Merge pull request #68 from wind-python/feature/add_to_dict_method_for_wind_turbine

Feature/add to_group method for wind turbine

Author: birgits

.gitignore

@@ -36,8 +36,6 @@ pip-delete-this-directory.txt
 
 # Doc
 doc/temp/*
-!doc/temp/windpowerlib.wind_farm.WindFarm.rst
-!doc/temp/windpowerlib.wind_turbine_cluster.WindTurbineCluster.rst
 .doctrees
 .buildinfo
 

doc/conf.py

@@ -157,7 +157,7 @@
 # Add any paths that contain custom static files (such as style sheets) here,
 # relative to this directory. They are copied after the builtin static files,
 # so a file named "default.css" will overwrite the builtin "default.css".
-html_static_path = ['_static']
+html_static_path = []
 
 # Add any extra paths that contain custom files (such as robots.txt or
 # .htaccess) here, relative to this directory. These files are copied

doc/getting_started.rst

@@ -55,9 +55,9 @@ The basic usage of the windpowerlib is shown in the ModelChain example that is a
 To run the example you need the example weather and turbine data used:
 
  * :download:`Example weather data file <../example/weather.csv>`
- * :download:`Example power curve data file <../example/data/example_power_curves.csv>`
- * :download:`Example power coefficient curve data file <../example/data/example_power_coefficient_curves.csv>`
- * :download:`Example nominal power data file <../example/data/example_turbine_data.csv>`
+ * :download:`Example power curve data file <../example/data/power_curves.csv>`
+ * :download:`Example power coefficient curve data file <../example/data/power_coefficient_curves.csv>`
+ * :download:`Example nominal power data file <../example/data/turbine_data.csv>`
 
 Furthermore, you have to install the windpowerlib and to run the notebook you also need to install `notebook` using pip3. To launch jupyter notebook type ``jupyter notebook`` in the terminal.
 This will open a browser window. Navigate to the directory containing the notebook to open it. See the jupyter notebook quick start guide for more information on `how to install <http://jupyter-notebook-beginner-guide.readthedocs.io/en/latest/install.html>`_ and

doc/modules.rst

@@ -63,14 +63,26 @@ Wind turbine data
 Functions and methods to obtain the nominal power as well as 
 power curve or power coefficient curve needed by the :py:class:`~.wind_turbine.WindTurbine` class.
 
-
 .. autosummary::
    :toctree: temp/
 
    wind_turbine.get_turbine_data_from_file
    wind_turbine.load_turbine_data_from_oedb
    wind_turbine.get_turbine_types
 
+.. _create_input_types_label:
+
+Data Container
+=====================
+
+Create data container to be used as an input in classes und functions.
+
+.. autosummary::
+   :toctree: temp/
+
+   wind_turbine.WindTurbineGroup
+   wind_turbine.WindTurbine.to_group
+
 .. _wind_farm_label:
 
 Wind farm calculations
@@ -233,4 +245,4 @@ TurbineClusterModelChain example
 The ``turbine_cluster_modelchain_example`` consists of the following functions
 as well as it uses functions of the ``modelchain_example``.
 
-.. include:: example_2.rst
+.. include:: example_2.rst

doc/temp/windpowerlib.wind_farm.WindFarm.rst

@@ -157,7 +157,7 @@
    "source": [
     "To initialize a specific turbine you need a dictionary that contains the basic parameters. A turbine is defined by its nominal power, hub height, rotor diameter, and power or power coefficient curve.\n",
     "\n",
-    "There are three ways to initialize a WindTurbine object in the windpowerlib. You can either specify your own turbine, as done below for 'my_turbine', or fetch power and/or power coefficient curve data from data files provided by the windpowerlib, as done for the 'enercon_e126', or provide your turbine data in csv files as done for the 'dummy_turbine' with an example file.\n",
+    "There are three ways to initialize a WindTurbine object in the windpowerlib. You can either use turbine data from the OpenEnergy Database (oedb) turbine library that is provided along with the windpowerlib, as done for the 'enercon_e126', or specify your own turbine by directly providing a power (coefficient) curve, as done below for 'my_turbine', or provide your own turbine data in csv files, as done for 'dummy_turbine'.\n",
     "\n",
     "You can execute the following to get a table of all wind turbines for which power and/or power coefficient curves are provided."
    ]
@@ -228,28 +228,6 @@
     "print(df[df[\"turbine_type\"].str.contains(\"E-101\")])"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": 33,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# specification of own wind turbine (Note: power coefficient values and\n",
-    "# nominal power have to be in Watt)\n",
-    "my_turbine = {\n",
-    "    'name': 'myTurbine',\n",
-    "    'nominal_power': 3e6,  # in W\n",
-    "    'hub_height': 105,  # in m\n",
-    "    'rotor_diameter': 90,  # in m\n",
-    "    'power_curve': pd.DataFrame(\n",
-    "            data={'value': [p * 1000 for p in [\n",
-    "                      0.0, 26.0, 180.0, 1500.0, 3000.0, 3000.0]],  # in W\n",
-    "                  'wind_speed': [0.0, 3.0, 5.0, 10.0, 15.0, 25.0]})  # in m/s\n",
-    "    }  \n",
-    "# initialisze WindTurbine object\n",
-    "my_turbine = WindTurbine(**my_turbine)"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": 6,
@@ -270,13 +248,10 @@
    "source": [
     "# specification of wind turbine where power curve is provided in the \n",
     "# oedb turbine library\n",
-    "# if you want to use the power coefficient curve change the value of\n",
-    "# 'power_coefficient_curve' to 'oedb'.\n",
+    "\n",
     "enercon_e126 = {\n",
     "        'turbine_type': 'E-126/4200',  # turbine type as in oedb turbine library\n",
-    "        'hub_height': 135,  # in m\n",
-    "        'rotor_diameter': 127,  # in m (only needs to be provided when calculating the power \n",
-    "                                # output using the power coefficient curve)\n",
+    "        'hub_height': 135  # in m\n",
     "    }\n",
     "# initialize WindTurbine object\n",
     "e126 = WindTurbine(**enercon_e126)"

