Monte Carlo Simulations of Wind Speed Data

Author:

Gallagher Ron1,Elmore Andrew Curtis2

Affiliation:

1. Assistant Professor, Department of Engineering, Western Kentucky University, 1906 College Heights Blvd., Bowling Green, KY 42101

2. Associate Professor, Department of Geological Engineering, Missouri University of Science and Technology, 129 McNutt Hall, 1400 North Bishop Ave., Rolla, MO 65409-0410

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.

Publisher

SAGE Publications

Subject

Energy Engineering and Power Technology,Renewable Energy, Sustainability and the Environment

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