The similar days method for predicting near surface wind vectors

摘要

A reliable forecast of the wind vector at a given site is an important problem with a broad scope of application. Many uses are in the field of wind power in which prediction of strong winds is important; other uses are in the field of civil engineering, where wind gusts are important to structural integrity. For predicting air pollution events or the hazard zone in case of toxic gas accidents the low wind scenarios are of the highest importance, especially under stable conditions. These low wind scenarios are the situations which meso-scale numerical models encounter difficulties or are often neglected when dealing with wind power tasks. Additional drawbacks of meso-scale numerical models in this context are their lack of site-specific detail and the fact that they are very demanding numerically. The 'similar days' method presented here is a method for the prediction of winds at a given location which works well also for low and variable wind conditions. The method is very efficient numerically: typically, runtime is less than a minute on a single PC. This method is based on using the last few hours' measurements at the given site and comparing it to an historical database. A set of criteria is defined to determine the time series similarity. Those similar days are used to construct the forecast. The similar days method was applied to a total of 5 years of measurements collected in two different locations. Very good agreement was achieved between prediction and measurements.