Optimization of wind turbine location in urban environment

Making energy clean, reliable and readily available is essential for fighting climate change and to supply an ever-rising global power demand. The aim of the study is to identify optimal locations for a wind turbine to be joined to a small-scale hybrid system at the main campus of UiT – The Arctic U...

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Bibliographic Details
Main Author: Hågbo, Trond-Ola
Format: Master Thesis
Language:English
Published: UiT The Arctic University of Norway 2017
Subjects:
Online Access:https://hdl.handle.net/10037/11620
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spelling ftunivtroemsoe:oai:munin.uit.no:10037/11620 2023-05-15T15:55:39+02:00 Optimization of wind turbine location in urban environment Hågbo, Trond-Ola 2017-06-01 https://hdl.handle.net/10037/11620 eng eng UiT The Arctic University of Norway UiT Norges arktiske universitet https://hdl.handle.net/10037/11620 openAccess Copyright 2017 The Author(s) VDP::Matematikk og Naturvitenskap: 400::Fysikk: 430 VDP::Mathematics and natural science: 400::Physics: 430 VDP::Teknologi: 500::Miljøteknologi: 610 VDP::Technology: 500::Environmental engineering: 610 Renewable energy Wind turbine Computational fluid dynamics Geographical information system EOM-3901 Master thesis Mastergradsoppgave 2017 ftunivtroemsoe 2021-06-25T17:55:25Z Making energy clean, reliable and readily available is essential for fighting climate change and to supply an ever-rising global power demand. The aim of the study is to identify optimal locations for a wind turbine to be joined to a small-scale hybrid system at the main campus of UiT – The Arctic University of Norway. To identify feasible areas for maximizing electric power production, techniques originating from two quite different disciplines are utilized: Geographical Information System and Computational Fluid Dynamics. Local weather data and detailed 3D-models are used as inputs to the wind simulations. Two optimal wind turbine locations are proposed with the following UTM-33N coordinates: (654053 – 7735418) at Realfagsbygget and (653410 - 7736185) at Grønnåsen. To further study the power production capability at Grønnåsen wind sensors were installed in the Avinor mast, 200 m east of the suggested optimal location. Here the average wind speed and power density at 21 m above ground level was calculated to be 4.22 m/s and 135.4 W/m^2 corresponding to the period of mid-February to mid-May 2017. For both the suggested optimal locations of a wind turbine, more weather data is necessary to accurately estimate the annual wind speed and power density averages. Master Thesis Climate change Arctic University of Norway UiT The Arctic University of Norway University of Tromsø: Munin Open Research Archive Arctic Norway Grønnåsen ENVELOPE(13.288,13.288,65.615,65.615)
institution Open Polar
collection University of Tromsø: Munin Open Research Archive
op_collection_id ftunivtroemsoe
language English
topic VDP::Matematikk og Naturvitenskap: 400::Fysikk: 430
VDP::Mathematics and natural science: 400::Physics: 430
VDP::Teknologi: 500::Miljøteknologi: 610
VDP::Technology: 500::Environmental engineering: 610
Renewable energy
Wind turbine
Computational fluid dynamics
Geographical information system
EOM-3901
spellingShingle VDP::Matematikk og Naturvitenskap: 400::Fysikk: 430
VDP::Mathematics and natural science: 400::Physics: 430
VDP::Teknologi: 500::Miljøteknologi: 610
VDP::Technology: 500::Environmental engineering: 610
Renewable energy
Wind turbine
Computational fluid dynamics
Geographical information system
EOM-3901
Hågbo, Trond-Ola
Optimization of wind turbine location in urban environment
topic_facet VDP::Matematikk og Naturvitenskap: 400::Fysikk: 430
VDP::Mathematics and natural science: 400::Physics: 430
VDP::Teknologi: 500::Miljøteknologi: 610
VDP::Technology: 500::Environmental engineering: 610
Renewable energy
Wind turbine
Computational fluid dynamics
Geographical information system
EOM-3901
description Making energy clean, reliable and readily available is essential for fighting climate change and to supply an ever-rising global power demand. The aim of the study is to identify optimal locations for a wind turbine to be joined to a small-scale hybrid system at the main campus of UiT – The Arctic University of Norway. To identify feasible areas for maximizing electric power production, techniques originating from two quite different disciplines are utilized: Geographical Information System and Computational Fluid Dynamics. Local weather data and detailed 3D-models are used as inputs to the wind simulations. Two optimal wind turbine locations are proposed with the following UTM-33N coordinates: (654053 – 7735418) at Realfagsbygget and (653410 - 7736185) at Grønnåsen. To further study the power production capability at Grønnåsen wind sensors were installed in the Avinor mast, 200 m east of the suggested optimal location. Here the average wind speed and power density at 21 m above ground level was calculated to be 4.22 m/s and 135.4 W/m^2 corresponding to the period of mid-February to mid-May 2017. For both the suggested optimal locations of a wind turbine, more weather data is necessary to accurately estimate the annual wind speed and power density averages.
format Master Thesis
author Hågbo, Trond-Ola
author_facet Hågbo, Trond-Ola
author_sort Hågbo, Trond-Ola
title Optimization of wind turbine location in urban environment
title_short Optimization of wind turbine location in urban environment
title_full Optimization of wind turbine location in urban environment
title_fullStr Optimization of wind turbine location in urban environment
title_full_unstemmed Optimization of wind turbine location in urban environment
title_sort optimization of wind turbine location in urban environment
publisher UiT The Arctic University of Norway
publishDate 2017
url https://hdl.handle.net/10037/11620
long_lat ENVELOPE(13.288,13.288,65.615,65.615)
geographic Arctic
Norway
Grønnåsen
geographic_facet Arctic
Norway
Grønnåsen
genre Climate change
Arctic University of Norway
UiT The Arctic University of Norway
genre_facet Climate change
Arctic University of Norway
UiT The Arctic University of Norway
op_relation https://hdl.handle.net/10037/11620
op_rights openAccess
Copyright 2017 The Author(s)
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