doc/temp/windpowerlib.wind_turbine_cluster.WindTurbineCluster.rst

@@ -94,15 +94,15 @@ def initialize_wind_turbines():
     Initializes three :class:`~.wind_turbine.WindTurbine` objects.
 
     This function shows three ways to initialize a WindTurbine object. You can
-    either specify your own turbine by directly providing a power (coefficient)
-    curve, as done below for 'my_turbine', or provide your own turbine data in
-    csv files as done for 'dummy_turbine', or you can use power and/or power
-    coefficient curve data from the OpenEnergy Database
-    (oedb) turbine library that is provided along with the windpowerlib,
-    as done for the 'enercon_e126'. Execute
-    ``windpowerlib.wind_turbine.get_turbine_types()`` to get a table
-    including all wind turbines for which power and/or power coefficient curves
-    are provided.
+    either use turbine data from the OpenEnergy Database (oedb) turbine library
+    that is provided along with the windpowerlib, as done for the
+    'enercon_e126', or specify your own turbine by directly providing a power
+    (coefficient) curve, as done below for 'my_turbine', or provide your own
+    turbine data in csv files, as done for 'dummy_turbine'.
+
+    To get a list of all wind turbines for which power and/or power coefficient
+    curves are provided execute `
+    `windpowerlib.wind_turbine.get_turbine_types()``.
 
     Returns
     -------
@@ -112,6 +112,15 @@ def initialize_wind_turbines():
 
     """
 
+    # specification of wind turbine where data is provided in the oedb
+    # turbine library
+    enercon_e126 = {
+        'turbine_type': 'E-126/4200',  # turbine type as in register
+        'hub_height': 135  # in m
+    }
+    # initialize WindTurbine object
+    e126 = WindTurbine(**enercon_e126)
+
     # specification of own wind turbine (Note: power values and nominal power
     # have to be in Watt)
     my_turbine = {
@@ -137,18 +146,6 @@ def initialize_wind_turbines():
     # initialize WindTurbine object
     dummy_turbine = WindTurbine(**dummy_turbine)
 
-    # specification of wind turbine where power curve is provided in the oedb
-    # turbine library
-    # if you want to use the power coefficient curve change the value of
-    # 'power_coefficient_curve' to True.
-    enercon_e126 = {
-        'turbine_type': 'E-126/4200',  # turbine type as in register
-        'hub_height': 135,  # in m
-        'rotor_diameter': 127,  # in m
-    }
-    # initialize WindTurbine object
-    e126 = WindTurbine(**enercon_e126)
-
     return my_turbine, e126, dummy_turbine
 
 

