When you’re scheduling energy consumption or exports, it’s essential to account for local generation—like a PV array or wind turbine. Flatpeak lets you submit both forecasted and actual local generation data. These records can feed into:
  • Energy scheduling endpoints (for forward planning)
  • Cost reporting endpoints
To track this, set the tariff_rate field to LOCAL when submitting metering data in either instant or aggregated cost reporting use case.

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Forecast generation

Use this to help Flatpeak plan ahead:
  • Submit expected generation via interval or cumulative metering endpoints.
  • Set the confidence parameter to anything less than 1.
Example request
curl --request PUT \
  --url https://api.flatpeak.com/meters/interval \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '[
  {
    "location_id": "loc_641b90b758fb8e6293716e40",
    "direction": "IMPORT",
    "tariff_rate": "LOCAL",
    "confidence": 0.9,
    "units": "W",
    "value": 968,
    "start_time": "2025-08-01T10:30:00Z",
    "end_time": "2025-08-01T11:00:00Z",
  }
]'

​
Actual generation

Use this to log real production data:
  • Submit actual generation to the same endpoints.
  • Set confidence to 1 — this will overwrite any previously submitted records for the same period.
Example request
curl --request PUT \
  --url https://api.flatpeak.com/meters/interval \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '[
  {
    "location_id": "loc_641b90b758fb8e6293716e40",
    "direction": "IMPORT",
    "tariff_rate": "LOCAL",
    "confidence": 1,
    "units": "W",
    "value": 1014,
    "start_time": "2025-08-01T10:30:00Z",
    "end_time": "2025-08-01T11:00:00Z"
  }
]'