65 Lange, Focken (b0015) 2009 Engle, Ng (b0130) 1993; 48 Fuentes, Chen, Davis, Lackmann (b0030) 2005; 16 Nfaoui, Buret, Sayigh (b0035) 1995; 56 Engle (b0095) 1982; 50 Ewing, Kruse, Thompson (b0085) 2008; 3 Erasmo, Wilfrido (b0025) 2007; 32 American Wind Energy Association, 2010, Year End 2009 Market Report. Alexiadis, Dokopoulos, Sahsamanoglou, Manousaridis (b0040) 1998; 63 Verbeek M. A guide to modern econometrics. 2rd version, John Wiley & Sons Inc.; 2004. p. 31, 285–8. Torres, Garcia, Deblas, Defrancisco (b0020) 2005; 79 Ma, Luan, Jiang, Liu, Zhang (b0070) 2009; 13 Engle (b0080) 2001; 15 Sentana (b0140) 1995; 62 Franses, McAleer (b0120) 2002; 17 Li G, Shi J. Bayesian adaptive combination of short-term wind speed forecasts from neural network models. Renew Energy; 2010. Hannan (b0170) 1980; 8 Payne, Carroll (b0115) 2009; 31 Breusch (b0190) 1978; 17 Poon, Granger (b0125) 2003; 41 Tol (b0105) 1997; 56 Nelson, Cao (b0150) 1992; 10 Payne (b0090) 2009; 31 Godfrey (b0195) 1978; 46 [accessed March 2010]. Ewing, Kruse, Schroeder (b0110) 2006; 17 Poon, Granger (b0155) 2003; XLI Akaike H. Information theory and extension of the maximum likelihood principle. In: Petrov BN, Cszaki F, editors. Second international symposium on information theory. Akademiai Kiado, Budapest; 1973. p. 267–81. . Sfetsos (b0045) 2000; 21 World Wind Energy Association. World Wind Energy Report; 2009. Nelson (b0135) 1991; 59 Louka, Galanis, Siebert, Kariniotakis, Katsafados, Pytharoulis (b0055) 2008; 96 Glosten, Jagannathan, Runkle (b0145) 1993; 48 Schwarz (b0180) 1978; 6 [accessed July 2010]. Bollerslev (b0100) 1986; 31 Steel, Torrie (b0160) 1960 Li, Shi (b0050) 2010; 87 10.1016/j.apenergy.2010.09.028_b0065 Franses (10.1016/j.apenergy.2010.09.028_b0120) 2002; 17 Engle (10.1016/j.apenergy.2010.09.028_b0095) 1982; 50 Sentana (10.1016/j.apenergy.2010.09.028_b0140) 1995; 62 10.1016/j.apenergy.2010.09.028_b0165 Lange (10.1016/j.apenergy.2010.09.028_b0015) 2009 Ma (10.1016/j.apenergy.2010.09.028_b0070) 2009; 13 Louka (10.1016/j.apenergy.2010.09.028_b0055) 2008; 96 Hannan (10.1016/j.apenergy.2010.09.028_b0170) 1980; 8 Ewing (10.1016/j.apenergy.2010.09.028_b0085) 2008; 3 Godfrey (10.1016/j.apenergy.2010.09.028_b0195) 1978; 46 Nelson (10.1016/j.apenergy.2010.09.028_b0135) 1991; 59 Payne (10.1016/j.apenergy.2010.09.028_b0115) 2009; 31 10.1016/j.apenergy.2010.09.028_b0005 Payne (10.1016/j.apenergy.2010.09.028_b0090) 2009; 31 Fuentes (10.1016/j.apenergy.2010.09.028_b0030) 2005; 16 Alexiadis (10.1016/j.apenergy.2010.09.028_b0040) 1998; 63 Li (10.1016/j.apenergy.2010.09.028_b0050) 2010; 87 Tol (10.1016/j.apenergy.2010.09.028_b0105) 1997; 56 Ewing (10.1016/j.apenergy.2010.09.028_b0060) 2007; 95 10.1016/j.apenergy.2010.09.028_b0010 Erasmo (10.1016/j.apenergy.2010.09.028_b0025) 2007; 32 Poon (10.1016/j.apenergy.2010.09.028_b0155) 2003; XLI 10.1016/j.apenergy.2010.09.028_b0175 10.1016/j.apenergy.2010.09.028_b0075 Poon (10.1016/j.apenergy.2010.09.028_b0125) 2003; 41 Engle (10.1016/j.apenergy.2010.09.028_b0130) 1993; 48 Bollerslev (10.1016/j.apenergy.2010.09.028_b0100) 1986; 31 Schwarz (10.1016/j.apenergy.2010.09.028_b0180) 1978; 6 Breusch (10.1016/j.apenergy.2010.09.028_b0190) 1978; 17 Nelson (10.1016/j.apenergy.2010.09.028_b0150) 1992; 10 Sfetsos (10.1016/j.apenergy.2010.09.028_b0045) 2000; 21 Engle (10.1016/j.apenergy.2010.09.028_b0080) 2001; 15 Ewing (10.1016/j.apenergy.2010.09.028_b0110) 2006; 17 Nfaoui (10.1016/j.apenergy.2010.09.028_b0035) 1995; 56 Torres (10.1016/j.apenergy.2010.09.028_b0020) 2005; 79 Ljung (10.1016/j.apenergy.2010.09.028_b0185) 1978; 65 Steel (10.1016/j.apenergy.2010.09.028_b0160) 1960 Glosten (10.1016/j.apenergy.2010.09.028_b0145) 1993; 48
