Designing an index for assessing wind energy potential. (November 2015)

• Record Type: Journal Article
• Authors: Ritter, Matthias; Shen, Zhiwei; López Cabrera, Brenda; Odening, Martin; Deckert, Lars
• Is Part Of: Renewable energy. Volume 83(2015)
• Page Start: 416
• Page End: 424
• Publication Date: 2015-11
• Subjects: Wind power -- Energy production -- Renewable energy -- Onshore wind -- MERRA; Renewable energy sources -- Periodicals; Power resources -- Periodicals; Énergies renouvelables -- Périodiques; Ressources énergétiques -- Périodiques; 333.794
• DOI: 10.1016/j.renene.2015.04.038
• Languages: English
• ISSNs: 0960-1481

Abstract

Abstract: 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. Highlights: We suggest a new approach to assess the local wind energy potential. Long-term low-scale wind speed data at turbine position are derived from MERRA data. A five-parameter logistic function converts wind speeds into production. The wind energy index allows for an estimation of the expected wind power generation.