Fix docs link check and build issues

doc/conf.py

@@ -128,7 +128,10 @@ def setup(sphinx):
         "shapely.%s",
     ),
     "ding0": ("https://dingo.readthedocs.io/en/dev/api/ding0.html#%s", "ding0.%s"),
-    "pypsa": ("https://pypsa.readthedocs.io/en/latest/components.html#%s", "pypsa.%s"),
+    "pypsa": (
+        "https://pypsa.readthedocs.io/en/latest/user-guide/components.html#%s",
+        "pypsa.%s",
+    ),
     "plotly": (
         "https://plotly.com/python-api-reference/generated/%s.html",
         "plotly.%s",

doc/index.rst

@@ -15,7 +15,7 @@ The toolbox currently includes:
 
   * `ding0 <https://github.com/openego/ding0>`_ tool for synthetic medium and low
     voltage grid topologies for the whole of Germany
-  * `OpenEnergy DataBase (oedb) <https://openenergy-platform.org/dataedit/schemas>`_ for
+  * `OpenEnergy DataBase (oedb) <https://openenergyplatform.org/dataedit/schemas>`_ for
     feed-in time series of fluctuating renewables and scenarios for future
     power plant park of Germany
   * `demandlib <https://github.com/oemof/demandlib>`_ for electrical load time series

doc/quickstart.rst

@@ -188,8 +188,8 @@ Aside from grid topology data you may eventually need a dataset on future
 installation of power plants. You may therefore use the scenarios developed in
 the `open_eGo <https://openegoproject.wordpress.com>`_ project that
 are available in the
-`OpenEnergy DataBase (oedb) <https://openenergy-platform.org/dataedit/schemas>`_
-hosted on the `OpenEnergy Platform (OEP) <https://openenergy-platform.org/>`_.
+`OpenEnergy DataBase (oedb) <https://openenergyplatform.org/dataedit/schemas>`_
+hosted on the `OpenEnergy Platform (OEP) <https://openenergyplatform.org/>`_.
 eDisGo provides an interface to the oedb using the package
 `ego.io <https://github.com/openego/ego.io>`_. ego.io gives you a python
 SQL-Alchemy representations of the oedb and access to it by using the

doc/usage_details.rst

@@ -241,7 +241,7 @@ This mode can be invoked as follows:
 For the following components you can use existing time series:
 
 * Fluctuating generators: Feed-in time series for solar and wind power plants can be
-  retrieved from the `OpenEnergy DataBase <https://openenergy-platform.org/dataedit/schemas>`_.
+  retrieved from the `OpenEnergy DataBase <https://openenergyplatform.org/dataedit/schemas>`_.
 * Conventional loads: Standard load profiles for the different sectors residential,
   commercial, agricultural and industrial are generated using the oemof
   `demandlib <https://github.com/oemof/demandlib/>`_.

edisgo/edisgo.py

@@ -417,7 +417,7 @@ def set_time_series_active_power_predefined(
                 Technology- and weather cell-specific hourly feed-in time series are
                 obtained from the
                 `OpenEnergy DataBase
-                <https://openenergy-platform.org/dataedit/schemas>`_. See
+                <https://openenergyplatform.org/dataedit/schemas>`_. See
                 :func:`edisgo.io.timeseries_import.feedin_oedb` for more information.
 
                 This option requires that the parameter `engine` is provided in case
@@ -478,7 +478,7 @@ def set_time_series_active_power_predefined(
 
                 Sets active power demand time series using individual hourly electricity
                 load time series for one year obtained from the `OpenEnergy DataBase
-                <https://openenergy-platform.org/dataedit/schemas>`_.
+                <https://openenergyplatform.org/dataedit/schemas>`_.
 
                 This option requires that the parameters `engine` and `scenario` are
                 provided. For further settings, the parameter `timeindex` can also be
@@ -933,7 +933,7 @@ def import_generators(self, generator_scenario=None, **kwargs):
         Gets generator park for specified scenario and integrates generators into grid.
 
         The generator data is retrieved from the
-        `open energy platform <https://openenergy-platform.org/>`_. Decommissioned
+        `open energy platform <https://openenergyplatform.org/>`_. Decommissioned
         generators are removed from the grid, generators with changed capacity
         updated and new generators newly integrated into the grid.
 
@@ -1928,7 +1928,7 @@ def import_electromobility(
         Imports electromobility data and integrates charging points into grid.
 