References_xml	– volume: 96 start-page: 2348 year: 2008 end-page: 2362 ident: b0055 article-title: Improvements in wind speed forecasts for wind power prediction purposes using Kalman filtering publication-title: J Wind Eng Ind Aerodynam – volume: 16 start-page: 449 year: 2005 end-page: 464 ident: b0030 article-title: Modeling and predicting complex space-time structures and patterns of coastal wind fields publication-title: Environmetrics – volume: 41 start-page: 478 year: 2003 end-page: 539 ident: b0125 article-title: Forecasting volatility in financial markets: a review publication-title: J Econ Literature, Amer Econ Assoc – volume: 17 start-page: 334 year: 1978 end-page: 355 ident: b0190 article-title: Testing for autocorrelation in dynamic linear models publication-title: Aust Econ Papers – reference: Akaike H. Information theory and extension of the maximum likelihood principle. In: Petrov BN, Cszaki F, editors. Second international symposium on information theory. Akademiai Kiado, Budapest; 1973. p. 267–81. – volume: 8 start-page: 1071 year: 1980 end-page: 1081 ident: b0170 article-title: The estimation of the order of an ARMA process publication-title: Ann Stat – volume: 79 start-page: 65 year: 2005 end-page: 77 ident: b0020 article-title: Forecast of hourly average wind speed with Arma models in Navarre (Spain) publication-title: Sol Energy – volume: 56 start-page: 113 year: 1997 end-page: 122 ident: b0105 article-title: Autoregressive conditional heteroscedasticity in daily wind speed measurements publication-title: Theor Appl Climatol – volume: 46 start-page: 1293 year: 1978 end-page: 1302 ident: b0195 article-title: Testing against general autoregressive and moving average error models when the regressors include lagged dependent variables publication-title: Econometrica – reference: Kariniotakis G, Stavrakakis G, Nogaret E. A fuzzy logic and neural network based wind power model. In: Proceedings of the european wind energy conference, Goteborg, Sweden; 1996. p. 596–9. – volume: 56 start-page: 301 year: 1995 end-page: 314 ident: b0035 article-title: Stochastic simulation of hourly average wind speed sequences in Tangiers (Morocco) publication-title: Sol Energy – volume: 31 start-page: 1194 year: 2009 end-page: 1203 ident: b0090 article-title: Further evidence on modeling wind speed and time-varying turbulence publication-title: Energy Sources, Part A: Recovery, Utiliz, Environ Effects – volume: 62 start-page: 639 year: 1995 end-page: 661 ident: b0140 article-title: Quadratic arch models publication-title: Rev Econ Studies – year: 1960 ident: b0160 article-title: Principles and procedures of statistics – volume: 31 start-page: 307 year: 1986 end-page: 327 ident: b0100 article-title: Generalized autoregressive conditional heteroskedasticity publication-title: J Econ – volume: 95 start-page: 209 year: 2007 end-page: 219 ident: b0060 article-title: Time series analysis of wind speed using VAR and the generalized impulse response technique publication-title: J Wind Eng Ind Aerodynam – volume: 17 start-page: 419 year: 2002 end-page: 424 ident: b0120 article-title: Financial volatility: an introduction publication-title: J Appl Economet – reference: > [accessed July 2010]. – volume: 6 start-page: 461 year: 1978 end-page: 464 ident: b0180 article-title: Estimating the dimension of a model publication-title: Ann Stat – volume: 32 start-page: 2116 year: 2007 end-page: 2128 ident: b0025 article-title: Wind speed forecasting in the south coast of Oaxaca, Mexico publication-title: Renew Energy – reference: Li G, Shi J. Bayesian adaptive combination of short-term wind speed forecasts from neural network models. Renew Energy; 2010. – reference: World Wind Energy Association. World Wind Energy Report; 2009. < – volume: 31 start-page: 1759 year: 2009 end-page: 1769 ident: b0115 