OutageMap

OutageMap is an open-source software that can be used to generate weather related outage data for a given power distribution network. The framework uses a set of fragility curves to describe the extent of weather impacts on physical features, which can be applied in a straightforward way to real-world networks and extreme weather conditions once data of the actual physical networks and their past impact outcomes becomes available

This is the code repository for the following paper. To use this repo, please cite:

Kenneth McDonald, Colin Le, and Zhihua Qu. "Open-Source Modeling of Extreme Weather Impact on Distribution Networks." Accepted to Open Source Modeling and Simulation of Energy Systems (OSMSES), 2024.

Installing OutageMap

OutageMap was designed using Python 3.11.9 and Anaconda.

First, clone or download the repository.

If you do not have an existing Anaconda installation, go to https://www.anaconda.com/products/individual, click on skip registration, and then click the green download button.

In the windows search bar, type and select Anaconda Prompt. Open the prompt and navigate to OutageMap/Conda Environment Setup using cd commands. This is where the enviroment .yml file is currently stored. Once in the directory run the following command:

conda env create -f environment.yml

This creates the Python environment named OutageMap, with all the packages needed to run the software.

To activate the environment, run:

conda activate OutageMap

Move back to the main directory OutageMap using

cd ..

Running the Example

Collecting the Network Data

Inside the repo folder, navigate to the P3R folder and then the DSS folder. Upon downloading the repository, the OpenDSS files used for the simulation presented in the paper are already given.

To redownload them, you can use the following:

1. If you do not have one, create a free AWS account and download the AWS CLI interface from: https://awscli.amazonaws.com/AWSCLIV2.msi. Check to make sure AWS was installed correctly by running the following in a Command Prompt:

   aws --version 

2. In the same Command Prompt navigate to the OutageMap/P3R/DSS and run the command

   mkdir P3R && cd P3R && mkdir profiles && mkdir scenarios && cd scenarios && mkdir base_timeseries && cd base_timeseries && mkdir opendss && cd opendss && cd ../../..

   to create the folders and empty subdirectories.

3. Run each command to download the files

   aws s3 cp s3://oedi-data-lake/SMART-DS/v1.0/2018/SFO/P3R/scenarios/base_timeseries/opendss/ ./scenarios/base_timeseries/opendss --recursive --no-sign-request

   aws s3 cp s3://oedi-data-lake/SMART-DS/v1.0/2018/SFO/P3R/profiles/ ./profiles --recursive --no-sign-request

   Once the data has completed downloading, you may close the command prompt.

4. Navigate to OutageMap/P3R/DSS/P3R/scenarios/base_timeseries/opendss/p3rhs0_1247/p3rhs0_1247--p3rdt1052 and you should now see the files

   • Buscoords.dss
   • Capacitors.dss
   • Lines.dss
   • LineCodes.dss
   • Loads.dss
   • Loadshapes.dss
   • Master.dss
   • Transformers.dss

   For the final step, we now want to copy these files, along with the folder labeled OutageMap/P3R/DSS/P3R/profiles to OutageMap/P3R/DSS/profiles. Then folder OutageMap/P3R/DSS/P3R can be removed.

5. Open OutageMap/P3R/DSS/Loadshapes.dss in Notepad, press Ctrl+F and replace every occurence of ../../../../../profiles to profiles.

Extracting Data from OpenDSS files

To extract the data from the OpenDSS circuit into Python, run OutageMap/importData.py by calling the command

python importData.py

Upon successful execution, you should obtain the graph of the network below

Collection of Extreme Weather Events

To import the weather event from the CSV into Python, run OutageMap/getWeather.py by calling the command:

python getWeather.py

The steps to obtained the weather event CSV are detailed in Extreme Weather Events from NOAA.

Conversion of Weather Features to Weather Impact Score

To scale the data and convert to a weather impact score, run OutageMap/findWeatherImpact.py by calling the command:

python findWeatherImpact.py

Generating the Outage Data

To generate the outage data, run OutageMap/main.py by calling the command:

python main.py

Upon successful execution, you should obtain the outage map below

Other Information

Extreme Weather Events from NOAA

The collection of extreme weather events starts on NOAA’s Storm Event Database. As stated in the paper, the chosen event for this tutorial is a “bomb cyclone” event that occurred on March 21st, 2023 in the Greater San Francisco Area.

We start by heading to the site at https://www.ncdc.noaa.gov/stormevents/.

1. We then choose California in the “Select State or Area” and press Search.

2. The next page is a advanced search tool. We set

   • Set the start and end data to 03/21/2023 and 03/22/2023
   • San Francisco for the County
   • All events for event type

   and then press search.

3. The results, as shown below, indicate 7 events that occurred during March 21st all relating to strong or high wind events. To download this data, we click CSV Download, which is encased in a black box in image below.

Next, we open the downloaded CSV to modify the contents through the following:

1. We only need one entry to define the event, so we take the end date and time of the last row, and move it to the first row. Rows 3-8 can be deleted after.

2. The next step is to convert the time zone from PST to UTC since NLDAS2 requires UTC time. To do so, we change the start time to 1900, the end date to be 3/22/2023 and the end time to be 0500.

3. Once these changes have been made, the file can be saved in the OutageMap directory and closed.