WattTime

WattTime is a provider of electricity grid-related data, to assist with identifying emissions reductions. Through the WattTime Connector, you can materialize the following points in your graph:

• Index
  • MOER
• Historical
  • MOER
  • AOER
  • Health Damages
• Forecast
  • MOER
  • Health Damages

Use Cases

Potential use cases include:

• Comparing projected energy usage against baselines
• Identifying cycles to optimize energy usage schedules

Configuration

The authorization for the WattTime Connector utilizes the WattTime API username and password:

Credential	Description
Username	The username registered with the WattTime API
Password	The password registered with the WattTime API

When you save the configuration, the connector looks up the WattTime grid region that serves each mapped building and which signals your account can access there. It remembers these results rather than asking WattTime on every update: regions are re-checked weekly, and buildings outside WattTime's coverage and your account's signal access are re-checked daily. Saving the configuration re-checks everything immediately, so save it again after WattTime changes your plan or coverage.

This connector allows you to select which of the points you wish to materialize in your graph when you are first configuring the connector. The connector runs on the following intervals:

• Historical Points: Every 5 minutes. Each poll picks up everything WattTime has published since the last value imported for that point, so signals WattTime publishes late (average emissions can arrive 12-15 hours behind) are still captured. After an interruption, the connector catches up on at most the previous 7 days (168 hours). A newly enabled point starts with the most recent 24 hours of available data
• Index Points: Every 15 minutes
• Forecast Points: Every 1 day, with a horizon of 24 hours { //Forecast Timeseries Payload "forecast": [ //"data" in the forecast response { "point_time": "2024-02-27T16:40:00+00:00", "value": 208.6 }, { "point_time": "2024-02-27T16:45:00+00:00", "value": 208.6 }, { "point_time": "2024-02-27T16:50:00+00:00", "value": 191.4 } //And so on ], "period": 300, // meta.data_point_period_seconds "generatedAt": "2024-02-27T16:40:00+00:00", //meta.generated_at "forecastHorizonHours": 24 //from the request configuration }

Mapped Concepts

Connector Concept	Mapped Type
Electrical Grid	Electrical_Grid_Region
HIistorical	Average_GHG_Emissions_Rate, Electricity_GHG_Emissions_Health_Damage, Marginal_GHG_Emissions_Rate
Index	Marginal_Operating_Emissions_Rate_Index

Sample Code

This connector is tied to an electrical grid, as opposed to a specific building, so you have to go a slightly different route to retrieve the data from the building level. The building will be a part of the grid, so we'll use isPartOf to get to the grid level, then filter to the specific grid using the place ID. We'll then find the points associated with the grid to get the various electrical data. Historical and index points hold a number, returned in float64Value; forecast points hold the whole forecast as a JSON object, returned in json (the forecast arrays below are shortened to their first three entries):

{
  buildings(filter: {id: {eq: "BLDG81uBVj9UZ1XmSgtyKxABCD"}}) {
    id
    name
    isPartOf(filter: {id: {eq: "PLCFABybzfaoZgpa6KwML1234"}}) {
      id
      name
      exactType
      hasPoint {
        id
        name
        series(latest: true) {
          value {
            float64Value
            json
          }
          timestamp
        }
      }
    }
  }
}