Skip to content

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

32 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Hosting Capacity Runner

Python script to request run for hosting capacity work package.

Setup

Run the following to install dependencies.

pip install -r requirements.txt

Usage

  1. Update the auth_config.json file to with the authentication details for the Zepben EWB instance you are connecting to

  2. Update the config.json file with the feeders, years, and scenarios you want to run.

  3. Run the run_forecast_work_package.py python script passing the directory where the auth_config.json and config.json files are located (If no config directory is passed it will look for the config files in the current directory).

    ./run_forecast_work_package.py ./config

The monitor_progress.py script can also be used to retrieve and print progress of your work package.

Interventions

Use run_intervention_work_package.py ./config to run an Intervention work package against a prior (base) work package. Set INTERVENTION_TYPE near the top of the script to choose which intervention to run (COMMUNITY_BESS, LV_STATCOMS, DISTRIBUTION_TAP_OPTIMIZATION, DISTRIBUTION_TX_OLTC, TARIFF_REFORM, CONTROLLED_LOAD_HOT_WATER, DVMS, or PHASE_REBALANCING) and BASE_WORK_PACKAGE_ID to point at the base work package's ID, then edit the relevant build_..._intervention() function for that type's parameters.

Calibration

  1. Use run_calibration.py ./config to launch a calibration workflow.
  2. Modify and use monitor_calibration_run.py ./config to monitor the status of a calibration workflow.
  3. Use check_calibration_sets.py ./config to retrieve the IDs of all calibration results that have been run.
  4. Modify and use get_calibration_transformer_settings.py ./config to retrieve the calculated distribution transformer tap settings from the calibration run.

These settings can then be configured in a hosting capacity work package to apply the tap settings to the models.

Workflow

A typical calibration workflow is as follows:

flowchart TD
  A[Start: Run calibration model study] --> B[Run simulation during low absolute demand period to determine tap positions]
  B --> C[Define set of tap positions for use in Hosting Capacity Method HCM]
  C --> D[Prepare for model evaluation across multiple time periods; using above tap position in config]
  D --> E[Run simulation for one time period]
  E --> F[Collect outputs: voltages, flows, etc.]
  F --> G[Evaluate model accuracy]
  G --> H{More time periods to test?}
  H -- Yes --> E
  H -- No --> I[End: Use results to assess model calibration]
Loading

About

Python script to request run for hosting capacity work package.

Resources

Stars

0 stars

Watchers

1 watching

Forks

Releases

Packages

Used by

Contributors

Languages