.. _gridequivalentexample:

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Grid Equivalent Example
#############################

Here is an example of what you can do:

Create Example Network
--------------------------------------------------

First, we create an example network.

.. code:: python

	from pandapower import runpp
    from pandapower.networks import case9

	net = case9()
    
	# getting power flow results
	runpp(net)
    
    
Define Grid Areas
--------------------------------------------------
The created network is shown below. Assuming that the buses (red) [0, 3, 4, 8] belong to the internal subsystem which should be remained, and the external subsystem consists of buses (green) [1, 2, 5, 6, 7] that are going to be reduced. The boundary buses [4, 8] are belonging to the internal subsystem.

.. image:: /pics/gridequivalent/full_case9.png
	:width: 42em
	:alt: alternate Text
	:align: center
    

Execute Grid Equivalent Calculation
--------------------------------------------------

According to the above assumptions, input variables for the Ward-equivalent are:

.. code:: python

	# equivalent type
	eq_type = "ward"
    
	# internal buses: we don't need to give all internal buses to the function. Just one of them is enough.
	internal_buses = [0]
    
	# boundary buses
	boundary_buses = [4, 8]

Then we start the Ward-equivalent calculation:

.. code:: python

	net_eq = pp.grid_equivalents.get_equivalent(net, eq_type, boundary_buses, internal_buses)


Power Flow Results Comparison
--------------------------------------------------
We can compare the power flow results between the original grid "net" and the reduced grid "net_eq":

.. code:: python

	print("--- power flow (original grid) ---")
	net.res_bus
	print("--- power flow (reduced grid) ---")
	net_eq.res_bus

.. image:: /pics/gridequivalent/res_comparison.png
	:width: 42em
	:alt: alternate Text
	:align: center

It can be seen that the power flow results (**vm_pu**, **va_degree**) of the internal buses [0, 3, 4, 8] in both grids are the same (the difference is smaller than :math:`10^{-6}` pu or degree), i.e., the equivalent calculation is successful. The **p_mw** and **q_mvar** values at the boundary buses [4, 8] are different due to the created Ward elements. The figure below shows the reduced grid.

.. image:: /pics/gridequivalent/reduced_case9.png
	:width: 42em
	:alt: alternate Text
	:align: center

Equivalent Elements
--------------------------------------------------
We can print the calculated Ward elements using:

.. code:: python

	print("--- ward (original grid) ---")
	net.ward
	print("--- ward (reduced grid) ---")
	net_eq.ward
    
.. image:: /pics/gridequivalent/ward.png
	:width: 42em
	:alt: alternate Text
	:align: center

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.. Note::
    If you compare the resulting (x)ward-parameters between **pandapower** and **PowerFactory**, you will see they are different. 
    This is because in **PowerFactory** the admittance matrix is reconstructed according to a voltage sensitivity analysis, 
    which is not open-source and leads to the difference.