# Fast Numerical Wind Turbine Candidate Site Evaluation
## 1 Introduction  
Small wind turbines (Figure 1), which are defined as turbines with rotor swept area under 200 m\({}^{2}\) and generating electricity below a certain voltage [1], are popular and being installed at an increasing rate [2, 3, 4, 5]. The wind characteristics at the site of a wind turbine have a big influence on its performance [6, 7] and noise emissions [8]. Thus, it is important to select a good site for placing it. The standard method for evaluating a candidate site for a wind turbine is collecting long-term wind measurements at the site. The decision on whether to install a wind turbine at a particular location is most often based on the annual energy production, which can be estimated from the wind speed distribution and the wind turbine power curve [9, 10, 11]. The measurement taking time and delaying the decision process is the issue addressed in this work. The motivation for this investigation is avoiding the long wait for wind measurements from the candidate turbine site to be collected. A method for the fast evaluation of the feasibility of a site for the possible placement of a wind turbine is developed and tested. The method predicts the yearly time series of the wind speed at the site and derives the wind speed distribution from it. The distribution is more important than the time series,because it is related to the annual energy production. The presented method would be easy to use at different sites without requiring additional research--the goal is for the application of the method to fit the budget of a small wind turbine construction. The assumed situation that is being addressed is the following:  
* Because of time constraints, one month of wind speed measurements from the candidate turbine site is available. * A fine resolution numerical weather prediction (NWP) model for the area is available and its predictions for the past are available. * Past measurements from meteorological stations in the area, but not from the site under examination, are available. * One year of wind speed and direction signals for the candidate site are sought after, so 11 months are predicted. * A yes/no decision on installing the wind turbine at the exact location is required--the option of adjusting the location is not considered. For clarification of the further notation, signal is a time-dependent physical quantity that carries information regarding the system. It can be either measured on the real system or obtained as an output of a model. System is the atmosphere and the other parts of the environment that influence the weather, and model is a numerical approximation of the system. Shortening the measurement period involves risks that are proportional to the size of the project. Therefore, it is particularly tempting to use an alternative and less accurate site evaluation method if the wind turbine is small. One possible alternative would be using NWP-predicted signals as a proxy for local wind speed, even though NWP models, such as Weather Research and Forecasting model (WRF), do not reflect local terrain effects as they represent values ascribed to staggered grid points [12]. Furthermore, unlike big wind turbines, small ones may be used at low heights above ground and in areas with low average wind speed, where NWP is particularly inaccurate in predicting local wind speed. Because of these reasons, the presented method is likely to be especially suitable for evaluating sites for small wind turbines. Figure 1: A small wind turbine. Photo by [PERSON]. The goals are achieved with a novel approach in this field--system identification. An experimental model (i.e., a mathematical model that is based on measurement data) is trained with a short time series of training data, one month in our case. The output of the model is the wind speed at the candidate turbine site, which only has to be measured during the training period.