Näytä suppeat kuvailutiedot

dc.contributor.authorSaengyuenyongpipat, Paitoon
dc.date.accessioned2010-04-19T04:04:29Z
dc.date.available2010-04-19T04:04:29Z
dc.date.issued2010
dc.identifier.otheroai:jykdok.linneanet.fi:1126786
dc.identifier.urihttps://jyx.jyu.fi/handle/123456789/23245
dc.description.abstractIn this study, measure-correlate-predict (MCP) algorithms - Simple Linear Regression and Variance Ratio Methods - for predicting wind speed were studied. The MCP algorithms were successfully used to predict missing wind speeds at two sites in Jyväskylä and Viitasaari, respectively. These two algorithms used data from one of the site to predict missing wind speed data at the other site. The results obtained using the MCP methods were compared using metrics that showed the characteristics of the predicted data to be unbiased compared to measured data. From the data of this study, we also evaluated wind power density at both sites which categorized the local wind resources as poor since the determined wind power densities were less than 100 W/m2.
dc.format.extent37 sivua
dc.language.isoeng
dc.rightsThis publication is copyrighted. You may download, display and print it for Your own personal use. Commercial use is prohibited.en
dc.rightsJulkaisu on tekijänoikeussäännösten alainen. Teosta voi lukea ja tulostaa henkilökohtaista käyttöä varten. Käyttö kaupallisiin tarkoituksiin on kielletty.fi
dc.subject.otherMeasure-Correlate-Predict (MCP) algorithms
dc.subject.otherwind energy
dc.subject.otherweibull distribution
dc.titleDemonstrating measure-correlate-predict algorithms for estimation of wind resources in central Finland
dc.identifier.urnURN:NBN:fi:jyu-201004191537
dc.type.dcmitypeTexten
dc.type.ontasotPro gradufi
dc.type.ontasotMaster’s thesisen
dc.contributor.tiedekuntaMatemaattis-luonnontieteellinen tiedekuntafi
dc.contributor.tiedekuntaFaculty of Sciencesen
dc.contributor.laitosFysiikan laitosfi
dc.contributor.laitosDepartment of Physicsen
dc.contributor.yliopistoUniversity of Jyväskyläen
dc.contributor.yliopistoJyväskylän yliopistofi
dc.rights.accesslevelopenAccessfi
dc.contributor.oppiainekoodi402
dc.subject.ysotuulienergia


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Näytä suppeat kuvailutiedot