Impact of near-future turbine technology on the wind power potential of low wind regions

Sean Martin, Sungmoon Jung and Arda Vanli

Applied Energy, 2020, vol. 272, issue C, No S0306261920307637

Abstract: Near-future wind turbines – with increased hub heights, larger rotors, and improved energy capture methods – have the potential to bring wind power to previously undeveloped low wind regions. To date, however, little published research has been completed for these less profitable locations. This research studies the wind resource characteristics of low wind sites to determine the impact of near-future turbine technologies on wind energy potential. Histograms of hourly wind speed data at nine Florida sites, for the period 2005–2014, were compared with data fit to a Modified-Weibull probability distribution. Estimates of annual energy production and turbine capacity factors were then determined for a near-future wind turbine. Histograms for the low wind sites were found to have three characteristic shapes – Type I, II and III - that are related to the annual 10 m mean wind speed and the probability that observed wind speeds are less than 4 m/s. While sites with a Type I characteristic shape benefitted the most from near-future turbine technology, sites having Type II and Type III characteristic shapes appear to be the most viable for future wind power development. Energy estimates obtained using the Modified-Weibull distribution overestimated annual energy production by 5.6%, on average, as compared to estimates obtained using histograms. Overestimation was the greatest for sites having histograms with a Type I characteristic shape, 8.0% on average, and the least for sites having a Type III characteristic shape, 2.8% on average. Characteristic shapes can be useful to analyze the wind power potential at low wind sites.

Keywords: Wind power; Low wind region; Florida; Weibull distribution; Wind energy potential; Wind resource assessment (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (9)

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DOI: 10.1016/j.apenergy.2020.115251

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