WindDataSuite allows the calculation of the site energy yield and the site quality
of a wind turbine (for a 5-years operation period) according to the
Technical Guideline 10 (TG 10, published by FGW e.V. Berlin)
in just a few steps.
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 and
is 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. NEW: Precipitation data.
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
- Import (WAsP-WTG, WAsP-POW, WDS-CSV) and export (WAsP-WTG, WDS-CSV) of power curves.
- Time zone management and time corrections
Manifold diagrams (views).
NEW: Comprehensive graphic filters.
NEW: Data editor with many functions. NEW: Now also for raw data.
- Topographic maps (dynamically scaled of OpenTopoMap tiles) as background image
- NEW: More tools for fonts management.
NEW: More tools for fonts management.
(see Fig.17: Font selection window)
- Diagram export into image files in arbitrary size and arbitrary printing resolution
- Diagram transfer to the system clipboard, also in high printing resolution
- Images pin board for collecting diagrams
- Interactive graphical data selection and data removal
- Data filtering with manifold conditions and their combinations
Data averaging (temporal, seasonal, sectorial, height profile).
NEW: Also summing up instead of averaging of time integral quantities.
Binning (1-, 2-, and 3-dimensional), also wind direction sector specific.
Specific bin interval bounds, irregular bin interval bounds.
- 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.
Multiple, and multivariate correlation,
Wind direction sector specific correlations.
- 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 at 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)
Editing power curves and adjusting to other air density.
Power curves with date constraint and/or time constraint.
Comprehensive calculation of energy yields and energy yield losses
with manifold shutdown options and power curve options.
Shadow flicker shutdown, shutdown with seasonal night fractions thresholds
(e.g. night-tenths), annual and monthly evaluation.
NEW: Shutdown conditions expanded by precipitation parameters.
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
- Fill-up of missing wind profile data
- Fill-up of missing time series data
- Shifting the times of a time series
Scaling down the time step of a time series.
Also with mean preserving polynomial interpolation.
NEW: Also splitting instead of interpolating of time integral quantities.