         Electromobility data can be obtained from the `OpenEnergy DataBase
-        <https://openenergy-platform.org/dataedit/schemas>`_ or from self-provided
+        <https://openenergyplatform.org/dataedit/schemas>`_ or from self-provided
         data. In case you want to use self-provided data, it needs to be generated
         using the tools
         `SimBEV <https://github.com/rl-institut/simbev>`_ (required version:
@@ -1960,7 +1960,7 @@ def import_electromobility(
             * "oedb"
 
                 Electromobility data is obtained from the `OpenEnergy DataBase
-                <https://openenergy-platform.org/dataedit/schemas>`_.
+                <https://openenergyplatform.org/dataedit/schemas>`_.
 
                 This option requires that the parameters `scenario` and `engine` are
                 provided.
@@ -2143,7 +2143,7 @@ def import_heat_pumps(self, scenario, engine, timeindex=None, import_types=None)
         between two scenarios: 'eGon2035' and 'eGon100RE'.
 
         The data is retrieved from the
-        `open energy platform <https://openenergy-platform.org/>`_.
+        `open energy platform <https://openenergyplatform.org/>`_.
 
         # ToDo Add information on scenarios and from which tables data is retrieved.
 
@@ -2305,7 +2305,7 @@ def apply_heat_pump_operating_strategy(
     def import_dsm(self, scenario: str, engine: Engine, timeindex=None):
         """
         Gets industrial and CTS DSM profiles from the
-        `OpenEnergy DataBase <https://openenergy-platform.org/dataedit/schemas>`_.
+        `OpenEnergy DataBase <https://openenergyplatform.org/dataedit/schemas>`_.
 
         Profiles comprise minimum and maximum load increase in MW as well as maximum
         energy pre- and postponing in MWh. The data is written to the
@@ -2356,7 +2356,7 @@ def import_home_batteries(
         between two scenarios: 'eGon2035' and 'eGon100RE'.
 
         The data is retrieved from the
-        `open energy platform <https://openenergy-platform.org/>`_.
+        `open energy platform <https://openenergyplatform.org/>`_.
 
         The batteries are integrated into the grid (added to
         :attr:`~.network.topology.Topology.storage_units_df`) based on their building

edisgo/io/dsm_import.py

@@ -28,7 +28,7 @@ def oedb(
 ):
     """
     Gets industrial and CTS DSM profiles from the
-    `OpenEnergy DataBase <https://openenergy-platform.org/dataedit/schemas>`_.
+    `OpenEnergy DataBase <https://openenergyplatform.org/dataedit/schemas>`_.
 
     Profiles comprise minimum and maximum load increase in MW as well as maximum energy
     pre- and postponing in MWh.

edisgo/io/generators_import.py

@@ -42,9 +42,9 @@ def oedb_legacy(edisgo_object, generator_scenario, **kwargs):
     The importer uses SQLAlchemy ORM objects. These are defined in
     `ego.io <https://github.com/openego/ego.io/tree/dev/egoio/db_tables/>`_.
     The data is imported from the tables
-    `conventional power plants <https://openenergy-platform.org/dataedit/\
+    `conventional power plants <https://openenergyplatform.org/dataedit/\
     view/supply/ego_dp_conv_powerplant>`_ and
-    `renewable power plants <https://openenergy-platform.org/dataedit/\
+    `renewable power plants <https://openenergyplatform.org/dataedit/\
     view/supply/ego_dp_res_powerplant>`_.
 
     When the generator data is retrieved, the following steps are conducted:

edisgo/io/heat_pump_import.py

@@ -583,7 +583,7 @@ def _grid_integration(
 def efficiency_resistive_heaters_oedb(scenario, engine):
     """
     Get efficiency of resistive heaters from the
-    `OpenEnergy DataBase <https://openenergy-platform.org/dataedit/schemas>`_.
+    `OpenEnergy DataBase <https://openenergyplatform.org/dataedit/schemas>`_.
 
     Parameters
     ----------

edisgo/io/timeseries_import.py

@@ -74,7 +74,7 @@ def _timeindex_helper_func(
 def feedin_oedb_legacy(edisgo_object, timeindex=None):
     """
     Import feed-in time series data for wind and solar power plants from the
-    `OpenEnergy DataBase <https://openenergy-platform.org/dataedit/schemas>`_.
+    `OpenEnergy DataBase <https://openenergyplatform.org/dataedit/schemas>`_.
 
     Parameters
     ----------
@@ -158,7 +158,7 @@ def feedin_oedb(
 ):
     """
     Import feed-in time series data for wind and solar power plants from the
-    `OpenEnergy DataBase <https://openenergy-platform.org/dataedit/schemas>`_.
+    `OpenEnergy DataBase <https://openenergyplatform.org/dataedit/schemas>`_.
 