article-title: Modeling wind speed and time-varying turbulence in geographically dispersed wind energy markets in China publication-title: Energy Sources, Part A: Recovery, Utiliz, Environ Effects – volume: XLI start-page: 478 year: 2003 end-page: 539 ident: b0155 article-title: Forecasting volatility in financial markets: a review publication-title: J Econ Literature – year: 2009 ident: b0015 article-title: Physical approach to short term wind power prediction – volume: 48 start-page: 1749 year: 1993 end-page: 1778 ident: b0130 article-title: Measuring and testing the impact of news on volatility publication-title: J Finance – reference: > [accessed March 2010]. – volume: 21 start-page: 23 year: 2000 end-page: 35 ident: b0045 article-title: A comparison of various forecasting techniques applied to mean hourly wind speed time series publication-title: Renew Energy – reference: American Wind Energy Association, 2010, Year End 2009 Market Report. < – volume: 50 start-page: 987 year: 1982 end-page: 1000 ident: b0095 article-title: Autoregressive conditional heteroscedasticity with estimates of variance of United Kingdom inflation publication-title: Econometrica – volume: 48 start-page: 1779 year: 1993 end-page: 1801 ident: b0145 article-title: On the relationship between the expected value and the volatility of the nominal excess returns on stocks publication-title: J Finance – volume: 87 start-page: 2313 year: 2010 end-page: 2320 ident: b0050 article-title: On comparing three artificial neural networks for wind speed forecasting publication-title: Appl Energy – volume: 17 start-page: 119 year: 2006 end-page: 127 ident: b0110 article-title: Time series analysis of wind speed with time-varying turbulence publication-title: Environmetrics – volume: 15 start-page: 157 year: 2001 end-page: 168 ident: b0080 article-title: GARCH 101: the use of ARCH/GARCH models in applied econometrics publication-title: J Econ Perspect – volume: 63 start-page: 61 year: 1998 end-page: 68 ident: b0040 article-title: Short term forecasting of wind speed and related electrical power publication-title: Sol Energy – volume: 13 start-page: 915 year: 2009 end-page: 920 ident: b0070 article-title: A review on the forecasting of wind speed and generated power publication-title: Renew Sustain Energy Rev – volume: 59 start-page: 347 year: 1991 end-page: 370 ident: b0135 article-title: Conditional heteroskedasticity in asset returns: a new approach publication-title: Econometrica – volume: 65 start-page: 297 year: 1978 end-page: 303 ident: b0185 article-title: On a measure of a lack of fit in time series models publication-title: Biometrika – volume: 3 start-page: 340 year: 2008 end-page: 347 ident: b0085 article-title: Analysis of time-varying turbulence in geographically-dispersed wind energy markets publication-title: Energy Sources, Part B: Econ, Plan, Policy – volume: 10 start-page: 229 year: 1992 end-page: 235 ident: b0150 article-title: Inequality constraints in the univariate GARCH model publication-title: J Business Econ Stat – reference: . – reference: Verbeek M. A guide to modern econometrics. 2rd version, John Wiley & Sons Inc.; 2004. p. 31, 285–8. – volume: 16 start-page: 449 issue: 5 year: 2005 ident: 10.1016/j.apenergy.2010.09.028_b0030 article-title: Modeling and predicting complex space-time structures and patterns of coastal wind fields publication-title: Environmetrics doi: 10.1002/env.714 – volume: 50 start-page: 987 year: 1982 ident: 10.1016/j.apenergy.2010.09.028_b0095 article-title: Autoregressive conditional heteroscedasticity with estimates of variance of United Kingdom inflation publication-title: Econometrica doi: 10.2307/1912773 – volume: 41 start-page: 478 issue: 2 year: 2003 ident: 10.1016/j.apenergy.2010.09.028_b0125 