Using ComStock to Analyze Cost

In addition to providing information on energy use in the U.S. commercial building stock, ComStock™ can also support assessment of energy-related costs if combined with external data sets. This document discusses how ComStock data can be combined with external cost data. We discuss two different classes of costs:

1) Utility cost – This is the cost of purchasing heat, fuel, and/or electricity in the commercial building stock, either for the present day or with various energy efficiency or electrification upgrade technologies.

2) Upgrade cost – This is the cost of installing an upgrade, including both the purchase of equipment and materials and the labor costs for installing the upgrade.

About Utility Cost Assessment

There are several nuances in calculating utility cost. Utility rates vary nationwide, and even within a single utility service territory, there might be several available commercial rates. Furthermore, for assessments that aim to examine energy costs into the future, custom assessments might be desirable. ComStock does not currently include utility costs in data releases, but they are expected to be included for the first time in the March 2024 data release. For the forthcoming release, national-scale utility cost data will be drawn from the Utility Rate Database. This provides a snapshot of utility costs under present day utility rates, with variation by location and utility. Detailed documentation on that assessment will be included with the data set release.

For users desiring a custom cost assessment, ComStock provides both annual and time-series energy consumption by fuel, location, and building type. When matched with a utility rate, this energy consumption can be converted to energy cost. As a simple example, if electricity costs are $0.14 per kWh, the total annual cost of electricity in a building or group of buildings could be found by multiplying the annual sum of the total electricity in a building (variable by $0.14. For an assessment looking at the costs before and after an upgrade, this base cost could be compared to the energy costs after the upgrade with the same variable; the change in cost can be calculated by using the ComStock output variable on energy savings ( Furthermore, because energy consumption and energy savings are both output by ComStock as time series, more complicated tariff structures could also be applied, such as demand charges or time-of-use rates. A full list of the basic energy output variables is given below.

  Total Energy Energy Savings (by upgrade)
Electricity (kWh)
Natural Gas (kWh)
Other Fuels (kWh)
District Heating (kWh)
District Cooling (kWh)

Note: These energy outputs are all given in kWh for ease of adding up total energy use, but kWh is unlikely to be the default unit for fuel costs outside electricity.

In addition to these variables, which give total energy consumption and savings by fuel, ComStock also provides end-use level consumption and savings if more detailed cost assessment is desired (e.g., HVAC-related energy costs). For a full list of ComStock output variables, reference the “data_dictionary.tsv” file for the relevant release on the Open Energy Data Initiative.

About Upgrade Cost Assessment

The cost of installing energy-related upgrades is important for a wide range of stakeholders in selecting and designing building retrofits, but ComStock does not currently provide this information. Understanding how much an upgrade will cost is dependent on several factors including local labor costs, workforce capabilities, equipment and material costs, seasonal factors, and supply chain constraints, all of which vary over time depending on other economic factors. For this reason, upgrade costs vary greatly by location and time.

In this documentation, we provide information on how ComStock output variables could be matched with local data on upgrade costs to perform a stock-level assessment of upgrade costs. Different types of upgrades will have different cost considerations. Throughout the discussion, we assign “confidence” levels to each of the variables. See the table below for the confidence levels and their definitions. Furthermore, we highlight variables that are commonly used in cost assessment, but are missing from the ComStock output, with a “Not Output” tag. These confidence levels will be updated as additional improvements are added to ComStock.

Output Variable Confidence Level Definitions

Confidence Level Definition
High Output variable offers an appropriate approximation of the real commercial building stock and could be used directly in costing.
Moderate Output variable could be used in costing, depending on the use case. Generally suitable for back-of-the-envelope calculations but may be off by a factor of 2–10.
Low There might be significant discrepancies between ComStock and real commercial building stock characteristics, and the variable should be used with caution. Results could be off by a factor of 10.
Not Output Variable could be used in a cost assessment but is not currently a ComStock output.

