How to get model output

The Get Site Forecast endpoint returns the optimal forecast, constructed from multiple model outputs based on a priority scheme, as described here. If you need the raw output of a specific model, use the Get Model Output endpoint instead.

Step 1: Get the model IDs

Before querying a model’s output you need its unique identifier, the model ID. Retrieve it using the List Site Models endpoint. You can filter the results to only ML or physical models by setting the model_type parameter to ai or physical, respectively.

Get model IDs

import requests

api_key = "Your API key" # Set your API key
site_id = "a923653c-26f1-1b29-955d-ffde5d182276" # Set the site ID

url = f"https://api.rebase.energy/platform/v2/sites/{site_id}/models"
headers = {"Authorization": api_key, "Content-Type": "application/json"}

response = requests.get(url, headers=headers)
response.raise_for_status()
response = response.json()

Response example

[
    {   
        'id': '0c456ecb-d245-4569-bc8e-4e67a566dcd72',
        'name': 'SolarForecast_Ensemble_QuantReg',
        'label': 'ML-Acc-Medium',
        'version': 1,
        'display_name': 'ML-Acc-Medium',
        'priority': 3,
        'output_types': [],
        'state': [{'state': 'training', 'timestamp_utc': '2025-09-15T00:32:48.391452Z'}]},
    {
        'id': '1d567fa0-e356-467a-cd9f-5f78b901c345',
        'name': 'SolarForecast_Ensemble_QuantReg',
        'label': 'ML-Acc-Short',
        'version': 2,
        'display_name': 'ML-Acc-Short',
        'priority': 2,
        'output_types': [],
        'state': [{'state': 'training', 'timestamp_utc': '2025-09-15T00:41:51.224815Z'}]}
]

The response is a list of models configured for the site, with the following fields:
id: The unique model identifier. Use this as model_id in Step 2.
name: The name of the forecasting model.
label: A short label for the model.
version: The version number of the model.
display_name: The name shown for the model in the platform.
priority: The model’s priority rank within the site’s forecast combination.
output_types: The output types the model produces.
state: The model’s training state history.

Step 2: Get the latest model output

Using the model ID from Step 1, query the latest output for that model with the Get Model Output endpoint. If no start_date is provided, the output is returned from today 00:00 UTC onwards.

Get latest model output

import requests

api_key = "Your API key" # Set your API key
model_id = "1d567fa0-e356-467a-cd9f-5f78b901c345" # Set the model ID

url = f"https://api.rebase.energy/platform/v2/models/{model_id}/output"
headers = {"Authorization": api_key, "Content-Type": "application/json"}

response = requests.get(url, headers=headers)
response.raise_for_status()
response = response.json()

Response example

{
    "model_id": "1d567fa0-e356-467a-cd9f-5f78b901c345",
    "model_version": 2,
    "model_name": "SolarForecast_Ensemble_QuantReg",
    "model_label": "ML-Acc-Short",
    "priority": 2,
    "as_of": "2025-10-01T09:40:52.800337Z",
    "forecast": [
        0.0,
        0.0,
        0.0,
        0.0,
        0.0
    ],
    "valid_time": [
        "2025-10-01T00:00:00Z",
        "2025-10-01T00:15:00Z",
        "2025-10-01T00:30:00Z",
        "2025-10-01T00:45:00Z",
        "2025-10-01T01:00:00Z"
    ],
    "capacity": [
        76000.0,
        76000.0,
        76000.0,
        76000.0,
        76000.0
    ]
}

The response is a JSON object with the following fields:
model_id: The unique identifier of the model.
model_version: The version number of the model.
model_name: The name of the forecasting model.
model_label: The label of the model, i.e. the label field from Step 1.
priority: The model’s priority rank within the site’s forecast combination.
as_of: The reference time, i.e. the forecasts returned are the most recent ones that were available at this time.
forecast: It contains the forecast values.
valid_time: It contains the target times, i.e. the periods which are forecasted.
capacity: It contains the site capacity in kilowatts [kW] for each target period.

Query historical model output

Every model run is archived, so you can retrieve a model’s output as it was issued at an earlier point in time. This is the model level equivalent of the historical site forecast. You can provide the following request parameters. Start date start_date
Specify the starting target period of the forecast. If not provided, it defaults to today 00:00 UTC.
Example: "2025-08-02 15:00" End date end_date
Specify the ending target period of the forecast.
Example: "2025-08-02 16:00" Reference time as_of
Specify the reference time. The API will return the most recent model output which was available at the reference time and covers the period between start_date and end_date. If not provided, then by default the request time is considered as reference time.
Example: "2025-08-01 11:00" Time zone tz
Specify the time zone. The default time zone is UTC.
Example: "CET" Output type output_type
Specify which output of the model to return. The default is "forecast". "clearky" can be used for the physical models clearsky output. Normalization handling normalization_handling
Specify if the output is returned in absolute values "auto" or normalized by the capacity "disabled". The default is "auto". In the example below we want to query the output of the model with ID 1d567fa0-e356-467a-cd9f-5f78b901c345 for the period between 2025-08-02 15:00 and 2025-08-02 16:00 which was available at 11:00 in the morning the previous day, i.e. the day-ahead forecast. All times are in UTC.

Get historical model output

import requests

api_key = "Your API key" # Set your API key
model_id = "1d567fa0-e356-467a-cd9f-5f78b901c345" # Set the model ID
start_date = "2025-08-02 15:00" # Set the start date
end_date = "2025-08-02 16:00" # Set the end date
as_of = "2025-08-01 11:00" # Set the reference time

url = f"https://api.rebase.energy/platform/v2/models/{model_id}/output"
headers = {"Authorization": api_key, "Content-Type": "application/json"}
params = {
    "start_date": start_date,
    "end_date": end_date,
    "as_of": as_of
}

response = requests.get(url, headers=headers, params=params)
response.raise_for_status()
response = response.json()

Response example

{
    "model_id": "1d567fa0-e356-467a-cd9f-5f78b901c345",
    "model_version": 2,
    "model_name": "SolarForecast_Ensemble_QuantReg",
    "model_label": "ML-Acc-Short",
    "priority": 2,
    "as_of": "2025-08-01T11:00:00Z",
    "forecast": [
        49076.07965239071,
        46358.204584880375,
        43007.28450049107,
        38891.100735672335,
        33866.317940143104
    ],
    "valid_time": [
        "2025-08-02T15:00:00Z",
        "2025-08-02T15:15:00Z",
        "2025-08-02T15:30:00Z",
        "2025-08-02T15:45:00Z",
        "2025-08-02T16:00:00Z"
    ],
    "capacity": [
        76000.0,
        76000.0,
        76000.0,
        76000.0,
        76000.0
    ]
}

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Rebase Dashboard

Step 1: Get the model IDs

Step 2: Get the latest model output

Query historical model output

​Step 1: Get the model IDs

​Step 2: Get the latest model output

​Query historical model output

Step 1: Get the model IDs

Step 2: Get the latest model output

Query historical model output