Quantifying the effect of vortex generator installation on wind power production: An academia-industry case study

Hoon Hwangbo, Yu Ding, Oliver Eisele, Guido Weinzierl, Ulrich Lang and Georgios Pechlivanoglou

Renewable Energy, 2017, vol. 113, issue C, 1589-1597

Abstract: This paper presents an academia-industry joint study concerning effective methods to estimate and quantify the effect of vortex generator installation on wind power production. This problem has presented a challenge to the wind industry, because (a) vortex generator installation may lead to a moderate 1–5% extra power production, but this level of improvement is difficult to be accurately detected; and (b) it is equally difficult to validate the estimated effect of vortex generator installation because a controlled experiment is practically impossible to conduct to provide a credible baseline. An academic institute and a wind technology company team up to tackle this challenge. The two teams develop their own version of quantification methods, which are profoundly different. The academic method uses 10-min data and makes use of both power and environmental data, whereas the company method uses high-frequency data via primarily a direct power comparison approach that relies less on the environmental data. When applying the respective methods to two inland wind farms, each of which presents four pairs of turbines, the quantification results from the two methods are surprisingly consistent. We believe the consistent outcome presents a strong case of cross validation, testifying to the respective method's capability and credibility.

Keywords: Machine learning; Power curve; Power versus power; Statistical analysis; Vortex generator (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (19)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:113:y:2017:i:c:p:1589-1597

DOI: 10.1016/j.renene.2017.07.009

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