Savings Analysis

The Savings Analysis endpoint is the recommended place to go when you want to figure out how much money your residential customer can save by installing rooftop solar. answering the question, “What happens if I install a solar system with this configuration and these assumptions?”. A savings analysis can tell you how much your customer’s electricity bill will be reduced by (“avoided cost”), how expensive your solar power will be over the life of the system (PPA or lease cost), and any number of other things, depending on how you configure the calculation. We have a great tutorial that defines the end to ends steps you should follow . Read that before you continue here. But once you are familiar, this page dives into some of the details of how to get more out of your Savings Analysis call.

Running a Solar Lease or Loan Savings Analysis

Lets start with a common example of running a Savings Analysis to get our feet wet. For this one your account would already have electricity usage and a solar model. You pass in the usage profiles that you want to use to do the calculation, PPA rates, cost escalation assumptions, and other important parameters. It returns the complete results of the scenarios that you specify over the life of the project. Specifically, the a savings analysis returns a number of data series’, each of which contains your cost and savings numbers for the corresponding scenario. By default there are two series for each of the a) without solar (“before”), b) solar itself (“solar”) and c) with solar (“after”) scenarios. The first series contains the monthly results for the first year of the analysis, and the second one contains annual results for the entire analysis period.

Here’s an example of a request. It includes a solar lease, the tariff, and a solar profile.

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{
  "providerAccountId" : "example_account",
  "fromDateTime" : "2015-01-01",
  "propertyInputs" : [
  {
    "scenarios" : "after",
    "keyName" : "masterTariffId",
    "dataValue" : "518"
  },
  {
    "scenarios" : "before,after",
    "keyName" : "rateInflation",
    "dataValue" : "3.5"
  },
  {
    "scenarios" : "solar",
    "keyName" : "rateInflation",
    "dataValue" : "1.9"
  },
  {
    "scenarios" : "after,solar",
    "keyName" : "solarDegradation",
    "dataValue" : "1.5"
  },
  {
    "scenarios" : "after,solar",
    "keyName" : "providerProfileId",
    "dataValue" : "solar_profile"
  }],
  "rateInputs" : [
  {
    "scenarios" : "solar",
    "chargeType" : "FIXED_PRICE",
    "rateBands" : [
    {
      "rateAmount" : 99.99
    }]
  }]
}

Switching Tariffs After Going Solar

Set the masterTariffId property on the after scenario:

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{
    "scenarios" : "after",
    "keyName" : "masterTariffId",
    "dataValue" : "522"
}

Do a Quick Marking or Lead Generation “What-If?”

Sometimes you want to know what will happen if your system is half (or twice) the size that it is now. With the dataFactor parameter, you can do this without having to create an entirely new solar profile:

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{
    "scenarios" : "after,solar",
    "keyName" : "providerProfileId",
    "dataValue" : "{providerProfileId}",
    "dataFactor" "0.5"
}

This also works for consumption profiles.

Set A Solar Lease/PPA Price

Add an item to the rateInputs array and set its scenario to solar:

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"rateInputs" : [ {
    "scenarios" : "solar",
    "chargeType" : "FIXED_PRICE",
    "rateBands" : [ {
      "rateAmount" : 137.05
    } ]
} ]

This example would set your first-year lease rate to $137.05 per month. These inputs are structured just like TariffRates.

Extend the Duration of the Savings Analysis Projection

The default duration of a savings analysis is 20 years. For some customers, you may want to go longer – 25 years, for example. To do that, you can use the projectDuration property input parameter.

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{
    "scenarios" : "before,solar,after",
    "keyName" : "projectDuration",
    "dataValue" : "25"
}

Do An Accurate Analysis With just one Annual Consumption amount

It can often be difficult to get detailed data from a potential solar customer. Most of the time, this means that you have to do what you can with limited data. The savings analysis endpoint helps you here by giving you a simple way to do a detailed calculation if you only have one number: the customer’s annual energy consumption.

Here’s a bare-bones example:

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{
  "providerAccountId" : "api-eg-01",
  "fromDateTime" : "2014-09-01",
  "propertyInputs" : [ {
    "scenarios" : "before,after",
    "keyName" : "baselineType",
    "dataValue" : "typicalElectricity"
  }, {
    "scenarios" : "before,after",
    "keyName" : "loadSize",
    "dataValue" : "5000",
    "unit":"kWh"
  } ]
}

The two input parameters that we use are baselineType and loadSize. baselineType tells the API that you want to use our database of typicals to do your analysis. It will automatically choose an appropriate usage profile based on your account’s location and customer type. loadSize tells the API how much energy your customer is using in a year. In this case, they’re using 5,000 kWh. The typical profile is scaled up or down to meet the target load.

Further Reading

The Savings Analysis endpoint provides a lot of flexibility, which allows you to set up complex pre- and post-solar parameters when the situation calls for it. Consult the Savings Analysis documentation for details.