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Wind and tornado climatologies and wind resource modelling for a modern development situated in “Tornado Alley”

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  • Romanic, Djordje
  • Parvu, Dan
  • Refan, Maryam
  • Hangan, Horia

Abstract

The Kansas Project aims to establish a synergetic link between people and weather, as well as to explore different ways to harness the weather for its sustainable resources. The site is located in the South Central Kansas, United States. This case study presents wind and tornado climatology analyses coupled with a wind resource assessment study for this modern development. The wind analyses are conducted using wind data from weather station located in Medicine Lodge and for the period 1984–2015. The mean annual wind speed at the site is 4.45 m s−1 at 10 m height. The north-south bi-directionality of the wind rose is very pronounced. The mean annual wind speeds have a positive, but statistically not significant trend. A 50-year return period 5-s gust of 34 m s−1 is estimated at 10 m height. The deadliest and most damaging tornadoes around the site are F3 twisters, while the most common tornadoes are F2 and weaker. The WAsP package is used to calculate the regional wind atlas for five heights and five reference roughness lengths. Wind resource grids depict good wind energy potential at 50, 80, 100 and 150 m levels. In addition, roughness and topographic uncertainties related to WAsP performance are addressed in details.

Suggested Citation

  • Romanic, Djordje & Parvu, Dan & Refan, Maryam & Hangan, Horia, 2018. "Wind and tornado climatologies and wind resource modelling for a modern development situated in “Tornado Alley”," Renewable Energy, Elsevier, vol. 115(C), pages 97-112.
    • Handle: RePEc:eee:renene:v:115:y:2018:i:c:p:97-112
    DOI: 10.1016/j.renene.2017.08.026
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    2. Romane Bouchard & Djordje Romanic, 2023. "Monte Carlo modeling of tornado hazard to wind turbines in Germany," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 116(3), pages 3899-3923, April.
    3. Mingcan Li & Hanbin Xiao & Lin Pan & Chengjun Xu, 2019. "Study of Generalized Interaction Wake Models Systems with ELM Variation for Off-Shore Wind Farms," Energies, MDPI, vol. 12(5), pages 1-32, March.

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