Merge branch 'develop' of https://github.com/e2nIEE/pandapower into d…

…evelop

doc/about/units.rst

@@ -45,7 +45,7 @@ The power equation in the balanced three phase system is therefore given as :mat
 **Three Phase System (Unbalanced Load Flow)**
 
 For unbalanced three phase systems, the following conventions apply:
-	- voltage values are entered as phase-to-phase voltages
+    - voltage values are entered as phase-to-phase voltages
     - current values are entered as phase currents
     - But, Phase power values can be entered seperately in the new element **asymmetric_load** 
 

doc/control/controller.rst

@@ -16,6 +16,7 @@ The basic controller is the base controller class that should be subclassed when
 ConstControl
 ==============
 .. _ConstControl:
+
 This controller is made for the use with the time series module to read data from a DataSource and write it to the net.
 The controller can write the values either to a column of an element table (e.g. net.load.p_mw) or an attribute of another object that is
 stored in an element table (e.g. another controller, net.controller.object). To change a controller attribute, the variable must be defined
@@ -49,7 +50,7 @@ Discrete Tap Control
     :members:
 
 CharacteristicControl
-===============
+=====================
 
 The following controllers that use characteristics are predefined within the pandapower control module.
 

doc/elements/asymmetric_load.rst

@@ -51,6 +51,7 @@ Loads are modelled as PQ-buses in the power flow calculation.
 	:width: 40em
 	:alt: alternate Text
 	:align: center
+
 *Delta Load*
 
 .. image:: asym_del_load.png

doc/networks.rst

@@ -18,7 +18,6 @@ You can find documentation for the individual network modules of pandapower here
 .. toctree::
     :maxdepth: 2
 
-    networks/simbench
     networks/example
     networks/test
     networks/cigre

doc/powerflow/run.rst

@@ -8,6 +8,6 @@ pandapower provides  AC (Balanced/Unbalanced) and linearized (DC) powerflow.
 .. toctree:: 
     :maxdepth: 3
 
-    ac_3ph
     ac
-    dc
+    dc
+    ac_3ph

doc/timeseries/data_source.rst

@@ -3,7 +3,7 @@ Data Sources
 #############################
 
 DataSource Base Class
-=================
+=====================
 A ``DataSource`` object must be given to :ref:`const controllers <ConstControl>` in order to run time series simulations.
 The data source contains the values to be set in each time step by the controller. It has the function
 :code:`get_time_step_value(time_step)` which reads these values.
@@ -12,7 +12,7 @@ The data source contains the values to be set in each time step by the controlle
     :members:
 
 DataFrame Data Source
-=================
+=====================
 A ``DFData`` object is inherited from ``DataSource`` and contains a DataFrame which stores the time series values.
 
 .. autoclass:: pandapower.timeseries.data_sources.frame_data.DFData

doc/toolbox.rst

@@ -47,7 +47,7 @@ Result Information
 
 .. autofunction:: pandapower.nets_equal
 
-.. autofunction:: pandapower.clear_result_table
+.. autofunction:: pandapower.clear_result_tables
 
 ====================================
 Simulation Setup and Preparation

pandapower/control/controller/const_control.py

@@ -55,8 +55,8 @@ class ConstControl(Controller):
         dropped
 
     .. note:: If multiple elements are represented with one controller, the data source must have
-    integer columns. At the moment, only the DFData format is tested for the multiple const
-    control.
+        integer columns. At the moment, only the DFData format is tested for the multiple const
+        control.
     """
 
     def __init__(self, net, element, variable, element_index, profile_name=None, data_source=None,

pandapower/control/run_control.py

@@ -252,18 +252,20 @@ def run_control(net, ctrl_variables=None, max_iter=30, **kwargs):
     Function is running control loops for the controllers specified in net.controller
 
     INPUT:
-   **net** - pandapower network with controllers included in net.controller
+        **net** - pandapower network with controllers included in net.controller
 
     OPTIONAL:
-       **ctrl_variables** (dict, None) - variables needed internally to calculate the power flow. See prepare_run_ctrl()
-       **max_iter** (int, 30) - The maximum number of iterations for controller to converge
+        **ctrl_variables** (dict, None) - variables needed internally to calculate the power flow. See prepare_run_ctrl()
+
+        **max_iter** (int, 30) - The maximum number of iterations for controller to converge
 
     KWARGS:
-        **continue_on_divergence** (bool, False) - if run_funct is not converging control_repair is fired
-                                                   (only relevant if ctrl_varibales is None, otherwise it needs
+        **continue_on_divergence** (bool, False) - if run_funct is not converging control_repair is fired \
+                                                   (only relevant if ctrl_varibales is None, otherwise it needs \
                                                    to be defined in ctrl_variables anyway)
-        **check_each_level** (bool, True) - if each level shall be checked if the controllers are converged or not
-                                           (only relevant if ctrl_varibales is None, otherwise it needs
+
+        **check_each_level** (bool, True) - if each level shall be checked if the controllers are converged or not \
+                                           (only relevant if ctrl_varibales is None, otherwise it needs \
                                            to be defined in ctrl_variables anyway)
 
