Designing an Index forAssessing Wind EnergyPotential
Ritter, Matthias
Shen, Zhiwei
Cabrera, Brenda López
Odening, Martin
Deckert, Lars
To meet the increasing global demand for renewable energy such as wind energy, more and more new wind parks are installed worldwide. Finding a suitable location, however, requires a detailed and often costly analysis of the 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. In this paper, we suggest a new approach of assessing the local wind energy potential: Meteorological reanalysis data are applied to obtain long-term low-scale wind speed data at turbine location and hub height; then, with actual high-frequency production data, the relation between wind data and energy production is determined via a five parameter logistic function. The resulting wind energy index allows for a turbine-specific estimation of the expected wind power at an unobserved location. A map of wind power potential for whole Germany exemplifies the approach.
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