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Program Features WindDataSuite

WindDataSuite implements the outstandig, by WindDataSuite developed, MCP method (MSSCP) for the long-term extrapolation of short-term wind measurements. MSSCP is based on the evaluation of the wind field variability on the synoptic scale.

WindDataSuite implements an outstandig method for automatically removing data spikes. The mathematical algorithm is based on digital filters, is exceedingly reliable, objektive, and extremely fast.

WindDataSuite implements the design and application of digital filters. With WindDataSuite, you can design low-pas, high-pass, band-pass, and inverse band-pass filters and you can apply these onto the wind data. With digital filters, you can uncover certain signals in the frequency domain as, for example, the daily variability or the 1-year variability.

WindDataSuite is the enormously flexible. There are no fixed templates, neither for graphical display nor for data processing. At any time you may select which data parameter you want to be displayed and processed.

Data processing and evaluation is being performed by several processing modules which can be applied independently of each other and in arbitrary sequence.

Another outstanding feature of WindDataSuite is the performance and usability. Computing times are in the range of a few seconds, processing times by the users are in the range of a few minutes.

Some of the further features of WindDataSuite:

  • Reading/writing data of several measuring systems like meteorological mast, SODAR, and LiDAR
  • Reading/writing from/to the file system and from/to any database via database plugins. The plugin technology allows designing special input masks as well as embedding available database applications.
  • Reading time series data of DWD (Deutscher Wetterdienst) weather stations:
    • direct automatic internet download from the DWD server
    • station selection dependent on distance, bearing, and geodetic height difference from a wind park location
    • selection of parameters
    • selection of time range
    • graphic display of the stations in a wind rose diagram and interactive station selection
    • automatic detection and correction of time zone changes
    • automatic detection and report of changes in station location, measurement heights, measuring instruments, and data basis
    • automatic time series generation while adapting DWD specific data definitions
  • Reading MERRA-2 data of the NASA GEOS-5 model (Modern Era Retrospective-analysis for Research and Analysis - Version 2):
    • interactive definition of model subareas
    • direct automatic internet download from the MERRA-2 server
    • MERRA-2 model grid point selection dependent on distance, bearing, and geodetic height difference from a wind park location
    • selection of parameters
    • selection of time range
    • graphic display of the MERRA-2 model grid points in a wind rose diagram and interactive point selection
    • automatic time series generation while adapting and converting MERRA-2 specific data output
  • Import and export of WAsP-TAB files.
  • Time zone management and time corrections
  • Spreadsheet-near own data format for time series and binning
  • Diagram export into image files
  • Processing protocol
  • Comprehensive configuration facilities
  • Multilingual (English and German)
  • Interactive graphical data selection and data removal
  • Designing digital filters
  • Data filtering with digital filters
  • Automatically and manual despiking
  • Automatically and manual removal of data under deadlocks and icings
  • Data filtering with manifold conditions and their combinations
  • Data averaging (temporal, seasonal, sectorial, height profile)
  • Binning (1-, 2-, and 3-dimensional), also wind direction sector specific
  • Long-term extrapolation of short-term wind measurements with the outstanding MCP method MSSCP
  • Comprehenive management and conversions for calm winds and baffling winds
  • Comprehenive options for wind direction sectors
  • Generation of arbitrary time parameters
  • Time series statistics
  • Cross- and auto-correlations between any scalar and vector parameters and with any phase shifts.
  • Mean time series moments (1. to 4. order, temporal, seasonal, sectorial, height profile)
  • Running time series moments (1. to 4. order, arbitrary periods)
  • Calculation of air density and air pressure in any heights for dry and humid air dependent on measured/prescribed/calculated air temperature, relative air humidity, and air pressure
  • Calculation of derived quantities (e.g. turbulence intensities, Hellmann coefficients, flow angles, vertical shears, time derivatives)
  • Mathematical transformations on basis of easy to construct formulas with all arithmetic operations, with algebraic, transcendental, logical und special functions, and with any data variables
  • Fourier analysis
  • Fit to logarithmic wind profile (2- and 3-parameter fit)
  • Fit to Weibull distribution (2- and 3-parameter fit), also wind direction sector specific
  • Redistribution of the frequencies of calms and baffling winds onto the other wind direction sectors
  • Calculation of frequency distribution adjustments to new desired wind speed means
  • Calculation of the wind power density percentages and amounts
  • Several diagrams for data visualizing (time series, profile contouring, profiles, scatter diagram, parameter diagram, 2D-contouring diagram, wind rose scatter diagram, wind roses for frequencies and distributions), locations diagram

Examples

WindDataSuite is being developed in the programming language Java and thus cross-platform deployable.

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