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Importing real-world data

Background​

In this first part of the data benchmarking series, we will show you how to import real-world data (in .csv format) into the gridmo platform, so you can use it to overlay with dynamic study results.

In this part, we will:

  • Import real-world data from a generating system into the gridmo platform.
  • Plot the real-world data.
tip

You can download the complete example project file used in this series from the below link. The example data file and the models required to run this example simulation are packaged with the gridmo Engine - no further configuration is required.

note

This multi-part example assumes you have a basic understanding of the gridmo platform. If you are new to gridmo, please see the Getting started guide.

Example​

1) Add the data you want to import into your Engine's Inputs folder​

In gridmo, you can import generic time-series data by using the Data Node.

Place the data file in the Inputs folder of your gridmo Engine (including subfolders as desired) and paste the relative file path to the inputs folder in the Data Node's Input file name field, such as gridmo\data\e002_q_step_data.csv.

danger

Currently, only .csv files are currently supported by the Data Node.

2) Create a new gridmo Project and add the following Nodes​

  • Start Node
  • Data Node
  • Plot Node
  • End Node

And connect the Nodes together as shown below.

example of a data connected to a plot

3) Configure the Data Node​

  • Double click on the Data Node to open the configuration window.
  • Set the Input file name to the relative path of the .csv file you want to import, such as gridmo\data\e002_q_step_data.csv.
  • Switch to the Define outputs tab.
  • Add the following OUTPUT commands to convert the columns in the .csv file to Internode Variables for use in gridmo.
Data Node's Outputs field
// Convert from CSV column names into Internode Variables
OUTPUT, COL=V_pu, NAME=i_ch_poc_v
OUTPUT, COL=P_MW, NAME=i_ch_poc_p
OUTPUT, COL=Q_MVAr, NAME=i_ch_poc_q

The above commands convert each column from the name in the .csv file to an Internode Variable for use in gridmo. Specifically:

  • The column V_pu can be accessed by Nodes connected to this Data Node using i_ch_poc_v
  • The column P_MW can be accessed by Nodes connected to this Data Node using i_ch_poc_p
  • The column Q_MVAr can be accessed by Nodes connected to this Data Node using i_ch_poc_q
tip

If your .csv file is using a different unit than the unit you want for your simulation, you can use the optional argument VALSCALE= to apply a multiplicative scale.

You do not need to directly modify the source .csv file.

For example, if you .csv data file has voltage in kV (with a 33 kV base) you can use the following command:

Example of using VALSCALE= to convert kV to per unit
OUTPUT, COL=V_at_33kV, NAME=i_ch_poc_v, VALSCALE=1/33

4) Configure the Plot Node​

  • Double click on the Plot Node to open the configuration window.
  • Set the Plot type to PDF to output a PDF file.
  • Enter an output file name, such as Data example import.
  • Enter a plot title, such as Imported real-world data into gridmo.
  • In the Define Subplots tab:
    • Set the x-axis minimum 3 and maximum to 10
    • Under Subplots select 1 page, 2 rows and 3 columns.
    • Click on the + to add a new subplot. For each subplot:
      • Enter a title in Subplot title, such as Vpoc.
      • Under y-axis Channels enter each of the Internode Variables with the double curly brackets, such as {{i_ch_poc_v}}

example screenshot of configured subplots in plot Node

5) Launch the simulation​

  • Launch the simulation
  • The output plot should show the real-world data you imported plotted as per your configuration of the Plot Node.

6) Review the results​

  • We can see in our outputs folder (example below) that we have plotted the real-world data:
    • ✅ Point of connection voltage, active power and reactive power are all plotted.
    • ✅ We can see in our data that the test being recorded appears to be a single reactive power step.

example of results from step 1, showing data only, POC P Q and V

Next step​

In the next step, we will overlay the real-world data we added in this step with the results of a dynamic study.