quickstart.md

Quick Start

In this quick start a simple 10kV network as below is calculated. A line connects two nodes. One node has a source. The other node has a symmetric load. The full code for this section is provided in {{ "quick_example.py".format(gh_link_head_blob) }}.

node_1 ---line_3--- node_2
 |                    |
source_5            sym_load_4

The library uses a graph data model to represent the physical components and their attributes, see Graph Data Model.

Before we start working on the network, we need first import the main model class as well as some helper functions for enumerations and meta data.

from power_grid_model import LoadGenType
from power_grid_model import PowerGridModel
from power_grid_model import initialize_array

Input Data

The library uses dictionaries of numpy structured arrays as the main (input and output) data exchange format between Python interface and C++ core. Detailed design of data interface can be found in Native Data Interface.

The helper function {py:class}power_grid_model.initialize_array can be used to easily generate an array of the correct format.

# node
node = initialize_array('input', 'node', 2)
node['id'] = [1, 2]
node['u_rated'] = [10.5e3, 10.5e3]

The code above generates a node input array with two nodes, and assigns the attributes of the nodes to the array. Similarly, we can create input arrays for line, load, and generation. A dictionary of such arrays is used for input_data and update_data.

# line
line = initialize_array('input', 'line', 1)
line['id'] = [3]
line['from_node'] = [1]
line['to_node'] = [2]
line['from_status'] = [1]
line['to_status'] = [1]
line['r1'] = [0.25]
line['x1'] = [0.2]
line['c1'] = [10e-6]
line['tan1'] = [0.0]
line['i_n'] = [1000]
# load
sym_load = initialize_array('input', 'sym_load', 1)
sym_load['id'] = [4]
sym_load['node'] = [2]
sym_load['status'] = [1]
sym_load['type'] = [LoadGenType.const_power]
sym_load['p_specified'] = [2e6]
sym_load['q_specified'] = [0.5e6]
# source
source = initialize_array('input', 'source', 1)
source['id'] = [5]
source['node'] = [1]
source['status'] = [1]
source['u_ref'] = [1.0]
# all
input_data = {
    'node': node,
    'line': line,
    'sym_load': sym_load,
    'source': source
}

Another example of how to create components can be found in Input data.

The keys of the dictonary of arrays are unique and should match with the respective `type name` of the component. 
See, e.g., that type name of {hoverxref}`user_manual/components:node` is `node`.

Instantiate Model

We can instantiate the model by calling the constructor of {py:class}power_grid_model.PowerGridModel

model = PowerGridModel(input_data, system_frequency=50.0)

Power Flow Calculation

To run calculations, use the object methods {py:class}power_grid_model.PowerGridModel.calculate_power_flow or {py:class}power_grid_model.PowerGridModel.calculate_state_estimation functions. Refer Calculations for more details on the many optional arguments.

result = model.calculate_power_flow()

Both input and output data are dictionaries of structured numpy arrays. We can use pandas to convert them to data frames and print them.

print('Node Input')
print(pd.DataFrame(input_data['node']))
print('Node Result')
print(pd.DataFrame(result['node']))

The result data can then be viewed in tabular forms.

Node Input
   id  u_rated
0   1  10500.0
1   2  10500.0
Node Result
   id  energized      u_pu             u   u_angle
0   1          1  0.999964  10499.619561 -0.000198
1   2          1  0.994801  10445.415523 -0.003096

Validation

To validate the input_data and update_data for valid values, use {py:class}power_grid_model.validation.validate_input_data and {py:class}power_grid_model.validation.validate_batch_data. Refer to Data Validator for more details

Batch Data

Optionally, we can add batch scenarios using the update_data argument. The code below initializes a symmetric load update array with a shape of (5, 4). This is in the form of $\text{number of batches} \times \text{number of components}$. The update_data is an optional argument to the {py:class}power_grid_model.PowerGridModel object or the calculation functions.

from power_grid_model import initialize_array

sym_load_update = initialize_array('update', 'sym_load', (5, 4))
# --- Add other sym_load attributes --- 
update_data = {
    "sym_load": sym_load_update
}

model = PowerGridModel(input_data=input_data, update_data=update_data)