| dc.contributor.author | Yang, Kaolee | |
| dc.contributor.author | Aziz, Mohammad | |
| dc.date.accessioned | 2019-09-03T19:07:56Z | |
| dc.date.available | 2019-09-03T19:07:56Z | |
| dc.date.issued | 2018-05 | |
| dc.identifier.uri | http://digital.library.wisc.edu/1793/79304 | |
| dc.description | Color poster with text, charts, and graphs. | en_US |
| dc.description.abstract | The fast depletion of non-renewable energy has challenged researchers to look for clean and fuel-efficient sources. Among the bioenergies, wind energy has shown to be clean, fuel-efficient, and cost-effective. Thus, researchers are actively seeking for ways to describe wind speed distribution. The most commonly used distribution is Weibull. However, typical wind speed show skewness and bimodality therefore we focused on flexible skew distributions. We demonstrated the accuracy of each model with application to three datasets and a Monte Carlo simulation. | en_US |
| dc.description.sponsorship | Ronald E. McNair Postbaccalaureate Program; University of Wisconsin--Eau Claire Office of Research and Sponsored Programs | en_US |
| dc.language.iso | en_US | en_US |
| dc.relation.ispartofseries | USGZE AS589; | |
| dc.relation.ispartofseries | USGZE AS589; | |
| dc.subject | Wind speed distribution function | en_US |
| dc.subject | Monte Carlo simulation | en_US |
| dc.subject | Posters | en_US |
| dc.title | Modeling Wind Speed Distributions Using Skewed Probability Functions : A Monte Carlo Simulation with Applications to Real Wind Speed Data | en_US |
| dc.type | Presentation | en_US |