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Designing an index for assessing wind energy potential
Humboldt-Universität zu Berlin, Department of Agricultural Economics, Berlin, Germany.ORCID iD: 0000-0003-2543-3673
Humboldt-Universität zu Berlin, Department of Agricultural Economics, Berlin, Germany.
Humboldt-Universität zu Berlin, School of Business and Economics, Ladislaus von Bortkiewicz Chair of Statistics, Berlin, Germany.
Humboldt-Universität zu Berlin, Department of Agricultural Economics, Berlin, Germany.
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2015 (English)In: Renewable energy, ISSN 0960-1481, E-ISSN 1879-0682, Vol. 83, p. 416-424Article in journal (Refereed) Published
Abstract [en]

To meet the increasing global demand for renewable energy, such as wind energy, an increasing number of wind parks are being constructed worldwide. Finding a suitable location requires a detailed and often costly analysis of local wind conditions. Plain average wind speed maps cannot provide a precise forecast of wind power because of the non-linear relationship between wind speed and production. We suggest a new approach to assess the local wind energy potential. First, meteorological reanalysis data are applied to obtain long-term low-scale wind speed data at specific turbine locations and hub heights. Second, the relation between wind data and energy production is determined via a five parameter logistic function using actual high-frequency energy production data. The resulting wind energy index allows for a turbine-specific estimation of the expected wind power at an unobserved location. A map of the wind power potential for Germany exemplifies our approach.

Place, publisher, year, edition, pages
Elsevier, 2015. Vol. 83, p. 416-424
Keywords [en]
Energy production, MERRA, Onshore wind, Renewable energy, Wind power, Location, Wind, Energy productions, Five parameter logistic, High frequency HF, Non-linear relationships, Onshore winds, Renewable energies, Wind energy index, power generation, renewable resource, wind farm, wind turbine, wind velocity, Germany
National Category
Economics Energy Engineering
Identifiers
URN: urn:nbn:se:hj:diva-54527DOI: 10.1016/j.renene.2015.04.038ISI: 000358455100039Scopus ID: 2-s2.0-84929309116OAI: oai:DiVA.org:hj-54527DiVA, id: diva2:1614628
Available from: 2021-11-26 Created: 2021-11-26 Last updated: 2021-11-26Bibliographically approved

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Ritter, Matthias

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