For a full list of ComStock output variables, reference the “data_dictionary.tsv” file for the relevant release on the Open Energy Data Initiative. For complete details about how ComStock models the following systems, see the ComStock Reference Documentation.

1. Windows and Opaque Envelope - Caveats and Considerations

The most relevant variables for envelope upgrade costs—the surface areas of the windows, exterior walls, and roof—are listed in the table below.

  Variable Name Units Confidence Level
Roof Area out.params.ext_roof_area m2 High
Window Area out.params.ext_window_area m2 Moderate
Exterior Wall Area out.params.ext_wall_area m2 Moderate
Window Count N/A # Not Output

In the most simplistic application of these variables, the total area of each component could be multiplied by the unit material cost of the upgrade, adding in the labor associated with installation. However, there are a few considerations for using these variables for cost analysis based on how ComStock calculates geometry. ComStock does not use real building geometry such as that found in lidar or building footprint databases; instead, it uses the bar method to estimate building geometry. A key limitation of this approach is that underestimates exterior surface area, which impacts both window area and exterior opaque envelope. If these ComStock variables are used for a cost analysis, the user should be aware that they are likely underestimates for the real amounts of building surface area that would need to be upgraded. Furthermore, ComStock does not provide a count of windows upgraded in a building, which is impactful for window upgrade cost.

A few other ComStock variables, shown below, might aid in envelope upgrade cost calculation, depending on the cost data available or supplemental methods for determining retrofit material volume.

  Variable Name Variable Description Confidence Level
Floor area in.sqft Building total floor area (ft2) High
Original energy code in.energy_code_followed_during_original_building_construction Energy code used during initial construction Moderate
Building system energy code in.energy_code_followed_last_*_replacement Energy code used for most recent building system replacement Moderate
Floors in.number_of_stories Above-grade stories Moderate
Total floors in.number_stories Total floors (including below-grade) Moderate
Wall type in.wall_construction_type Type of construction (e.g., steel, wood) Moderate
Building aspect ratio in.aspect_ratio Ratio of North/South facade length relative to East/West facade length Moderate

* Building system, such as walls, roof, lighting, and interior equipment.

2. Heating, Ventilating, and Air Conditioning (HVAC) - Caveats and Considerations

The ComStock calibration process utilizes energy use as the metric of performance, not necessarily equipment counts. For costing, this is relevant to many equipment categories, but especially HVAC. In ComStock, the total building heating or cooling equipment capacity is reasonably estimated, so cost methodologies should focus on backing out the number of units from the total capacity based on floor area, not using equipment counts directly. For some HVAC categories, ComStock does provide equipment counts and approximate size estimates of different equipment (e.g., 5-ton chiller), but these should be used cautiously. As a byproduct of the model creation process, the various heating and cooling zones created in the models could be substantially bigger or smaller than a typical zone that would be found in reality, leading to oversizing or undersizing of HVAC equipment.   In the table below, the most significant HVAC variables are highlighted.

  Variable Name Units Confidence Level
HVAC system energy code in.energy_code_followed_during_last_hvac_replacement Energy code used for most recent HVAC replacement Moderate
Total HVAC capacity in building by equipment type (e.g., chiller, boiler, heat pump, water-air heat pump, VRF) out.params.chiller_capacity tons High
  out.params.boiler_capacity kBTU/hr High
  out.params.furnace_capacity kBTU/hr High
  out.params.heat_pump_cooling_capacity kBTU/hr High
  out.params.heat_pump_heating_capacity kBTU/hr High
  out.params.wa_hp_cooling_capacity W Moderate
  out.params.wa_hp_heating_capacity W Moderate
  out.params.vrf_total_indoor_unit__cooling_capacity W Moderate
  out.params.vrf_total_indoor_unit__heating_capacity W Moderate
  out.params.vrf_total_outdoor_unit__cooling_capacity W Moderate
  out.params.vrf_total_outdoor_unit__heating_capacity W Moderate
Total building cooling capacity out.params.cooling_equipment_capacity tons Moderate
Total building heating capacity out.params.heating_equipment kBTU/hr Moderate
HVAC count variables x size (e.g., 10 5-ton units) out.params.hvac_count_boilers__** # Low
  out.params.hvac_count_chillers__** # Low
  out.params.hvac_count_dx_cooling__** # Low
  out.params.hvac_count_dx_heating__** # Low
  out.params.hvac_count_furnace__** # Low
  out.params.hvac_count_heat_pumps_cooling # Low
  out.params.hvac_count_heat_pumps_heating # Low
  out.params.vrf_indoor_unit_count # Low
  out.params.vrf_outdoor_unit_count # Low
Fan, pump, motor sizing for whole building equipment N/A   Not Output
Fan, pump, motor sizing for zonal equipment N/A   Not Output
Duct run lengths N/A   Not Output

