WindDataSuite implements the outstanding new Measure Correlate Predict method MSSCP
(Multiple Synoptic Scale Correlate Predict).
MSSCP is the, by WIND DATA SUiTE developed, Measure Correlate Predict method 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 outstanding method for automatically removing
data spikes. The mathematical algorithm is based on digital filters,
is exceedingly reliable, objective, 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
WindDataSuite is the enormously flexible.
There are no fixed templates.
At any time, you may select which data parameter you want to be displayed and processed,
and which modules for data processing and data evaluation you want to apply.
Some of the many other 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 plug-in. The plug-in 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
10-minutes data, hourly data, diurnal maximal wind peak values
station selection dependent on distance, bearing, and geodetic height difference from a wind park location
selection of parameters
selection of time range
graphical 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 of the hourly data 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
graphical 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
- Manifold diagrams (views)
- Topographic maps (dynamically scaled of OpenTopoMap tiles) as background image
- Diagram export into image files
- Interactive graphical data selection and data removal
- 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
- Comprehensive options for wind direction sectors
Reconstruction of standard deviations and wind peak values from averaged data
Adjusting wind speeds to the hub height
Several polynomial expansions
- 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 turbulence intensities (averages, IEC 61400-1 Edition 3, polynomial fitting)
Calculation of derived quantities (e.g.
Hellmann coefficients, flow angles, vertical shears, time derivatives)
Calculation of wind power densities
Comprehensive calculation of extreme winds (also seasonal, also wind direction sector specific)
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
- Calculation of frequency distribution adjustments to new desired wind speed means
- Calculation of the wind power density percentages and amounts