Performance analysis of the first method for long-term turbulence intensity estimation at potential wind energy sites

• Long-term estimation of turbulence intensity is carried out using J-turb algorithm.
• RMSE and number of used months are correlated by exponential decay functions.
• Intermonthly variations stronger bias J-turb estimates than the interannual ones.
• Good performances are achieved for all the selected wind speed thresholds.

The paper presents a validation test of a recent algorithm implemented by the author to correlate turbulence intensity (TI) data recorded at two meteorological masts and based on the conditional probability to measure simultaneous events of wind speed, direction and TI. Two testing sites, located about 5 km apart from each other in a hilly terrain, in the South of Australia, are considered in this work. Three years of concurrent data (2005–2008) are analyzed to estimate a long-term (LT) representative TI. A complete examination of the scores is carried out by spanning dimension and temporal period of the data samples used in the correlation analysis. Root mean square error, committed by the method to approximate mean value of TI measured in each of the three years, can be correlated with number of used months by exponential decay functions. The intermonthly variations stronger affect the accuracy of the results than the yearly ones. However, the average errors are always moderate and good performances are achieved for all the considered wind speed thresholds and also when examining different periods of the year. The tested methodology represents an important step through standardization of Measure-correlate-predict (MCP) technique for TI assessment.