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W ind Resource Assessment      135


                                     Frequency [%]

                                                       NNE
                                           N
                             NNW
                                           12
                                           10
                                                               ENE
                                            8
                    WNW
                                            6
                                            4
                                            2
                    W                                            E
                                                  5       10



                     WSW                                      ESE




                              SSW           S          SSE

                  Concurrent site data          MCP result (long-term site data)
                                      (c)

              FIGURE 7-9 (Continued)

              Generic Prediction Method
              The purpose of prediction is to compute a transfer function, f (x):

                                     Y = f (X) + ε                 (7-2)
              where Y is the predicted time series for onsite wind data, X is the
              reference time series (long-term wind data), and ε is the residual.
              Prediction is a two-step process:

                    Computation of transfer function, f (). The function f () is de-

                    termined based on a forecasting method that is applied to 1
                    (or more) year of onsite measurement data and concurrent
                    long-term reference data.
                    Creation of the predicted time series using f () and ε. The function

                     f () is applied to long-term reference data and the residual
                    term is added to the result. The residual term ε is important
                    because ignoring it can cause the energy production to be
                                             9
                    underestimated by up to 10%. The reason will be explained
                    later in the section.
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