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dc.contributor.advisorBirkelund, Yngve
dc.contributor.authorFossem, Anders Aarhuus
dc.date.accessioned2020-01-29T08:45:46Z
dc.date.available2020-01-29T08:45:46Z
dc.date.issued2019-12-13
dc.description.abstractThe need for energy increases globally due to rapid expansion of population and prosperity. To meet this demand while decreasing carbon emission and eventually transition out fossil fuel, efficient utilization of wind power is prominent. This study evaluates the performance of the Weather Research and Forecast model (WRF) with respect to wind speed and wind direction. The area of the study is the northernmost wind farm site in the world, Havøygavlen. It is located just about 50 kilometers southwest of the North cape, consisting of a complex and coastal terrain. The model simulation period was the entire year of 2017, and the resulting estimates where compared to on-site data measured at hub height at each of the 16 turbines located at the site. In terms of forecasting capability, the Model was evaluated using correlation, Root Mean Square Error and Bias. The assessment showed little agreement and implementing finer resolution displayed no apparent improvements. The estimate was particularly vulnerable to sudden changes in wind speed, and performed more accurately in periods of low to moderate wind speeds. Annual weather resource assessment of the site was performed using box plots, annual average wind maps and wind speed histograms. The model is unsuccessful at capturing the high complexity of the terrain, ultimately leading to an underestimation of the wind resources. However, enhanced domain resolution improved the predictive performance, which agreed adequately with the on-site measurements. Furthermore, the annual average wind maps provided valuable knowledge about the local wind patterns surrounding the site. Annual wind roses and wind fields at specific times of high wind speed occurrence was used to evaluate the model’s estimated wind direction. Enhanced domain resolution showed improved directional stability and ability to capture the terrain’s effect on the wind before arriving at the site. As a preliminary wind resource tool, the model performs sufficiently, despite the complex terrain of the studied area.en_US
dc.identifier.urihttps://hdl.handle.net/10037/17252
dc.language.isoengen_US
dc.publisherUiT The Arctic University of Norwayen_US
dc.publisherUiT Norges arktiske universiteten_US
dc.rights.accessRightsopenAccessen_US
dc.rights.holderCopyright 2019 The Author(s)
dc.rights.urihttps://creativecommons.org/licenses/by-nc-sa/4.0en_US
dc.rightsAttribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)en_US
dc.subject.courseIDEOM-3901
dc.subjectVDP::Mathematics and natural science: 400::Information and communication science: 420::Mathematical modeling and numerical methods: 427en_US
dc.subjectVDP::Matematikk og Naturvitenskap: 400::Informasjons- og kommunikasjonsvitenskap: 420::Matematisk modellering og numeriske metoder: 427en_US
dc.subjectWind resource mappingen_US
dc.subjectNumerical weather modelsen_US
dc.subjectWRFen_US
dc.subjectWind in complex terrainen_US
dc.subjectVDP::Technology: 500::Environmental engineering: 610en_US
dc.subjectVDP::Teknologi: 500::Miljøteknologi: 610en_US
dc.subjectRenewable energyen_US
dc.subjectWind poweren_US
dc.subjectWind power productionen_US
dc.titleWind resource assessment using weather research and forecasting model. A case study of the wind resources at Havøygavlen wind farmen_US
dc.typeMaster thesisen_US
dc.typeMastergradsoppgaveen_US


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Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
Med mindre det står noe annet, er denne innførselens lisens beskrevet som Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)