Abstract
One of the well-known methods for the determination of wind energy potential is the two-parameter Weibull distribution. It is clear that the success of the Weibull distribution for wind energy applications depends on the estimation of the parameters which can be determined by using various numerical methods. In the present study, Monte Carlo simulation method is performed by using six parameters estimation method that is used in the estimation of Weibull distribution parameters such as Maximum Likelihood Estimation (MLE), Least Squares Method (LSM), Method of Moments (MOM), Method of Logarithmic Moments (MLM), Percentile Method (PM), and L-Moment Method (LM), and is compared to Mean Squared Error (MSE) and Mean Absolute Percentage Error (MAPE). In this study, the wind energy potential of the Meşelik region in Eskişehir was modeled with two-parameter Weibull distribution. The average wind speed (m/s) data, which are gathered in 10-minute intervals from the measuring device installed 10 meters about the ground in Meşelik Campus of Eskişehir Osmangazi University, is used. As a result of the simulation study, it has been determined that MLE is the best parameter estimation method for two-parameter Weibull distribution in large sample sizes, and LM has the closest performance to MLE. The wind speed (m/h) data of the region has been successfully modeled with two-parameter Weibull distribution and the highest average wind power density has been obtained in July as 49.38295 (W/m2) while the lowest average wind power density has been obtained in October as 19.30044 (W/m2).
Highlights
In converting the wind potential to electrical energy, the wind speed distribution in the turbine installed area plays an important role along with wind turbine parameters
Average wind speed (m/h) data obtained in 10-minute intervals via data measuring devices installed 10 meters above the ground in Meşelik Campus of Eskişehir Osmangazi University are modeled with two-parameter Weibull distribution and the wind energy potential of the region has been statistically analyzed
L-Moment Method (LM) has been found as the best alternative parameter estimation method for Maximum Likelihood Estimation (MLE), which is the most commonly, used method in the modeling of wind speed data with Weibull distribution
Summary
In converting the wind potential to electrical energy, the wind speed distribution in the turbine installed area plays an important role along with wind turbine parameters. In the design of the system that will optimize the energy generation costs in practice, correct modeling of the wind regime in the area is crucial. The most commonly preferred method for the modeling of the frequency distribution of wind speeds is the Weibull distribution. There are several studies in which the wind potential of an area is determined through Weibull distribution (by Carta et al, 2009). Literature research indicates that many studies have been carried out to determine wind energy potential in different regions through the Weibull distribution. The following were given a few studies in which wind energy potential was determined by the Weibull distribution
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