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Application of an h-adaptive finite element model for wind energy assessment in Nevada

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  • Pepper, Darrell W.
  • Wang, Xiuling

Abstract

A multiscale modeling project for wind energy assessment in central Nevada has been conducted. The PSU/NCAR fifth-generation Mesoscale Model (MM5) was used in conjunction with an h-adaptive finite element model and local tower data for a 1-year cycle for the central region. The MM5 results and the local tower data are used as input into the microscale h-adaptive FEM model. The h-adaptive module permits resolution down to meter levels, allowing more accurate details regarding topographic features and wind velocity vectors. Multiscale results for assessing wind energy potential are presented in the form of monthly averaged wind power density maps. Potential locations for establishing wind farms in the region are discussed.

Suggested Citation

  • Pepper, Darrell W. & Wang, Xiuling, 2007. "Application of an h-adaptive finite element model for wind energy assessment in Nevada," Renewable Energy, Elsevier, vol. 32(10), pages 1705-1722.
    • Handle: RePEc:eee:renene:v:32:y:2007:i:10:p:1705-1722
    DOI: 10.1016/j.renene.2006.08.011
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    Cited by:

    1. Darrell Pepper & Xiuling Wang, 2008. "A self-adapting model for assessing hazardous environmental releases," 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. 44(3), pages 387-397, March.
    2. Salcedo-Sanz, Sancho & Ángel M. Pérez-Bellido, & Ortiz-García, Emilio G. & Portilla-Figueras, Antonio & Prieto, Luis & Paredes, Daniel, 2009. "Hybridizing the fifth generation mesoscale model with artificial neural networks for short-term wind speed prediction," Renewable Energy, Elsevier, vol. 34(6), pages 1451-1457.
    3. Angelis-Dimakis, Athanasios & Biberacher, Markus & Dominguez, Javier & Fiorese, Giulia & Gadocha, Sabine & Gnansounou, Edgard & Guariso, Giorgio & Kartalidis, Avraam & Panichelli, Luis & Pinedo, Irene, 2011. "Methods and tools to evaluate the availability of renewable energy sources," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(2), pages 1182-1200, February.
    4. de la Rosa, Juan José González & Pérez, Agustín Agüera & Palomares Salas, José Carlos & Ramiro Leo, José Gabriel & Muñoz, Antonio Moreno, 2011. "A novel inference method for local wind conditions using genetic fuzzy systems," Renewable Energy, Elsevier, vol. 36(6), pages 1747-1753.
    5. Wu, Jie & Wang, Jianzhou & Chi, Dezhong, 2013. "Wind energy potential assessment for the site of Inner Mongolia in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 21(C), pages 215-228.

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