** Multiple variables with similar names. For example, out.params.hvac_count_furnace__** represents all of the different size bin counts in the output, such as out.params.hvac_count_furnace_0_to_30_kbtuh and out.params.hvac_count_furnace_65_to_135_kbtuh.

3. Lighting - Caveats and Considerations

Similar to HVAC, ComStock provides estimates of capacity, in this case interior lighting power density, with high confidence, but the number of individual lighting fixtures is not provided in the output. Interior lighting costing methodologies could focus on backing out the number of fixtures desired for the upgrade based on the lighting power density and the building floor area, which is also output with high confidence from ComStock. ComStock also provides the peak power used in exterior lighting with moderate confidence. This is not a typical variable used in costing, but could perhaps be coupled with other information from ComStock such as building size and/or type to provide an approximation of the cost of upgrading these fixtures.

  Variable Name Units Confidence Level
Whole building interior lighting power density out.params.interior_lighting_power_density W/ft2 High
Peak exterior lighting electricity usage out.params.exterior_lighting_power W Moderate
Lighting fixture counts N/A # Not Output
Exterior lighting fixture counts N/A # Not Output

4. Designated Water Heating - Caveats and Considerations

For buildings that have separate water heating systems outside of co-generation with the HVAC system, data are provided on the total heating capacity volume with low confidence. Data on the counts of equipment, either given as total counts or counts by capacity size range, are provided in ComStock outputs with low confidence. In most ComStock models, a single water heater is used to meet the demands of the entire building. Some models use a booster water loop, in which case a separate water heater system will be modeled for the boost loop. Booster loops are included for buildings with kitchen space types, such as restaurants and schools.

  Variable Name Units Confidence Level
Service water heating energy code in.energy_code_followed_during_last_svc_water_htg_replacement Energy code used for most recent water heating replacement Moderate
Total water heating storage capacity out.params.hp_water_heater_total_volume gal Low
  out.params.non_hp_water_heater_total_volume gal Low
Total water heating capacity out.params.hp_water_heater_capacity W Low
Water heating equipment capacity by size range out.params.hp_water_heater__*__gal_total_volume gal Low
  out.params.non_hp_water_heater__*__gal_total_volume gal Low
Water heating equipment count out.params.hp_water_heater _count # Low
Whole service water heating equipment size out.params.hp_water_heater__*__gal__count # Low
Piping lengths N/A ft Not Output

5. Other Equipment - Caveats and Considerations

ComStock provides equipment counts for some kitchen equipment listed below. In general, these could be used as orders of magnitude bounding for costing, but the overall confidence in using these variables is low. Potential methodologies for costing these components could focus on supplementing the floor area renovated with this equipment with external data on the average size of kitchen spaces and the counts of equipment typically present in these spaces.

  Variable Name Units Confidence Level
Equipment counts out.params.num_broilers # Low
  out.params.num_fryers # Low
  out.params.num_griddles # Low
  out.params.num_ovens # Low
  out.params.num_ranges # Low
  out.params.num_steamers # Low

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