article-title: Forecasting volatility in financial markets: a review publication-title: J Econ Literature, Amer Econ Assoc doi: 10.1257/.41.2.478 – volume: 79 start-page: 65 issue: 1 year: 2005 ident: 10.1016/j.apenergy.2010.09.028_b0020 article-title: Forecast of hourly average wind speed with Arma models in Navarre (Spain) publication-title: Sol Energy doi: 10.1016/j.solener.2004.09.013 – year: 1960 ident: 10.1016/j.apenergy.2010.09.028_b0160 – volume: 95 start-page: 209 issue: 3 year: 2007 ident: 10.1016/j.apenergy.2010.09.028_b0060 article-title: Time series analysis of wind speed using VAR and the generalized impulse response technique publication-title: J Wind Eng Ind Aerodynam doi: 10.1016/j.jweia.2006.06.001 – volume: 31 start-page: 307 year: 1986 ident: 10.1016/j.apenergy.2010.09.028_b0100 article-title: Generalized autoregressive conditional heteroskedasticity publication-title: J Econ doi: 10.1016/0304-4076(86)90063-1 – volume: 32 start-page: 2116 issue: 12 year: 2007 ident: 10.1016/j.apenergy.2010.09.028_b0025 article-title: Wind speed forecasting in the south coast of Oaxaca, Mexico publication-title: Renew Energy doi: 10.1016/j.renene.2006.10.005 – volume: 3 start-page: 340 year: 2008 ident: 10.1016/j.apenergy.2010.09.028_b0085 article-title: Analysis of time-varying turbulence in geographically-dispersed wind energy markets publication-title: Energy Sources, Part B: Econ, Plan, Policy doi: 10.1080/15567240701232162 – volume: 59 start-page: 347 year: 1991 ident: 10.1016/j.apenergy.2010.09.028_b0135 article-title: Conditional heteroskedasticity in asset returns: a new approach publication-title: Econometrica doi: 10.2307/2938260 – ident: 10.1016/j.apenergy.2010.09.028_b0010 – volume: 10 start-page: 229 year: 1992 ident: 10.1016/j.apenergy.2010.09.028_b0150 article-title: Inequality constraints in the univariate GARCH model publication-title: J Business Econ Stat doi: 10.1080/07350015.1992.10509902 – volume: 21 start-page: 23 issue: 1 year: 2000 ident: 10.1016/j.apenergy.2010.09.028_b0045 article-title: A comparison of various forecasting techniques applied to mean hourly wind speed time series publication-title: Renew Energy doi: 10.1016/S0960-1481(99)00125-1 – volume: 46 start-page: 1293 year: 1978 ident: 10.1016/j.apenergy.2010.09.028_b0195 article-title: Testing against general autoregressive and moving average error models when the regressors include lagged dependent variables publication-title: Econometrica doi: 10.2307/1913829 – volume: 56 start-page: 301 year: 1995 ident: 10.1016/j.apenergy.2010.09.028_b0035 article-title: Stochastic simulation of hourly average wind speed sequences in Tangiers (Morocco) publication-title: Sol Energy doi: 10.1016/0038-092X(95)00103-X – ident: 10.1016/j.apenergy.2010.09.028_b0175 – ident: 10.1016/j.apenergy.2010.09.028_b0005 – volume: 31 start-page: 1759 issue: 19 year: 2009 ident: 10.1016/j.apenergy.2010.09.028_b0115 article-title: Modeling wind speed and time-varying turbulence in geographically dispersed wind energy markets in China publication-title: Energy Sources, Part A: Recovery, Utiliz, Environ Effects doi: 10.1080/15567030802462267 – volume: 48 start-page: 1749 issue: 5 year: 1993 ident: 10.1016/j.apenergy.2010.09.028_b0130 article-title: Measuring and testing the impact of news on volatility publication-title: J Finance doi: 10.1111/j.1540-6261.1993.tb05127.x – year: 2009 ident: 10.1016/j.apenergy.2010.09.028_b0015 – volume: 62 start-page: 639 year: 1995 ident: 10.1016/j.apenergy.2010.09.028_b0140 article-title: Quadratic arch models publication-title: Rev Econ Studies doi: 10.2307/2298081 – volume: 17 start-page: 119 year: 2006 ident: 10.1016/j.apenergy.2010.09.028_b0110 article-title: Time series analysis of wind speed with