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.
R. Gallagher and A. C. Elmore, "Monte Carlo Simulations of Wind Speed Data," Wind Engineering, vol. 33, no. 6, pp. 661-673, Multi-Science Publishing Co. Ltd, Dec 2009.
The definitive version is available at http://dx.doi.org/10.1260/0309-524X.33.6.661
Geosciences and Geological and Petroleum Engineering
Keywords and Phrases
Economic factors; Environmental engineering; Groundwater management; Monte carlo simulation; Wind energy; Wind turbines; Central ranges; Cumulative distribution function; Economic factors; Energy value; Regional weather; Scale value; Simulation result; Weather stations; Weibull shape; Wind speed data
International Standard Serial Number (ISSN)
Article - Journal
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