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Advanced W ind Resource Assessment       165


               Terrain Type                          RMS Error (%)
               Simple terrain, two met-towers              5
               Simple terrain, three met-towers            2
               Rolling hills, three met-towers             7
               Complex terrain, two met-towers            15
               Complex terrain, three met-towers           8
              TABLE 8-7  Root Mean Square Error in Wind Speed Estimation Using a Variety
              of Models for Spatial Extrapolation


                  4. Long-term climate adjustment. This pertains to the prediction
                    model used to produce a long-term wind estimate from short-
                    term measurements. In addition, it includes ability of hind-
                    casted data to predict the wind conditions in the future.
                  5. Plant loss uncertainty. Note, plant loss uncertainty is not the
                    same as plant losses. This item deals with uncertainty associ-
                    ated with estimates of losses.

                 The focus of this section will be on items (3) and (4).
                 In the spatial distribution model, uncertainty is pertinent if the
              measurement location and planned turbine location is not the same.
              Studies have shown the error in wind speed estimates varies by type
              of terrain and number of met-towers. Results from one such study by
                                       7
              DNV Global Energy Concepts is shown in Table 8-7.
                 Site-specific uncertainty because of long-term climate adjustment
              is difficult to estimate. Uncertainty of 3 to 5% is to be expected. A
                                                          8
              procedure for estimation is described by Siddabathini, but it requires
              several years of measurement data.


        Estimating Uncertainty of Annual Energy Production:
        Framework for Combining Uncertainty
              There are two aspects to understanding uncertainty: Amount of un-
              certainty and its impact on the quantity of interest (in this case, it is
              AEP or revenue). The impact is also called the sensitivity of a variable
              to the quantity of interest. Quantity of interest may be annual energy
              production (AEP) and financial performance such as payback period
              or net-present value (NPV). In the rest of this discourse, AEP will be
              the quantity of interest. The square of the combined uncertainty on
              AEP can be written in a generalized form as: 9

                                        N
                                       N
                               U 2  =                             (8-21)
                                 AEP        ρ i, j c i c j u i u j
                                      i=1 j=1
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