time-varying turbulence publication-title: Environmetrics doi: 10.1002/env.754 – volume: 8 start-page: 1071 year: 1980 ident: 10.1016/j.apenergy.2010.09.028_b0170 article-title: The estimation of the order of an ARMA process publication-title: Ann Stat doi: 10.1214/aos/1176345144 – volume: 48 start-page: 1779 year: 1993 ident: 10.1016/j.apenergy.2010.09.028_b0145 article-title: On the relationship between the expected value and the volatility of the nominal excess returns on stocks publication-title: J Finance doi: 10.1111/j.1540-6261.1993.tb05128.x – volume: 6 start-page: 461 year: 1978 ident: 10.1016/j.apenergy.2010.09.028_b0180 article-title: Estimating the dimension of a model publication-title: Ann Stat doi: 10.1214/aos/1176344136 – volume: 96 start-page: 2348 issue: 12 year: 2008 ident: 10.1016/j.apenergy.2010.09.028_b0055 article-title: Improvements in wind speed forecasts for wind power prediction purposes using Kalman filtering publication-title: J Wind Eng Ind Aerodynam doi: 10.1016/j.jweia.2008.03.013 – ident: 10.1016/j.apenergy.2010.09.028_b0075 doi: 10.1016/j.renene.2010.06.049 – volume: 56 start-page: 113 issue: 1–2 year: 1997 ident: 10.1016/j.apenergy.2010.09.028_b0105 article-title: Autoregressive conditional heteroscedasticity in daily wind speed measurements publication-title: Theor Appl Climatol doi: 10.1007/BF00863788 – volume: 65 start-page: 297 issue: 2 year: 1978 ident: 10.1016/j.apenergy.2010.09.028_b0185 article-title: On a measure of a lack of fit in time series models publication-title: Biometrika doi: 10.1093/biomet/65.2.297 – volume: 87 start-page: 2313 year: 2010 ident: 10.1016/j.apenergy.2010.09.028_b0050 article-title: On comparing three artificial neural networks for wind speed forecasting publication-title: Appl Energy doi: 10.1016/j.apenergy.2009.12.013 – volume: 17 start-page: 334 issue: 31 year: 1978 ident: 10.1016/j.apenergy.2010.09.028_b0190 article-title: Testing for autocorrelation in dynamic linear models publication-title: Aust Econ Papers doi: 10.1111/j.1467-8454.1978.tb00635.x – ident: 10.1016/j.apenergy.2010.09.028_b0065 – ident: 10.1016/j.apenergy.2010.09.028_b0165 – volume: 63 start-page: 61 issue: 1 year: 1998 ident: 10.1016/j.apenergy.2010.09.028_b0040 article-title: Short term forecasting of wind speed and related electrical power publication-title: Sol Energy doi: 10.1016/S0038-092X(98)00032-2 – volume: 13 start-page: 915 issue: 4 year: 2009 ident: 10.1016/j.apenergy.2010.09.028_b0070 article-title: A review on the forecasting of wind speed and generated power publication-title: Renew Sustain Energy Rev doi: 10.1016/j.rser.2008.02.002 – volume: 15 start-page: 157 issue: 4 year: 2001 ident: 10.1016/j.apenergy.2010.09.028_b0080 article-title: GARCH 101: the use of ARCH/GARCH models in applied econometrics publication-title: J Econ Perspect doi: 10.1257/jep.15.4.157 – volume: 31 start-page: 1194 issue: 13 year: 2009 ident: 10.1016/j.apenergy.2010.09.028_b0090 article-title: Further evidence on modeling wind speed and time-varying turbulence publication-title: Energy Sources, Part A: Recovery, Utiliz, Environ Effects doi: 10.1080/15567030801911223 – volume: XLI start-page: 478 year: 2003 ident: 10.1016/j.apenergy.2010.09.028_b0155 article-title: Forecasting volatility in financial markets: a review publication-title: J Econ Literature doi: 10.1257/.41.2.478 – volume: 17 start-page: 419 issue: 5 year: 2002 ident: 10.1016/j.apenergy.2010.09.028_b0120 article-title: Financial volatility: an introduction publication-title: J Appl Economet doi: 10.1002/jae.693
SSID	ssj0002120
Score	2.426556
Snippet	Accurately modeling the mean and volatility of wind speed can be beneficial to effective wind energy utilization. For this purpose, this paper evaluates the...
