Virtual Battery Location Selection

Overview

The virtual battery location selection step is used to inform how many thermostatically controlled loads (TCLs) are in your system. Additionally, housing data from the selected region is used in developing first-order thermal models for exploring the operating behavior of the air conditioners (AC) and heat pumps (HP). Users select a location (county, state, census division, or census region), and GridPIQ approximates how many TCLs of each type (ACs, HPs, refrigerators, and water heaters) are in the selected location, as well as the median year of construction, which dictates the thermal properties of the construction materials, and the average square-footage for the different housing types.

To obtain TCL and housing information, GridPIQ uses two sources: the US Census Bureau’s American Community Survey (ACS) and the US Energy Information Administration’s (EIA) Residential Energy Consumption Survey (RECS). For the ACS, GridPIQ uses 5-year data (2009-2016), and for the RECS, 2015 data is used.

ACS Data
GridPIQ uses the US Census ACS to obtain the total number of housing units in a region, their year of construction, and the number of housing units in the same structure. GridPIQ uses ACS detailed tables B25127_001E through B25127_087E. You can find the table descriptions here, and you can find subject definitions here. These tables describe “tenure by year structure built by units in structure.” Tenure denotes owner/renter occupied, year structure built is typically a two decade range (e.g. “Built 1980 to 1999”), and units in structure describes the housing type (e.g. single unit detached housing or apartment in building with more than five units).

For GridPIQ’s virtual battery analysis, we aren’t concerned with whether a home is occupied by a renter or owner, so tables which describe identical housing year of construction and units in structure but have different “tenure” values are aggregated together.

Unfortunately, the ACS detailed tables provide combined figures for the following categories:

  • one unit detached and attached housing together
  • mobile homes combined with boats, RVs, vans, etc.

    • GridPIQ uses the ACS data profile tables DP04_0007E, DP04_0008E, DP04_0014E, and DP04_0015E to dis-aggregate these categories into:

  • one unit attached
  • one unit detached
  • mobile homes

    • The median age of the dis-aggregated categories (e.g. one unit detached) is assumed to be the same as the median age of the aggregated categories (e.g. one unit detached and detached). This information is used for thermal modeling of homes.

    RECS Data
    GridPIQ uses RECS data to determine “saturation rates” for each TCL type where the saturation rate is the average number of TCL per household for each housing type. To do this, GridPIQ uses RECS tables hc3.7 and hc3.8 (appliances in homes), hc6.7 and hc6.8 (space heating in homes), hc7.7 and hc7.8 (air conditioning in homes), and hc8.7 and hc8.8 (water heating in homes).

    For each census division and census region, these tables are used to compute the saturation rate for each TCL type. For example, the “West” census region has approximately 26.4 million total homes. According to EIA RECS table hc6.8, approximately 1.8 million of these homes have heat pumps. Therefore, the heat pump saturation rate for the West census region is:
    \(\frac{1.8}{26.4} = 0.068 \) heat pumps per home

    The table below shows the saturation rates for each location (census regions and divisions) and TCL type.

    Region NameRegion TypeTCL TypeSaturation Rate
    Northeastregionrefrigerator1.3
    Northeastregionheat pump for heating0.03
    Northeastregionair conditioner1.35
    Northeastregionwater heater0.31
    Midwestregionrefrigerator1.33
    Midwestregionheat pump for heating0.03
    Midwestregionair conditioner1.1
    Midwestregionwater heater0.34
    Southregionrefrigerator1.26
    Southregionheat pump for heating0.2
    Southregionair conditioner1.17
    Southregionwater heater0.67
    Westregionrefrigerator1.29
    Westregionheat pump for heating0.07
    Westregionair conditioner0.81
    Westregionwater heater0.31
    New Englanddivisionrefrigerator1.29
    New Englanddivisionheat pump for heating0.03
    New Englanddivisionair conditioner1.2
    New Englanddivisionwater heater0.36
    Middle Atlanticdivisionrefrigerator1.31
    Middle Atlanticdivisionheat pump for heating0.04
    Middle Atlanticdivisionair conditioner1.4
    Middle Atlanticdivisionwater heater0.29
    East North Centraldivisionrefrigerator1.32
    East North Centraldivisionheat pump for heating0.03
    East North Centraldivisionair conditioner1.12
    East North Centraldivisionwater heater0.32
    West North Centraldivisionrefrigerator1.36
    West North Centraldivisionheat pump for heating0.04
    West North Centraldivisionair conditioner1.01
    West North Centraldivisionwater heater0.39
    South Atlanticdivisionrefrigerator1.26
    South Atlanticdivisionheat pump for heating0.26
    South Atlanticdivisionair conditioner1.15
    South Atlanticdivisionwater heater0.73
    East South Centraldivisionrefrigerator1.24
    East South Centraldivisionheat pump for heating0.21
    East South Centraldivisionair conditioner1.21
    East South Centraldivisionwater heater0.71
    West South Centraldivisionrefrigerator1.27
    West South Centraldivisionheat pump for heating0.09
    West South Centraldivisionair conditioner1.19
    West South Centraldivisionwater heater0.54
    Mountaindivisionrefrigerator1.31
    Mountaindivisionheat pump for heating0.09
    Mountaindivisionair conditioner0.82
    Mountaindivisionwater heater0.33
    Pacificdivisionrefrigerator1.28
    Pacificdivisionheat pump for heating0.06
    Pacificdivisionair conditioner0.79
    Pacificdivisionwater heater0.31

    Combining Information from ACS and RECS
    From the ACS data, we have the number of housing units by location, and from the RECS data, we have saturation rates for each TCL by census region and division. In order to obtain an estimate for the number of TCLs by type and region, the number of housing units is multiplied by the corresponding saturation rate. GridPIQ always uses the most granular region type possible (e.g. census region, division, state or county) in determining the saturation rate.