Improve Data Quality
Every data set has issues.
Quickly detect and flag problems such as tower shading, icing events, or sensor malfunctions, and filter bad data from calculations. Apply scaling factors, offsets, or time shifts, and even fill gaps.
Flag data segments based on visual inspection
By simply clicking and dragging on the time series graph, you can manually apply flags to data segments to identify problems such as sensor malfunctions or icing events. Once you have applied flags, you can use those flags to filter data from graphs and calculations.
Flag data segments based on formal criteria
Create your own flag rules to automatically flag all data segments that meet the criteria you specify.
Automatically flag data affected by tower shading
Windographer automatically detects tower shading patterns and generates the corresponding flag rules, so with two clicks you can flag every data point affected by tower shading.
Extrapolate vertically
Windographer analyzes the wind shear patterns in your data set and uses them to synthesize wind speed data for any height above ground. You can use this feature to estimate wind speeds at the hub height of a particular wind turbine.
Fill gaps
Fill gaps with synthetic data using an innovative Markov algorithm that replicates the observed distribution, diurnal pattern, autocorrelation, and wind shear pattern. This technique can reliably fill gaps up to several days in length, not only in wind speed data, but also in wind direction, temperature, or any other data column.
Apply an offset and scaling factor to any data segment
Convert units, correct a scaling error, or apply a directional offset to one or more data columns. Apply the changes to the entire length of the data set, or just a particular date range.
Apply a time shift to any data segment
Change time zones or correct clock errors by shifting any piece of the data set in time.
Track all modifications
Windographer tracks all modifications to the data set, so you can see its history.
