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Mapping key economic indicators of onshore wind energy in Sweden by using a geospatial methodology
KTH, School of Industrial Engineering and Management (ITM), Energy Technology, Energy Systems Analysis.
KTH, School of Industrial Engineering and Management (ITM), Energy Technology, Energy Systems Analysis.
KTH, School of Industrial Engineering and Management (ITM), Energy Technology, Energy Systems Analysis.
2016 (English)In: Energy Conversion and Management, ISSN 0196-8904, E-ISSN 1879-2227, Vol. 128, 211-226 p.Article in journal (Refereed) Published
Abstract [en]

Due to modern advancements in renewable energy systems and increasing prices of fossil fuels wind energy is getting a lot of attention all over the world. In this regard, Sweden also fixed motivated targets to get energy supply from local renewable energy resources. So, local wind power could help the country in achieving the targets. In this study, economic indicators of wind energy were spatially estimated for Sweden by using ArcGIS tool. In order to do this, as input data one-year high resolution modeled annual average wind data was processed by means of Rayleigh distribution, wind turbine power curve, land use constraints, technical constraints and economic parameters. Based on the input data, it was concluded that Sweden possesses economically feasible wind energy resource. The results of the study indicate that southern and central regions could produce economically viable wind electricity in all aspects as compared to the northern region of the country. Lastly, it was recommended to speed up wind energy penetration in Sweden, communal awareness and acceptance regarding the resource should be increased to avoid possible misunderstanding. Additionally, the capability of the national electric grid should be enhanced to take up the large scale unpredictable wind energy resource.

Place, publisher, year, edition, pages
Elsevier, 2016. Vol. 128, 211-226 p.
Keyword [en]
Economic, GIS, Indicators, Spatial, Wind electricity, Economics, Energy resources, Fossil fuels, Geographic information systems, Indicators (instruments), Input output programs, Land use, Renewable energy resources, Wind effects, Wind power, Wind turbines, Economic indicators, Economic parameters, Economically viable, Rayleigh distributions, Renewable energy systems, Technical constraints, Economic analysis
National Category
Energy Engineering
Identifiers
URN: urn:nbn:se:kth:diva-195204DOI: 10.1016/j.enconman.2016.09.055ISI: 000388047800019ScopusID: 2-s2.0-84989227706OAI: oai:DiVA.org:kth-195204DiVA: diva2:1051728
Note

QC 20161202

Available from: 2016-12-02 Created: 2016-11-02 Last updated: 2016-12-14Bibliographically approved

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