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WindographerMCP Onsite Data Tab

The Onsite Data tab of WindographerMCP allows you to import one or more onsite data sets, so for example if you are analyzing a project with five met towers and a LiDAR, you can create those six .windog files and then add all six to your WindographerMCP project as onsite data sets. Then you can analyze those data sets against each other, and reconstruct some or all of them to fill gaps or lengthen them to match the longest period of record.

Note that you will need a subscription license to import more than one onsite data set. The multiple data set capability of the WindographerMCP module is a preview of Windographer 5, which will be a major upgrade to which permanent licensees will have to pay to upgrade. But subscribers are always entitled to the latest features without upgrade fees, so we have enabled this v5 preview for subscribers. We can convert a permanent license to a subscription license (that expires 2.5 years after the purchase date, since permanent licenses cost 2.5x the cost of an annual subscription) for no cost, so contact us if you would like to convert to a subscription.

WindographerMPC Onsite Data Tab - Summary

The summary display shows a simple graphical comparison of the primary speed and direction sensors from each onsite data set.












WindographerMPC Onsite Data Tab - Summary Table

The summary table shows the most important statistical measures from each data set, with the option to analyze only concurrent time steps, meaning those in which all onsite data sets report valid data.











WindographerMPC Onsite Data Tab - Data Coverage

The data coverage display shows the presence or absence of valid data in every time step for every speed, direction, and temperature data column in all onsite data sets.












WindographerMPC Onsite Data Tab - Monthly Mean Speed

You can see monthly or annual means of all speed, direction, or temperature data columns on a single graph or in a single table for easy comparison.












WindographerMPC Onsite Data Tab - TI by Height

The turbulence-versus-height display option shows a graph or table of the turbulence versus height in every onsite data set.













WindographerMPC Onsite Data Tab - TI by Direction

Other display options include turbulence-versus-direction and turbulence-versus-speed.













WindographerMPC Onsite Data Tab - Speed Distribution

The speed distribution display shows a graph or table of the frequency of wind speeds in every onsite data set. Again, you can choose whether to enforce the concurrency requirement.












WindographerMPC Onsite Data Tab - Speed Correlation

Other display options include the correlation coefficient between all speed sensors in all onsite data sets, as well as direction and temperature sensors.












WindographerMPC Onsite Data Tab - Speed Scatter Plot

Other display options include scatter plots of any speed versus any other speed sensor in the onsite data sets. The X and Y axes can correspond to data columns in the same data set or different data sets, and you can choose the number of direction sectors into which to divide the data. You can create similar scatter plots of direction and temperature data columns as well.












WindographerMPC Onsite Data Tab - Reconstruction Window

The data-set-to-data-set reconstruction algorithm takes data from multiple nearby data sets and 'reconstructs' each one’s missing or invalid observations of speed, speed standard deviation, direction, and temperature using as reference the other data sets when appropriate, or other data column in the same data set when appropriate. The algorithm can extend each data set’s period of record to match that of the longest data set. The detailed results show the source of each reconstructed data segment, as well as a statistical summary of the data points reconstructed from each source.

WindographerMPC Onsite Data Tab - Reconstruction Results

The reconstruction process can be very effective at filling gaps and raising the data recovery rate in each data set. It can also lengthen each data set to start at the earliest start time, and end at the latest end time, so that they all share the same period of record.

The screenshot to the left shows the post-reconstruction state of the data sets that appear in the screenshot at the top of this page.