SourceID	proquest repec pascalfrancis crossref fao elsevier
SourceType	Aggregation Database Index Database Enrichment Source Publisher
StartPage	724
SubjectTerms	Applied sciences ARMA Asymmetry Colorado data collection Deterioration Energy Energy utilization Exact sciences and technology Forecasting GARCH GARCH-M heteroskedasticity Mathematical models Natural energy Nonlinearity Trends Volatility Wind energy Wind power generation Wind speed Wind speed Forecasting ARMA GARCH GARCH-M
Title	Comprehensive evaluation of ARMA–GARCH(-M) approaches for modeling the mean and volatility of wind speed
URI	https://dx.doi.org/10.1016/j.apenergy.2010.09.028 http://econpapers.repec.org/article/eeeappene/v_3a88_3ay_3a2011_3ai_3a3_3ap_3a724-732.htm https://www.proquest.com/docview/1663632246 https://www.proquest.com/docview/1777136831 https://www.proquest.com/docview/855718151
Volume	88
WOSCitedRecordID	wos000285217400017&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
hasFullText	1
inHoldings	1
isFullTextHit
isPrint
journalDatabaseRights	– providerCode: PRVESC databaseName: Elsevier SD Freedom Collection Journals 2021 customDbUrl: eissn: 1872-9118 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0002120 issn: 0306-2619 databaseCode: AIEXJ dateStart: 19950101 isFulltext: true titleUrlDefault: https://www.sciencedirect.com providerName: Elsevier
link	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV3Nb9MwFLe6lgM7IBhMKx-TkTiAUEYaJ7FzrKbyMdEJsU3qzXISe2vVplG_GDdO_AP8h_wlPCd20gLb2IGD3SpyLCfv5_eV954ReuH6AgwJP3EE8ZTjx17giEDFjmKhTFSqEukXicIf6fExGwyiT43Gd5sLsxrTLGOXl1H-X0kN14DYOnX2FuSuJoUL8B-IDj2QHfp_Irze4TN5YQLT62rehc75ud-14Q3knf5QBAqm09euAVtcXBYFGsoTcmwq1US767WHHXgZzDU2YRxfhtrpnsvNwz6tXiuLrMIq4Ge4LKVcbmWlVuNnqZyU3Ph8WKH0pDhn-PWRHZjWTlYblGVzsdzQ0bbZOp9lbA1PZI1p0jKL2shfWvo7_2DtpZdhdCDycv0mLC86cE12-UYt7d9kXBV5aIPaRtzOw_U83I04zLOFWh4NItZEre6H3uCokumeKfBpn2st1_zvK7pKzdlSYqrjb8UctqAqz07ZMG5aM5nLZE3HOb2P7hnjBHdLUD1ADZntoO21kpU7aLdXZ0bCUCMa5g_RaAN3uMYdniqscffz248CcS-d_itcow0D2rBFGwa0YY02DGjDNdr0HBptuEDbI3T2tnd6-N4xB3k4CdirCyeMJInjJAgjGlMRSzeKOzRWSviJTwXz0jSWJIzdJBSR9KSv3FgJ6nppxAKfKEV2UTObZnIPYQIWi-frso0q9T0B6rarQrCZaUcqN4g7bRTY984TU-VeH7Yy5tdTvo3eVPflZZ2XG--ILFm50VZLLZQDYm-8dw9wwMU5CHJ-duJpt6NW_sHcaKP9DXBUqwHd2gtA5Wyj5xYtHESB_r4nMjldznkHrIeQ6AqR14yhlHZIyAi8KXzFGBYEoLGCKdBGhwUaqzVIKQEf8Dx8xYlgDLqv0DQLgJ8hNAIthwZ7msNO5heLyeNbv9on6G7NVZ6i5mK2lM_QnWS1GM5n-2Zv_gLA2Qd3
linkProvider	Elsevier
openUrl	ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Comprehensive+evaluation+of+ARMA%E2%80%93GARCH%28-M%29+approaches+for+modeling+the+mean+and+volatility+of+wind+speed&rft.jtitle=Applied+energy&rft.au=Liu%2C+Heping&rft.au=Erdem%2C+Ergin&rft.au=Shi%2C+Jing&rft.date=2011-03-01&rft.issn=0306-2619&rft.volume=88&rft.issue=3&rft.spage=724&rft.epage=732&rft_id=info:doi/10.1016%2Fj.apenergy.2010.09.028&rft.externalDBID=n%2Fa&rft.externalDocID=10_1016_j_apenergy_2010_09_028
thumbnail_l	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0306-2619&client=summon
thumbnail_m	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0306-2619&client=summon
thumbnail_s	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0306-2619&client=summon