     Runs controller until each one converged or max_iter is hit.
@@ -272,6 +274,7 @@ def run_control(net, ctrl_variables=None, max_iter=30, **kwargs):
     2. Calculate an inital power flow (if it is enabled, i.e. setting the initial_run veriable to True)
     3. Repeats the following steps in ascending order of controller_order until total convergence of all
        controllers for each level:
+
         a) Evaluate individual convergence for all controllers in the level
         b) Call control_step() for all controllers in the level on diverged controllers
         c) Calculate power flow (or optionally another function like runopf or whatever you defined)

pandapower/create.py

@@ -698,8 +698,7 @@ def create_load(net, bus, p_mw, q_mvar=0, const_z_percent=0, const_i_percent=0,
             controllable loads in OPF
 
         **controllable** (boolean, default NaN) - States, whether a load is controllable or not. \
-            Only respected for OPF
-            Defaults to False if "controllable" column exists in DataFrame
+            Only respected for OPF; defaults to False if "controllable" column exists in DataFrame
 
     OUTPUT:
         **index** (int) - The unique ID of the created element
@@ -947,7 +946,8 @@ def create_load_from_cosphi(net, bus, sn_mva, cos_phi, mode, **kwargs):
 
         **mode** (str) - "underexcited" (Q absorption, decreases voltage) or "overexcited" (Q injection, increases voltage)
 
-        **kwargs are passed on to the create_load function
+    OPTIONAL:
+        same as in create_load, keyword arguments are passed to the create_load function
 
     OUTPUT:
         **index** (int) - The unique ID of the created load
@@ -985,7 +985,6 @@ def create_sgen(net, bus, p_mw, q_mvar=0, sn_mva=nan, name=None, index=None,
         **p_mw** (float) - The active power of the static generator  (positive for generation!)
 
     OPTIONAL:
-
         **q_mvar** (float, 0) - The reactive power of the sgen
 
         **sn_mva** (float, None) - Nominal power of the sgen
@@ -1013,9 +1012,8 @@ def create_sgen(net, bus, p_mw, q_mvar=0, sn_mva=nan, name=None, index=None,
         **min_q_mvar** (float, NaN) - Minimum reactive power injection - necessary for \
             controllable sgens in OPF
 
-        **controllable** (bool, NaN) - Whether this generator is controllable by the optimal
-        powerflow
-            Defaults to False if "controllable" column exists in DataFrame
+        **controllable** (bool, NaN) - Whether this generator is controllable by the optimal \
+            powerflow; defaults to False if "controllable" column exists in DataFrame
 
         **k** (float, NaN) - Ratio of nominal current to short circuit current
 
@@ -1306,9 +1304,8 @@ def create_storage(net, bus, p_mw, max_e_mwh, q_mvar=0, sn_mva=nan, soc_percent=
         **min_q_mvar** (float, NaN) - Minimum reactive power injection - necessary for a \
             controllable storage in OPF
 
-        **controllable** (bool, NaN) - Whether this storage is controllable by the optimal
-        powerflow
-            Defaults to False if "controllable" column exists in DataFrame
+        **controllable** (bool, NaN) - Whether this storage is controllable by the optimal \
+            powerflow; defaults to False if "controllable" column exists in DataFrame
 
     OUTPUT:
         **index** (int) - The unique ID of the created storage
@@ -3147,7 +3144,8 @@ def create_shunt_as_capacitor(net, bus, q_mvar, loss_factor, **kwargs):
 
         **loss_factor** (float) - loss factor tan(delta) of the capacitor bank
 
-        **kwargs are passed to the create_shunt function
+    OPTIONAL:
+        same as in create_shunt, keyword arguments are passed to the create_shunt function
 
 
     OUTPUT:
@@ -3347,7 +3345,7 @@ def create_dcline(net, from_bus, to_bus, p_mw, loss_percent, loss_mw, vm_from_pu
 
         **max_q_from_mvar** - Maximum reactive power at from bus. Necessary for OPF
 
-        **max_q_to_mvar ** - Maximum reactive power at to bus. Necessary for OPF
+        **max_q_to_mvar** - Maximum reactive power at to bus. Necessary for OPF
 
     OUTPUT:
         **index** (int) - The unique ID of the created element

pandapower/estimation/state_estimation.py

@@ -36,41 +36,46 @@ def estimate(net, algorithm='wls',
              **opt_vars):
     """
     Wrapper function for WLS state estimation.
+
     INPUT:
-        **net** - The net within this line should be created
+        **net** (pandapowerNet) - The net within this line should be created
+
+        **init** (string) - Initial voltage for the estimation. 'flat' sets 1.0 p.u. / 0° for all \
+            buses, 'results' uses the values from *res_bus* if available and 'slack' considers the \
+            slack bus voltage (and optionally, angle) as the initial values. Default is 'flat'
 
