Transform Models

Transform Model Help

This process transforms user OpenDSS models into a format understood by DISCO so that it can perform simulation and analysis with the models.

Given an input path of source data DISCO can determine the types of analysis it supports. The input path can be one of:

• a GEM config file; the JSON schema definition is here - GEM Model.

• a directory path which contains a format.toml with a source type definition. The source types are:

  • EpriModel

  • SourceTree1Model

  • SourceTree2Model

Input File

The --help option displays the types of analysis the source models support. For example, if the input path is a GEM file:

$ disco transform-model ./gem-file.json --help

Available analysis types: snapshot

For additional help run one of the following:
    disco transform-model ./gem-file.json snapshot --help

Input Directory

If the input path is a directory, for example, with type = SourceTree1Model in format.toml.

$ disco transform-model tests/data/smart-ds/substations/ --help

Available analysis types: snapshot time-series

For additional help run one of the following:
    disco transform-model tests/data/smart-ds/substations/ snapshot --help
    disco transform-model tests/data/smart-ds/substations/ time-series --help

Note

By default, the name of PV deployments directory is hc_pv_deployments, if the PV deployments are located in another directory, please specify the right directory by using option -P/--pv-deployments-dirname in the transform-model command.

Load Shape Data files

By default, DISCO replaces relative paths to load shape data files with absolute paths and does not copy them. This reduces time and consumed storage space. However, it also makes the directory non-portable to other systems.

If you want to create a portable directory with copies of these files, add this flag to the command:

$ disco transform-model tests/data/smart-ds/substations time-series -c
$ disco transform-model tests/data/smart-ds/substations time-series --copy-load-shape-data-files

DISCO Model in Depth

PyDSS Controllers

If you have custom controllers that need to be applied to simulation, please make the controllers are registered via PyDSS first.

Suppose we have particular controller settings defined in a my-custom-controllers.toml file:

[my_volt_var_curve]
Control1 = "VVar"
Control2 = "None"
Control3 = "None"
...

$ pydss controllers register PvController /path/my-custom-controllers.toml

Once registered, the following information could be used to create the input config related to pydss_controllers.

{
    "name": "project123",
    "controller_type": "PvController"
}

By default, the target PyDSS file that the PyDSS controller would be applied to is the deployment file, you do not need to specify the target DSS files. However, if you want to specify the target DSS files here, other than the deployment file,

{
    "name": "project123",
    "controller_type": "PvController",
    "targets": [
        "/data/dss/file1.dss",
        "/data/dss/file2.dss"
    ]
}

And, pydss_controllers supports multiple PyDSS controllers here,

[
    {
        "name": "project123",
        "controller_type": "PvController"
    },
    {
        "name": "project123",
        "type": "StorageController"
    },
]

Model Schema

DISCO uses pydantic models to define the schema of model inputs for each type of analysis. Given a type of analysis in DISCO, the schema shows all attributes used to define the analysis models.

Show Schema

The input configurations in JSON should meet the specifications defined by DISCO. To show the schema of a given analysis type, for example, SnapshotImpactAnalysisModel using this command with --mode show-schema option,

$ disco simulation-models --mode show-schema SnapshotImpactAnalysisModel

Show Example

A data example may be more straightforward, use --mode show-example option,

$ disco simulation-models --mode show-example SnapshotImpactAnalysisModel --output-file=disco-models/configurations.json
$ cat disco-models/configurations.json
[
    {
        "feeder": "J1",
        "tag": "2010",
        "deployment": {
            "name": "deployment_001.dss",
            "dc_ac_ratio": 1.15,
            "directory": "disco-models",
            "kva_to_kw_rating": 1.0,
            "project_data": {},
            "pv_locations": [],
            "pydss_controllers": null
        },
        "simulation": {
            "start_time": "2013-06-17T15:00:00.000",
            "end_time": "2014-06-17T15:00:00.000",
            "step_resolution": 900,
            "simulation_type": "Snapshot"
        },
        "name": "J1_123_Sim_456",
        "base_case": null,
        "include_voltage_deviation": false,
        "blocked_by": [],
        "job_order": null
    }
]

Validate Inputs

If you want to prepare the models manually then you must generate them in a JSON file and then validate them to make sure they match the schema.

$ disco simulation-models validate-file disco-models/configurations.json

The ValidationError will be raised if any input does not meet the specification defined by DISCO. The error messages should provide corrective action.