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Birgit SchachlerBirgit Schachler
Birgit Schachler
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Birgit Schachler
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Move detailed explanation of the basic example to separate file
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‎README.rst‎

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@@ -76,100 +76,3 @@ Matplotlib can be installed using pip3 but some Linux users reported that it is
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http://matplotlib.org/users/installing.html
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Example
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========
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Download the .csv data and the example file and execute it:
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https://github.com/wind-python/windpowerlib/tree/master/example
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Basic Usage
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===========
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You need three steps to get a time series.
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Warning
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~~~~~~~
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Be accurate with the units. In the example all units are given without a prefix.
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* pressure [Pa]
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* wind speed [m/s]
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* installed capacity [W]
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* nominal power [W]
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* area [m²]
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* temperature [°C]
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You can also use kW instead of W but you have to make sure that all units are changed in the same way.
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1. Initialise your Turbine or Module
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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To initialise your specific turbine you need a dictionary that contains your basic parameters.
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The most import parameter is the name of the turbine to get technical parameters from the provided libraries. Use the *get_wind_pp_types* function to get a list of all available converter types.
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.. code-block:: python
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from windpowerlib import basicmodel
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basicmodel.get_wind_pp_types()
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The other parameters are related to location of the plant like diameter of the rotor or the hub height. The existing model needs the following parameters:
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* h_hub: height of the hub in meters
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* d_rotor: diameter of the rotor in meters
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* wind_conv_type: Name of the wind converter according to the list in the csv file
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.. code:: python
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your_wind_turbine = basicmodel.SimpleWindTurbine(**your_parameter_set)
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If you pass a valid model the nominal_power and the cp-values are read from a file. If you want to use your own converter you can pass your own cp-series and nominal power instead of the converter type. This can be done with a dictionary (as shown above) or directly.
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.. code:: python
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your_wind_turbine = basicmodel.SimpleWindTurbine(cp_values=my_cp_values,
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nominal_power=my_nominal_power,
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d_rotor=my_d_rotor,
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h_hub=my_h_hub)
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2. Get your Feedin Time Series
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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To get your time series you have to pass a weather DataFrame (or dictionary) to your model.The DataFrame needs to have pressure, wind speed, temperature and the roughness length. The following names are used:
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* 'pressure'
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* 'temp_air'
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* 'v_wind'
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* 'z0'
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In an additional dictionary the height of the weather data has to be defined. The example shows a dictionary for the coasdat2 weather data set:
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.. code:: python
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coastDat2 = {
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'dhi': 0,
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'dirhi': 0,
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'pressure': 0,
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'temp_air': 2,
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'v_wind': 10,
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'Z0': 0}
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If your weather DataFrame has different column names you have to rename them. This can easily be done by using a conversion dictionary:
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.. code:: python
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name_dc = {
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'your pressure data set': 'pressure',
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'your ambient temperature': 'temp_air',
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'your wind speed': 'v_wind',
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'your roughness length': 'z0'}
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your_weather_DataFrame.rename(columns=name_dc)
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Now you can pass the weather data to the output method:
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.. code:: python
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your_wind_turbine.turbine_power_output(weather=weather_df, data_height=coastDat2)
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You will get the output of one wind_turbine in [W] if you followed the united recommendations from above.

‎doc/example_documentation.rst‎

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Basic Usage
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===========
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You need three steps to get a time series.
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Warning
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~~~~~~~
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Be accurate with the units. In the example all units are given without a prefix.
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* pressure [Pa]
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* wind speed [m/s]
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* installed capacity [W]
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* nominal power [W]
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* area [m²]
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* temperature [°C]
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You can also use kW instead of W but you have to make sure that all units are changed in the same way.
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1. Initialise your Turbine or Module
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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To initialise your specific turbine you need a dictionary that contains your basic parameters.
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The most import parameter is the name of the turbine to get technical parameters from the provided libraries. Use the *get_wind_pp_types* function to get a list of all available converter types.
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.. code-block:: python
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from windpowerlib import basicmodel
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basicmodel.get_wind_pp_types()
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The other parameters are related to location of the plant like diameter of the rotor or the hub height. The existing model needs the following parameters:
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* h_hub: height of the hub in meters
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* d_rotor: diameter of the rotor in meters
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* wind_conv_type: Name of the wind converter according to the list in the csv file
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.. code:: python
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your_wind_turbine = basicmodel.SimpleWindTurbine(**your_parameter_set)
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If you pass a valid model the nominal_power and the cp-values are read from a file. If you want to use your own converter you can pass your own cp-series and nominal power instead of the converter type. This can be done with a dictionary (as shown above) or directly.
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.. code:: python
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your_wind_turbine = basicmodel.SimpleWindTurbine(cp_values=my_cp_values,
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nominal_power=my_nominal_power,
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d_rotor=my_d_rotor,
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h_hub=my_h_hub)
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2. Get your Feedin Time Series
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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To get your time series you have to pass a weather DataFrame (or dictionary) to your model.The DataFrame needs to have pressure, wind speed, temperature and the roughness length. The following names are used:
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* 'pressure'
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* 'temp_air'
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* 'v_wind'
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* 'z0'
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In an additional dictionary the height of the weather data has to be defined. The example shows a dictionary for the coasdat2 weather data set:
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.. code:: python
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coastDat2 = {
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'dhi': 0,
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'dirhi': 0,
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'pressure': 0,
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'temp_air': 2,
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'v_wind': 10,
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'Z0': 0}
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If your weather DataFrame has different column names you have to rename them. This can easily be done by using a conversion dictionary:
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.. code:: python
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name_dc = {
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'your pressure data set': 'pressure',
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'your ambient temperature': 'temp_air',
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'your wind speed': 'v_wind',
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'your roughness length': 'z0'}
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your_weather_DataFrame.rename(columns=name_dc)
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Now you can pass the weather data to the output method:
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.. code:: python
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your_wind_turbine.turbine_power_output(weather=weather_df, data_height=coastDat2)
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You will get the output of one wind_turbine in [W] if you followed the united recommendations from above.

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