What is a Quick Switch?

We define a Quick Switch as an analysis conducted against an account using our Typical Baseline data. Typical Baselines are approximations for usage and solar production given the geographical location of the Account via the Account Address.

What is the difference between a Quick Switch and a Full Switch Analysis?

As noted above a Quick Switch uses Typical Baseline data as a approximation. A Full Switch uses user supplied data profiles such a real-world hourly usage and solar production data that is housed in a profile. The use of a custom user-supplied profile in a Savings Analysis request will trigger a Full Switch.

Quick Switch Template

{
    "accountId": "c02af6c6-9cb1-4ea1-bd82-61e419e0a754",
    "fromDateTime": "2025-10-01T00:00:00+00:00",
    "useIntelligentBaselining": true,
    "propertyInputs": [
        {
            "keyName": "projectDuration",
            "dataType": "INTEGER",
            "dataValue": "20"
        },
        {
            "keyName": "baselineType",
            "dataType": "STRING",
            "dataValue": "typicalSolarPv",
            "scenarios": "after,solar",
            "operator": "-"
        },
        {
            "keyName": "solarPvLoadOffset",
            "unit": "%",
            "dataValue": "80",
            "scenarios": "after,solar"
        },
        {
            "keyName": "rateInflation",
            "dataType": "DECIMAL",
            "dataValue": "1.9",
            "scenarios": "solar"
        },
        {
            "keyName": "baselineType",
            "dataType": "STRING",
            "dataValue": "typicalElectricity",
            "scenarios": "before,after"
        },
        {
            "keyName": "rateInflation",
            "dataType": "DECIMAL",
            "dataValue": "3",
            "scenarios": "before,after"
        },
        {
            "keyName": "masterTariffId",
            "displayName": "Residential",
            "dataType": "INTEGER",
            "dataValue": "512",
            "scenarios": "before"
        },
        {
            "keyName": "lseId",
            "displayName": "Georgia Power Co",
            "dataType": "INTEGER",
            "dataValue": "2756",
            "scenarios": "before"
        },
        {
            "keyName": "tariffCode",
            "displayName": "R-30",
            "dataType": "STRING",
            "dataValue": "R-30",
            "scenarios": "before"
        }
    ],
    "rateInputs": [
        {
            "chargeType": "CONSUMPTION_BASED",
            "chargePeriod": "MONTHLY",
            "transactionType": "BUY",
            "rateBands": [
                {
                    "rateAmount": 0.15
                }
            ],
            "scenarios": "solar"
        }
    ]
}

Supplemental Context:

As you can see above the request begins with our top level definitions such as the account identifier accountId (or providerAccountId if you choose), starting point (fromDateTime) and the indication that we are enabling intelligent baselining (useIntelligentBaselining).

`propertyInputs` List

The next component will be our property inputs. These are objects supplied as key/value pairs that have implications for the underlying calculation. These could be designations to pull in "Profile" data (example "keyName": "profileId"), or they could be criteria that influence cost, tiering, credits, or other account specific behavior impacting the analysis (example "keyName": "lowIncomeCustomer"). Our collection of properties are extensive, so we recommend a thorough read through of our Properties documentation to ensure you have a good grasp on how to identify, unpack, and facilitate their use in your savings analyses for optimal results.

Because this is a Quick Switch we are using Arcadia's typicalElectricity & typicalSolarPv properties. These stand in as helpful default approximations when real world data is not available. When using out Typical Baselines you will need to ensure "useIntelligentBaselining": true.

`rateInputs` List

This list houses any custom rates or adjustment we want to make to the calculation. You can read more about user adjusted rates and contracted rates with example request snippets to help guide your implementation. In this template we are mimicking a PPA at a $0.15/kWh rate. You could also include supplemental items that may not be captured by our Tariff models such as local or state taxes. On the subject of handling supplemental inputs like taxes and we outline our modeling policy here, please take a moment to review at your convenience.