Statistical analysis of environment Canada´s wind speed data

Wind energy utilities use wind speed modeling and prediction to forecast their power production in order to participate in electricity markets. Time-series models which are indirectly based on a Weibull Distribution (WD) are used extensively to predict wind speed. The WD is converted into an approximately Gaussian distribution, as there are no rigorously developed time-series models for random variables possessing a WD. This conversion is performed using the parameters of the WD, a procedure that may negatively impact the accuracy of the forecast - research has demonstrated that WDs under- or over-fit the lower and upper ranges of wind speed histograms. This paper reports on a study of the histories of wind speed forecasts and actual wind speed data available from Environment Canada and the resulting estimates of forecast error distributions and statistics. It is shown through statistical analysis that the hourly prediction error distributions are nearly Gaussian in nature. It also appears to show that the statistics of the wind-speed prediction error do not increase significantly as time increases, which is in contrast to other researchers´ arguments that the error increases over time. This result may warrant further investigation.