example/modelchain_example.ipynb

@@ -29,6 +29,8 @@
     "__copyright__ = \"Copyright oemof developer group\"\n",
     "__license__ = \"GPLv3\"\n",
     "\n",
+    "import pandas as pd\n",
+    "\n",
     "import modelchain_example as mc_e\n",
     "from windpowerlib import TurbineClusterModelChain, WindTurbineCluster, WindFarm\n",
     "\n",
@@ -92,19 +94,19 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "# specification of wind farm\n",
-    "example_farm_data = {\n",
-    "    'name': 'example_farm',\n",
-    "    'wind_turbine_fleet': [{'wind_turbine': my_turbine,  # as windpowerlib.WindTurbine\n",
-    "                            'number_of_turbines': 6},  # number of `my_turbine` turbines in farm (float \n",
-    "                                                       # values are possible as well)\n",
-    "                           {'wind_turbine': e126,\n",
-    "                            'total_capacity': 12.6e6}  # installed capacity of `my_turbine` turbines \n",
-    "                                                       # in farm in Watt\n",
-    "                           ]}\n",
-    "\n",
+    "# specification of wind farm data where turbine fleet is provided in a\n",
+    "# pandas.DataFrame\n",
+    "# for each turbine type you can either specify the number of turbines of\n",
+    "# that type in the wind farm (float values are possible as well) or the\n",
+    "# total installed capacity of that turbine type in W\n",
+    "wind_turbine_fleet = pd.DataFrame(\n",
+    "        {'wind_turbine': [my_turbine, e126],  # as windpowerlib.WindTurbine\n",
+    "         'number_of_turbines': [6, None],\n",
+    "         'total_capacity': [None, 12.6e6]}\n",
+    "    )\n",
     "# initialize WindFarm object\n",
-    "example_farm = WindFarm(**example_farm_data)"
+    "example_farm = WindFarm(name='example_farm',\n",
+    "                        wind_turbine_fleet=wind_turbine_fleet)"
    ]
   },
   {
@@ -128,13 +130,12 @@
     }
    ],
    "source": [
-    "# specification of wind farm (2) with a wind farm efficiency\n",
+    "# specification of wind farm data (2) containing a wind farm efficiency\n",
+    "# wind turbine fleet is provided using the to_group function\n",
     "example_farm_2_data = {\n",
     "    'name': 'example_farm_2',\n",
-    "    'wind_turbine_fleet': [{'wind_turbine': my_turbine,\n",
-    "                            'number_of_turbines': 6},\n",
-    "                           {'wind_turbine': e126,\n",
-    "                            'number_of_turbines': 3}],\n",
+    "    'wind_turbine_fleet': [my_turbine.to_group(6),\n",
+    "                           e126.to_group(total_capacity=12.6e6)],\n",
     "    'efficiency': 0.9}\n",
     "\n",
     "# initialize WindFarm object\n",
@@ -176,7 +177,7 @@
     "\n",
     "The TurbineClusterModelChain is a class that provides all necessary steps to calculate the power output of a wind farm or wind turbine cluster. \n",
     "\n",
-    "Like the ModelChain (see [basic example](modelchain_example.ipynb)) you can use the TurbineClusterModelChain with default parameters as shown in this example for the wind farm or specify custom parameters as done here for the cluster.\n",
+    "Like the ModelChain (see [basic example](modelchain_example_notebook.ipynb)) you can use the TurbineClusterModelChain with default parameters as shown in this example for the wind farm or specify custom parameters as done here for the cluster.\n",
     "If you use the 'run_model' method first the aggregated power curve and the mean hub height of the wind farm/cluster is calculated, then inherited functions of the ModelChain are used to calculate the wind speed and density (if necessary) at hub height. After that, depending on the parameters, wake losses are applied and at last the power output is calculated."
    ]
   },

example/modelchain_example.py

@@ -12,6 +12,8 @@
 __copyright__ = "Copyright oemof developer group"
 __license__ = "GPLv3"
 
+import pandas as pd
+
 try:
     from matplotlib import pyplot as plt
 except ImportError:
@@ -53,28 +55,26 @@ def initialize_wind_farms(my_turbine, e126):
 
     """
 
-    # specification of wind farm data
-    example_farm_data = {
-        'name': 'example_farm',
-        'wind_turbine_fleet': [
-            {'wind_turbine': my_turbine,  # as windpowerlib.WindTurbine
-             'number_of_turbines': 6},  # number of `my_turbine` turbines in
-                                        # farm (float values are possible as
-                                        # well)
-            {'wind_turbine': e126,
-             'total_capacity': 12.6e6  # installed capacity of `my_turbine`
-                                       # turbines in farm in Watt
-             }]}
+    # specification of wind farm data where turbine fleet is provided in a
+    # pandas.DataFrame
+    # for each turbine type you can either specify the number of turbines of
+    # that type in the wind farm (float values are possible as well) or the
+    # total installed capacity of that turbine type in W
+    wind_turbine_fleet = pd.DataFrame(
+        {'wind_turbine': [my_turbine, e126],  # as windpowerlib.WindTurbine
+         'number_of_turbines': [6, None],
+         'total_capacity': [None, 12.6e6]}
+    )
     # initialize WindFarm object
-    example_farm = WindFarm(**example_farm_data)
+    example_farm = WindFarm(name='example_farm',
+                            wind_turbine_fleet=wind_turbine_fleet)
 
     # specification of wind farm data (2) containing a wind farm efficiency
+    # wind turbine fleet is provided using the to_group function
     example_farm_2_data = {
         'name': 'example_farm_2',
-        'wind_turbine_fleet': [{'wind_turbine': my_turbine,
-                                'number_of_turbines': 6},
-                               {'wind_turbine': e126,
-                                'number_of_turbines': 3}],
+        'wind_turbine_fleet': [my_turbine.to_group(6),
+                               e126.to_group(total_capacity=12.6e6)],
         'efficiency': 0.9}
     # initialize WindFarm object
     example_farm_2 = WindFarm(**example_farm_2_data)