     Parameters
     ----------
@@ -319,7 +319,7 @@ def load_time_series_demandlib(edisgo_obj, timeindex=None):
 def cop_oedb(edisgo_object, engine, weather_cell_ids, timeindex=None):
     """
     Get COP (coefficient of performance) time series data from the
-    `OpenEnergy DataBase <https://openenergy-platform.org/dataedit/schemas>`_.
+    `OpenEnergy DataBase <https://openenergyplatform.org/dataedit/schemas>`_.
 
     Parameters
     ----------
@@ -377,7 +377,7 @@ def cop_oedb(edisgo_object, engine, weather_cell_ids, timeindex=None):
 def heat_demand_oedb(edisgo_obj, scenario, engine, timeindex=None):
     """
     Get heat demand profiles for heat pumps from the
-    `OpenEnergy DataBase <https://openenergy-platform.org/dataedit/schemas>`_.
+    `OpenEnergy DataBase <https://openenergyplatform.org/dataedit/schemas>`_.
 
     Heat demand data is returned for all heat pumps in the grid.
     For more information on how individual heat demand profiles are obtained see
@@ -498,7 +498,7 @@ def electricity_demand_oedb(
 ):
     """
     Get electricity demand profiles for all conventional loads from the
-    `OpenEnergy DataBase <https://openenergy-platform.org/dataedit/schemas>`_.
+    `OpenEnergy DataBase <https://openenergyplatform.org/dataedit/schemas>`_.
 
     Conventional loads comprise conventional electricity applications in the
     residential, CTS and industrial sector.

edisgo/network/heat.py

@@ -131,7 +131,7 @@ def set_cop(self, edisgo_object, ts_cop, **kwargs):
         Write COP time series for heat pumps to py:attr:`~cop_df`.
 
         COP time series can either be given to this function or be obtained from the
-        `OpenEnergy DataBase <https://openenergy-platform.org/dataedit/schemas>`_.
+        `OpenEnergy DataBase <https://openenergyplatform.org/dataedit/schemas>`_.
         In case they are obtained from the OpenEnergy DataBase the heat pumps need to
         already be integrated into the grid, i.e. given in
         :attr:`~.network.topology.Topology.loads_df`.
@@ -150,7 +150,7 @@ def set_cop(self, edisgo_object, ts_cop, **kwargs):
             * 'oedb'
 
                 COP / efficiency data are obtained from the `OpenEnergy DataBase
-                <https://openenergy-platform.org/dataedit/schemas>`_.
+                <https://openenergyplatform.org/dataedit/schemas>`_.
                 In case of heat pumps weather cell specific hourly COP time series
                 are obtained (see :func:`edisgo.io.timeseries_import.cop_oedb` for more
                 information). Using information on which weather cell each heat pump
@@ -317,7 +317,7 @@ def set_heat_demand(self, edisgo_object, ts_heat_demand, **kwargs):
         Write heat demand time series of heat pumps to py:attr:`~heat_demand_df`.
 
         Heat demand time series can either be given to this function or be obtained from
-        the `OpenEnergy DataBase <https://openenergy-platform.org/dataedit/schemas>`_.
+        the `OpenEnergy DataBase <https://openenergyplatform.org/dataedit/schemas>`_.
         In case they are obtained from the OpenEnergy DataBase the heat pumps need to
         already be integrated into the grid, i.e. given in
         :attr:`~.network.topology.Topology.loads_df`.
@@ -336,7 +336,7 @@ def set_heat_demand(self, edisgo_object, ts_heat_demand, **kwargs):
             * 'oedb'
 
                 Heat demand time series are obtained from the `OpenEnergy DataBase
-                <https://openenergy-platform.org/dataedit/schemas>`_ (see
+                <https://openenergyplatform.org/dataedit/schemas>`_ (see
                 :func:`edisgo.io.timeseries_import.heat_demand_oedb` for more
                 information).
                 Time series are only obtained for heat pumps that are already integrated

edisgo/network/timeseries.py

@@ -1204,7 +1204,7 @@ def predefined_fluctuating_generators_by_technology(
                 Technology and weather cell specific hourly feed-in time series are
                 obtained from the
                 `OpenEnergy DataBase
-                <https://openenergy-platform.org/dataedit/schemas>`_. See
+                <https://openenergyplatform.org/dataedit/schemas>`_. See
                 :func:`edisgo.io.timeseries_import.feedin_oedb` for more information.
 
                 This option requires that the parameter `engine` is provided in case