Market Suitability and Performance Tradeoffs Offered by Commercial Wind Turbines across Differing Wind Regimes

Souma Chowdhury, Ali Mehmani, Jie Zhang and Achille Messac
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Souma Chowdhury: Department of Mechanical and Aerospace Engineering, University at Buffalo, Buffalo, NY 14260, USA
Ali Mehmani: Lenfest Center for Sustainable Energy, Columbia University, New York, NY 10027, USA
Jie Zhang: Department of Mechanical Engineering, University of Texas at Dallas, Richardson, TX 75080, USA
Achille Messac: College of Engineering, Architecture and Computer Sciences, Howard University, Washington, DC 20059, USA

Energies, 2016, vol. 9, issue 5, 1-31

Abstract: The suitability of turbine configurations to different wind resources has been traditionally restricted to considering turbines operating as standalone entities. In this paper, a framework is thus developed to investigate turbine suitability in terms of the minimum cost of energy offered when operating as a group of optimally-micro-sited turbines. The four major steps include: (i) characterizing the geographical variation of wind regimes in the onshore U.S. market; (ii) determining the best performing turbines for different wind regimes through wind farm layout optimization; (iii) developing a metric to quantify the expected market suitability of available turbine configurations; and (iv) exploring the best tradeoffs between the cost and capacity factor yielded by these turbines. One hundred thirty one types of commercial turbines offered by major global manufacturers in 2012 are considered for selection. It is found that, in general, higher rated power turbines with medium tower heights are the most favored. Interestingly, further analysis showed that “rotor diameter/hub height” ratios greater than 1.1 are the least attractive for any of the wind classes. It is also observed that although the “cost-capacity factor” tradeoff curve expectedly shifted towards higher capacity factors with increasing wind class, the trend of the tradeoff curve remained practically similar.

Keywords: capacity factor; cost of energy; turbine selection; wind farm layout optimization; wind map (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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