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Monte Carlo Simulations of Wind Speed Data

Monte Carlo Simulations of Wind Speed Data A new Monte Carlo simulation procedure and nearby regional weather station data are used to predict wind speed and turbine energy. The evaluation of the predication values used cumulative distribution function (CDF) graphs. The predication process employed Weibull shape and scale values developed from 1, 12, 20 and 24 years of record for each weather station. Simulation using one year of wind speed data of a weather station located downwind of the wind turbine site resulted in the greatest match of simulation results to the measured values[ED1]. Most simulations of energy values were a closer match to the measured values than those of wind speed. A closer match was defined as simulated values in the CDF central range of 10 to 75 percent which is also a 25 to 75 percent probability factor. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Wind Engineering SAGE

Monte Carlo Simulations of Wind Speed Data

Wind Engineering , Volume 33 (6): 13 – Dec 1, 2009

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References (12)

Publisher
SAGE
Copyright
© 2009 SAGE Publications
ISSN
0309-524X
eISSN
2048-402X
DOI
10.1260/0309-524X.33.6.661
Publisher site
See Article on Publisher Site

Abstract

A new Monte Carlo simulation procedure and nearby regional weather station data are used to predict wind speed and turbine energy. The evaluation of the predication values used cumulative distribution function (CDF) graphs. The predication process employed Weibull shape and scale values developed from 1, 12, 20 and 24 years of record for each weather station. Simulation using one year of wind speed data of a weather station located downwind of the wind turbine site resulted in the greatest match of simulation results to the measured values[ED1]. Most simulations of energy values were a closer match to the measured values than those of wind speed. A closer match was defined as simulated values in the CDF central range of 10 to 75 percent which is also a 25 to 75 percent probability factor.

Journal

Wind EngineeringSAGE

Published: Dec 1, 2009

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