-        **init** - (string) Initial voltage for the estimation. 'flat' sets 1.0 p.u. / 0° for all
-        buses, 'results' uses the values from *res_bus* if available and 'slack' considers the
-        slack bus voltage (and optionally, angle) as the initial values. Default is 'flat'
     OPTIONAL:
-        **tolerance** - (float) - When the maximum state change between iterations is less than
-        tolerance, the process stops. Default is 1e-6
+        **tolerance** (float) - When the maximum state change between iterations is less than \
+            tolerance, the process stops. Default is 1e-6
 
-        **maximum_iterations** - (integer) - Maximum number of iterations. Default is 10
+        **maximum_iterations** (integer) - Maximum number of iterations. Default is 10
 
-        **calculate_voltage_angles** - (boolean) - Take into account absolute voltage angles and phase
-        shifts in transformers, if init is 'slack'. Default is True
+        **calculate_voltage_angles** (boolean) - Take into account absolute voltage angles and phase \
+            shifts in transformers, if init is 'slack'. Default is True
 
-        **zero_injection** - (str, iterable, None) - Defines which buses are zero injection bus or the method
-        to identify zero injection bus, with 'wls_estimator' virtual measurements will be added, with
-        'wls_estimator with zero constraints' the buses will be handled as constraints
-            "auto": all bus without p,q measurement, without p, q value (load, sgen...) and aux buses will be
-                identified as zero injection bus
-            "aux_bus": only aux bus will be identified as zero injection bus
-            None: no bus will be identified as zero injection bus
-            iterable: the iterable should contain index of the zero injection bus and also aux bus will be identified
-                as zero-injection bus
+        **zero_injection** (str, iterable, None) - Defines which buses are zero injection bus or the method \
+                to identify zero injection bus, with 'wls_estimator' virtual measurements will be added, with \
+                'wls_estimator with zero constraints' the buses will be handled as constraints
+
+                - "auto": all bus without p,q measurement, without p, q value (load, sgen...) and aux buses will be \
+                        identified as zero injection bus
+                - "aux_bus": only aux bus will be identified as zero injection bus
+                - None: no bus will be identified as zero injection bus
+                - iterable: the iterable should contain index of the zero injection bus and also aux bus will be identified \
+                    as zero-injection bus
+
+        **fuse_buses_with_bb_switch** (str, iterable, None) - Defines how buses with closed bb switches should \
+            be handled, if fuse buses will only fused to one for calculation, if not fuse, an auxiliary bus and \
+            auxiliary line will be automatically added to the network to make the buses with different p,q injection \
+            measurements identifieble
+
+                - "all": all buses with bb-switches will be fused, the same as the default behaviour in load flow
+                - None: buses with bb-switches and individual p,q measurements will be reconfigurated \
+                    by auxiliary elements
+                - iterable: the iterable should contain the index of buses to be fused, the behaviour is contigous e.g. \
+                    if one of the bus among the buses connected through bb switch is given, then all of them will still \
+                    be fused
 
-        **fuse_buses_with_bb_switch** - (str, iterable, None) - Defines how buses with closed bb switches should
-        be handled, if fuse buses will only fused to one for calculation, if not fuse, an auxiliary bus and
-        auxiliary line will be automatically added to the network to make the buses with different p,q injection
-        measurements identifieble
-            "all": all buses with bb-switches will be fused, the same as the default behaviour in load flow
-            None: buses with bb-switches and individual p,q measurements will be reconfigurated
-                by auxiliary elements
-            iterable: the iterable should contain the index of buses to be fused, the behaviour is contigous e.g.
-                if one of the bus among the buses connected through bb switch is given, then all of them will still
-                be fused
     OUTPUT:
         **successful** (boolean) - Was the state estimation successful?
     """

pandapower/opf/run_powermodels.jl

@@ -40,6 +40,9 @@ function run_powermodels(json_path)
                                         setting = Dict("output" => Dict("branch_flows" => true)))
     end
 
+    result["termination_status"] = string(result["termination_status"])
+    result["dual_status"] = string(result["dual_status"])
+    result["primal_status"] = string(result["primal_status"])
 
     return result
 end

pandapower/timeseries/output_writer.py

@@ -57,7 +57,7 @@ class OutputWriter(JSONSerializableClass):
         **output_path** (string, None) - Path to a folder where the output is written to.
 
         **output_file_type** (string, ".p") - output filetype to use.
-        Allowed file extensions: [*.xls, *.xlsx, *.csv, *.p, *.json]
+        Allowed file extensions: [.xls, .xlsx, .csv, .p, .json]
         Note: XLS has a maximum number of 256 rows.
 
         **csv_separator** (string, ";") - The separator used when writing to a csv file