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doc/whatsnew/v0-1-0.txt

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v0.1.0 ()
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+++++++++++++++++++++++++
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Documentation
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New classes
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###########
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* WindFarm class for modelling a wind farm. Defines a standard set of wind farm
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attributes, for example aggregated power curve and wind farm efficiency to
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take wake losses into account.
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* WindTurbineCluster class for modelling a turbine cluster that contains
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several wind turbines and/or wind farms. This class is useful for gathering
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all wind turbines in a weather data grid cell. An aggregated power curve
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can be calculated which considers the wake losses of the wind farms by a
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set efficiency if desired.
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* TurbineClusterModelChain class shows the usage of new functions and classes
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of windpowerlib v.0.1 and is based on the ModelChain class.
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New functions
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#############
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* power curve smoothing for taking into account the spatial distribution of
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wind speed
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* application of wake losses to a power curve
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* application of wake losses to a wind speed time series
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* logarithmic interpolation/extrapolation for wind speed time series
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* gauss distribution
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* estimation of turbulence intensity by roughness length
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Testing
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#######
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* Add continuous integration to automatically test the windpowerlib for
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different python versions and to check the test coverage.
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* added continuous integration to automatically test the windpowerlib for
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different python versions and to check the test coverage
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Documentation
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#############
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* added second example section and jupyter notebook
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Other changes
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#############
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TODO * removed deprecated attributes (.ix)
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Contributors
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############
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* Sabine Haas
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* Birgit Schachler
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* Uwe Krien

windpowerlib/wind_farm.py

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power_output : pandas.Series
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The calculated power output of the wind farm.
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Examples TODO: test example
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Examples
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--------
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>>> from windpowerlib import wind_farm
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>>> from windpowerlib import wind_turbine

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