WSU-Restoration Application

This repository contains the restoration application for IEEE 9500-node model (https://github.com/GRIDAPPSD/Powergrid-Models/tree/develop/blazegraph/test/dss/WSU). The application is hosted on GridAPPS-D platform.

Layout

Please clone the repository https://github.com/GRIDAPPSD/gridappsd-docker (refered to as gridappsd-docker repository) next to this repository (they should both have the same parent folder)

Creating the restoration application container

1. From the command line execute the following commands to build the wsu-restoration container

   osboxes@osboxes> cd WSU-Restoration
   osboxes@osboxes> docker build --network=host -t wsu-restoration-app .

2. Add the following to the gridappsd-docker/docker-compose.yml file

   wsu_res_app:
   image: wsu-restoration-app
   volumes:
     - /opt/ibm/ILOG/CPLEX_Studio129/:/opt/ibm/ILOG/CPLEX_Studio129
   environment:
     GRIDAPPSD_URI: tcp://gridappsd:61613
   depends_on:
     - gridappsd   
     
   # Adjust the CPLEX version based on which you have

3. Run the docker application

   osboxes@osboxes> cd gridappsd-docker
   osboxes@osboxes> ./run.sh
   
   # You will now be inside the container, the following starts gridappsd
   
   gridappsd@f4ede7dacb7d:/gridappsd$ ./run-gridappsd.sh
   

Executing the restoration application container

1. Getting the container ready

   # Open a new terminal
   
   osboxes@osboxes> cd WSU-Restoration
   osboxes@osboxes> docker exec -it gridappsddocker_wsu_res_app_1 bash
   
   # This will take you to the application container. Following steps will make the application container ready to run with all requirements
   
   a. Once you are inside the container, the following installs CPLEX to be used by the application 
   
   root@1b762c641f24:/usr/src/gridappsd-restoration# cd /opt/ibm/ILOG/CPLEX_Studio129/cplex/python/3.6/x86-64_linux/ ; python setup.py install
   
   
   b. Note that the python version supported by CPLEX_Studio129 is 3.6. If you have a different version of CPLEX, it might require different version of python for interface. In such a case, make sure the application container has correct version of python installed.
   
   
   c. Next, get back to the path where application is mounted
   
   root@1b762c641f24:/opt/ibm/ILOG/CPLEX_Studio129/cplex/python/3.6/x86-64_linux# cd /usr/src/gridappsd-restoration
   
   
   d. The following runs the application from terminal
   
   root@1b762c641f24:/usr/src/gridappsd-restoration# cd Restoration
   root@1b762c641f24:/usr/src/gridappsd-restoration/Restoration# python main.py [simulation_ID] '{"power_system_config":  {"Line_name":"_AAE94E4A-2465-6F5E-37B1-3E72183A4E44"}}'    

2. Start the platform

   # At this point, we are ready to start the platform using browser: localhost:8080/ 
   
   # Run the platform and take the [simulation_ID] from the browser to Step 1.d for running the application in the terminal.
   

Visualization

To start the application through the viz follow the directions here: https://gridappsd.readthedocs.io/en/latest/using_gridappsd/index.html#start-gridapps-d-platform

Fault events can be added using the Test Configuration page. The added events for a simulation can be seen in the Events view. An example of the event is shown here: https://github.com/Jeffrey-Simpson/gridappsd-cmd/blob/master/saved_examples/test_scheduled_event_1_fault.json

Note that the WSU-Restoration application gets triggered only when the fault event is added in the test case. During normal operation, application stays quite.

Forming optimization problem

In the optimization problem, test feeders are modeled as graph; G (V, E), where V is set of nodes and E is set of edges. The graph and line parameters of the test feeder can be extracted from (https://github.com/shpoudel/D-Net).

Get real-time topology and load data of the test case

First, the real time topology of the test case is extracted from the operating feeder in platform (top_identify.py). Then, load data for each node is obtained (get_Load.py) and stored in json format to be used in linear power flow while writing constraints for optimization problem.

Isolation and Restoration

Once fault is identified in the test case, Isolation.py is invoked which isolates the fault from all possible directions. Then restoration_WSU.py solves the optimization. The output of optimization is the list of switches to toggle for reconfiguration such that load restored is maximixed. Grid-forming DERs can also be utilized to form islands if required.