flexmeasures-client 0.1.1

Async client to connect to the FlexMeasures API

FlexMeasures Client

The FlexMeasures Client provides a python package to connect to a FlexMeasures server to manage flexible assets.

The Flexmeasures Client package provides functionality for authentication, posting sensor data, triggering schedules and retrieving schedules from a FlexMeasures instance through the API.

Getting Started

To get started using the FlexMeasures Client package first an account needs to be registered with a FlexMeasures instance or a local FlexMeasures instance needs to be created. Registring a to a FlexMeasures instance can be done through Seita BV. To create a local instance of FlexMeasures follow the FlexMeasures documentation.

In this example we are connecting to localhost:5000, To connect to a different host add the host in the initialization of the client.

Install using pip:

pip install flexmeasures-client

Initialization and Authentication:

from client import FlexMeasuresClient
client = FlexMeasuresClient(email="[e-mail]", password="pw")

Retrieve available assets and sensors:

assets = await client.get_assets()
sensors = await client.get_sensors()

Post a measurement from a sensor:

await client.post_measurements(
        sensor_id=<sensor_id>, # integer
        start="2023-03-26T10:00+02:00", #iso datetime
        duration="PT6H", # iso timedelta
        values=[1,2,3,4], # list
        unit="kWh",
        entity_address=<sensor_entity_address>, # string
    )

With FlexMeasures a schedule can be requested to optimize at what time the flexible assets can be activated to optimize for price of energy or emissions. The calculation of the schedule can take some time depending on the complexity of the calculations and therefore the requests have been split in a trigger for the schedule and a retrieve schedule call. Trigger a schedule:

schedule_uuid = await flexmeasures_client.trigger_storage_schedule(
        sensor_id=<sensor_id>, # int
        start="2023-03-26T10:00+02:00", # iso datetime
        duration="PT12H", #iso timedelta
        soc_unit="kWh",
        soc_at_start=50, #soc_units (kWh)
        soc_targets=[
            {
                "value": 100, #soc_units (kWh)
                "datetime": "2023-03-03T11:00+02:00", # iso datetime
            }
        ],
        consumption_price_sensor=<consumption_price_sensor_id>, # int
    )

The trigger_storage_schedule return a schedule_uuid. This can be used to retrieve the schedule. The client will re-try if until the schedule is available or the MAX_POLLING_STEPS of 10 is reached. Retrieve schedule:

schedule = await flexmeasures_client.get_schedule(
            sensor_id=<sensor_id>, #int
            schedule_id="<schedule_uuid>", # uuid
            duration="PT45M" # iso timedelta
        )

The schedule returns a Pandas DataFrame that can be used to regulate the flexible assets.

Making Changes & Contributing

This project uses pre-commit, please make sure to install it before making any changes:

pip install pre-commit
cd flexmeasures-client
pre-commit install

It is a good idea to update the hooks to the latest version:

pre-commit autoupdate

Don’t forget to tell your contributors to also install and use pre-commit.

Note

This project has been set up using PyScaffold 4.4. For details and usage information on PyScaffold see https://pyscaffold.org/.