Page 137 - Fluid Power Engineering
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114   Chapter Seven


              data were then quality-controlled and assimilated with a data assimi-
              lation system kept unchanged over the reanalysis period.” NCAR data
              is available on 2.5 latitude by 2.5 longitude spatial grid and 6-h tem-
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              poral grid. NCAR dataset is available in an easy-to-access form from
              a service provided by WindPRO, a wind assessment tool. It provides
              wind speed at 10- and 42-m heights, and wind direction. In addition to
              this coarse dataset, finer datasets are available for specific regions, for
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              example, NARR (North American Regional Reanalysis) covers most
              of North America and ECMWF (European Centre for Medium-Range
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              Weather Forecasting) covers most of Europe. The NARR dataset is
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                                     ◦
              available on 1 latitude by 1 longitude spatial grid and 3-h temporal
              grid. This dataset is not available in an easy-to-access method and
              format.
                 The large-scale nature of reanalysis data does not account for the
              local effects like elevation changes and roughness. Since it is a com-
              pilation of multiple data sources, the local effects are taken out from
              each data source to create a reanalysis dataset.


        Resource Estimation Models
              Given the three types of data sources, a variety of models are used to
              estimate wind speed. The most commonly used models are mesoscale,
              computational fluid dynamics (CFD), and microscale models. The
              purpose of these models is to use the wind data described in the pre-
              vious section and create wind data for desired regions. The created
              wind data contains wind speed at multiple heights (or wind speed at
              single height and wind shear), and wind direction.


        Mesoscale Models
              Mesoscale scale models describe weather phenomena that have a
              spatial resolution of 20 to 2,000 km and a temporal resolution of
              hours to days. These models take as input reanalysis data, elevation,
              and roughness data. The reanalysis data provides the external forc-
              ing of the model through boundary conditions. The most common
              mesoscale model are KAMM (http://www.mesoscale.dk/), MM5
              (www.mmm.uear.edu/mm5/mm5-home.html), and MC2 (www.
              cmc.ec.gc.ca/rpn/modcom/en/index en.html). The resolution of the
              models is a few kilometers and the coverage is a few hundred kilome-
              ters. The basic equations related to conservation of mass, momentum,
              and energy are solved in a finite element grid with a temporal resolu-
              tion. Simulations with the mesoscale model yield a statistical picture
              of wind speed and wind direction.
                 Mesoscale models are combined with microscale models to pro-
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              vide useful results for prospecting. The most common combination
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