Demonstrating measure-correlate-predict algorithms for estimation of wind resources in central Finland

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Show simple item record Saengyuenyongpipat, Paitoon 2010-04-19T04:04:29Z 2010-04-19T04:04:29Z 2010
dc.identifier.uri en
dc.description.abstract In 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.extent 37 sivua
dc.language.iso eng
dc.rights This publication is copyrighted. You may download, display and print it for Your own personal use. Commercial use is prohibited. en
dc.rights Julkaisu on tekijänoikeussäännösten alainen. Teosta voi lukea ja tulostaa henkilökohtaista käyttöä varten. Käyttö kaupallisiin tarkoituksiin on kielletty. fi
dc.rights openAccess fi
dc.subject.other Measure-Correlate-Predict (MCP) algorithms
dc.subject.other wind energy
dc.subject.other weibull distribution
dc.title Demonstrating measure-correlate-predict algorithms for estimation of wind resources in central Finland
dc.identifier.urn URN:NBN:fi:jyu-201004191537
dc.subject.ysa tuulienergia
dc.type.dcmitype Text en
dc.type.ontasot Pro gradu fi
dc.type.ontasot Master’s thesis en
dc.contributor.tiedekunta matemaattis-luonnontieteellinen tiedekunta fi
dc.contributor.tiedekunta Faculty of Sciences en
dc.contributor.laitos fysiikan laitos fi
dc.contributor.laitos Department of Physics en
dc.contributor.yliopisto University of Jyväskylä en
dc.contributor.yliopisto Jyväskylän yliopisto fi

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