MCP

The MCP (Measure-Correlate-Predict) module is for long-term correction of measured wind data on site based on correlation with long-term reference data.

Calculation Models

MCP ModulLinear regression MCP

The (Linear) regression tool enables the user to inspect the fit directly through an animated graph. If the fit is not satisfactory, a wide range of parameters may be fine-tuned to provide a better fit. The regression tool is not limited to linear regression, but also higher order polynomials may be used in modelling wind speeds and wind veer.

Matrix MCP

The matrix method in windPRO models the changes in wind speed and wind direction through a joint distribution fitted on the ‘matrix’ of observations of wind speed and wind direction changes. The user may choose to either use polynomials fitted to the data statistics or – where appropriate – to use the measured samples directly when doing the matrix MCP.

Weibull Scale MCP

The Weibull Scale method is a very simple empirical method, which does its manipulation directly on the Weibull form and scale parameters (A,k) as well as on the frequency distribution. The Weibull scale method has the advantage, that it will match the nature of the wind at most places.

Wind Index MCPEN_MCP2

The index correlation method compares production output during the period of local measurement to that of the entire reference period thus creating a wind index value for the local measurements to correct the calculated production with. Even though this method may seem rather crude and primitive when comparing to other MCP methods, it has its advantages in stability and performance – even in the cases where other MCP methods seem to fail – as it relies heavily on local measurements and less on reference data.

Access to online Long-term Reference Data

Within the module, users can download NCEP/NCAR (worldwide, grid resolution of 2.5° longitude/latitude), NARR (North America, 32 km resolution), QSCAT (offshore, variable resolution), Blended Coastal Winds (offshore), MERRA (0.5° lat. x 0.6°long.), CFSR (0.5°), METAR (5000 Airports worldwide), SYNOP(7000 synoptical stations worldwide). These data can be imported directly into a METEO Object and used as long-term reference data.
Other data available per subscription: the EMD ConWx Mesoscale model with hourly output available for Europe (resolution 3×3 km). And available per credits: the EMD-WRF Mesoscale On-demand data where the EMD’s mesoscale model is run for a specific point where ever on the globe

Necessary Input Data (Objects)

Please note that the objects are entered in the windPRO module BASIS, where objects are put directly on a map and properties applied. The MCP module uses the METEO object as a data container:
METEO Object: The data container for wind data either as time series data, table data or Weibull distribution.

Calculation Reports

The “end result” from the MCP analysis is a wind statistic generated with WAsP/WAsP-CFD based on a terrain description and the long term corrected wind data. This can be used directly in a PARK calculation or for a wind resource map calculation. For non-WAsP use or further analyses, the long term corrected wind data can be exported as time series.

A very strong feature of the MCP module is the graphic comparison between local measurements and concurrent predictions based on long-term reference and the calculated transfer function to check the success of the prediction.
Numerous reports are available, including a generalized overview report and a detailed report for each method used.

View reports from the MCP module

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