Energy Modeling

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What is It?

Energy modeling is an effective, low-cost way of predicting building energy use using computer software. Energy modeling software programs have the capability of simulating building energy performance using hourly climatic data (e.g. temperature, relative humidity, cloud cover, solar gain, etc.) for the specific location of the building. This type of modeling is best done very early in the design process to evaluate the energy performance of different materials, construction types, and HVAC equipment. This allows an owner to evaluate the sustainability and life-cycle cost effectiveness of these options before investing in them. Energy performance is dependent on building components such as:

  • building orientation
  • glazing percentages (window-to-wall ratio)
  • insulation of walls, roofs and floors
  • the efficiency of the HVAC equipment, and
  • functional uses of the building.

Computer simulation tools help predict and form decisions such as these while allowing the design team to learn more about how the building will react to the natural elements.

Also known as: energy simulation, building energy use simulation.

Why is it Important?

  • Strengthens our relationship to the earth. The simulation helps us learn how the natural climatic systems (sun, wind, clouds rain, night/day, etc) affect the building.
  • Shows us how to minimize our environmental impact by reducing energy use and its associated fossil fuel consumption, carbon and pollution issues.
  • Produces financial savings by reducing energy costs, as well as making sure our investments are resulting in the most sustainable solution possible.
  • It's accessible to all. There is very good energy modeling software is available for free to individuals and communities to predict and reduce their energy use.

When to Use It?

  • Energy modeling is typically used during two critical times in the design of a building:
  1. Conceptual design - to analyze the benefits of alternative options for reducing energy demands (e.g. more insulation, higher thermal windows, different HVAC systems etc.)
  2. Technical design - to size for the different HVAC components required for engineering design and procurement.

Things to remember:

  • Best used as early as possible in the design process. This is because the building envelope (walls, windows, roof, and floor) has the most impact on the building's energy use, and is typically hard to change later on.
  • Because building energy use is affected by many interdependent variables, some of which cannot be modeled completely, use the tool as a relative guide to see how changing one component or system affect the building performance. In this way the tool can create an unending set of learning opportunities for the team to really understand how the building behaves.
  • The tool is a good predictor of the overall performance of the building, but has limitations as a precise predictor of energy use and costs of specific components.
  • The energy modeling tools that we used are not able to simulate many of our designs and strategies. We used closest approximations where possible.

Green Garage Example

Sustainability Goals

  • Provide support for a net zero energy design plan (achieve at least a 70% reduction in building energy use with passive design strategies.)
  • Quickly show how each building energy design decisions are related to each other and to everything around the building.

Strategy and Conceptual Design

Green Garage Energy Modeling Tools

During the conceptual and design phases of the project we used three modeling tools:

  • WUFI
    • Predicts temperature, dew point and humidity transfer through wall and roof systems.
    • Incorporates Detroit weather and climate data.
    • Verifies R-Values calculated by hand and by Energy-10.
  • Energy-10
    • Provides a simple, fast, and low-cost method of predicting energy use for the entire building.
    • Incorporates Detroit weather and climate data.
    • Always compares your current building design to a "low-energy" building design provided by the Energy-10 authors as a benchmark for a high efficiency building.
    • Organizes output in graphical form that non-technical people can understand and relate to
    • Has a feature called "DVIEW" that looks at hourly data by variables(heat loss, heat gain, outdoor temperature, etc.) This data can be exported into other applications such as Microsoft Excel and shared.
    • Can be used during the entire process to predict and then verify and refine energy performance

  • eQuest
    • Provides same type of modeling and simulation tools as Energy-10, but with more detailed inputs.
    • Energy-10 was not able to model many of our systems, we are hoping that eQuest can do a bit more with the unconventional strategies.
    • eQuest has more funding and research being directed toward it, so there is probably more support.
    • eQuest is free, so we can have as many people downloading the software and sharing files as we need or want.
    • As long as we are able to get meaningful results, we will be able to use eQuest throughout the commissioning process.
    • We should be able to use eQuest to model client/community projects to help others save energy.
    • It is relatively easy to use (compared to DOE2).
    • Lots of online support and documentation.
    • Used in industries that have a need to do energy modeling.
    • eQuest can model something other than a shoebox design, so may be more universal.

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Model Inputs

  • Here are our key design assumptions of for modeling the Green Garage in eQuest and Energy-10: Green Garage - Current Design Assumptions
  • We used three different versions of the model for the Green Garage.

Version 1.0 results
x1,000,000,000 Btu
Software Energy-10 V.1 eQuest V.1 Comments
* Heating
*Possible differences in weather data and HVAC systems
* Cooling
* Lights
May account for lighting for functions differently
* Other
May be related to fan use in E10
* Total

    • Version 2.0: New envelope with super-insulated walls and roof and insulated windows.
      • One of the first things we learned from Energy-10 was the choice of HVAC equipment affects heating and cooling loads. This is because some HVAC systems bring in outside air, which most of the time is colder or warmer than the desired temperature of the indoor air . It takes energy to change the supply air to the right temperature.
      • We found we could look at what the building envelope would do without any HVAC equipment by "enabling free run mode" in the simulation. With our building envelope conditions and no equipment, the temperature would approach freezing only during the coldest days.
      • We discovered that insulating the envelope and choosing commonly available efficient windows would make a very large difference in annual energy use.
      • Assuming all double-pane, low-e windows -- we found that reducing the window U-value did not result in a significant energy savings to balance the cost of a very low U-value window.
      • We went through several iterations at this stage so that we could look at one system or component at a time. See Energy-10 Versions page for details.
      • Because we chose a relatively low solar heat gain co-efficient to begin with, most of our internal gains will result from lighting, equipment, and people.
    • Version 2.5: New envelope with super-insulated walls and roof and insulated windows, conventional HVAC, and daylighting.

Version 2.5 results
x1,000,000,000 Btu
Software Energy-10 V.2.5 eQuest V.2.5 Comments
* Heating
* Cooling
* Lights
Not sure if eQuest is applying daylighting correctly
* Other
* Total

    • Version 3.0: Best fit HVAC system, solar hot water, daylighting, and photovoltaics applied.
      • Energy-10's low-energy case, annual energy use results for each of the three versions are fairly static.
      • Our forecast annual energy use is a 90% reduction in version 3.0 compared to version 1.0 (goal was 70%), and is actually LOWER than Energy-10's low energy case.

Version 3.0 results
x1,000,000,000 Btu
Software Energy-10 V.3 eQuest V.3 Comments
* Heating
* Cooling
* Lights
* Other
* Total

The most recent load estimates for heating and cooling:

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How the models compare to our heating and cooling strategies:

Only partially able to model the geo-solar hybrid
Not able to model this in either Energy-10 or eQuest
Not able to model this in either Energy-10 or eQuest
Modeled as Fixed COP of 5 Heat Pump, Fixed COP DX Compressor EER 30 in Energy-10
Modeled as Fixed COP of 5 Ground Source Heat Pump, Fixed COP DX Compressor EER 30 in eQuest
Not able to model this in Energy-10, did not model as radiant in eQuest
Modeled as Solar DHW in Energy-10, did not model DHW in eQuest
Ventilation modeled in both Energy-10 and eQuest as ONLY the minimum 800 cfm based on occupancy type per code.
Modeled all components in both, except for the white roof is not an input option in Energy-10
Fully modeled in Energy-10, still under investigation in eQuest
Setpoints on thermostats in both models for within temperature range, neither model contains humidity inputs

eQuest Learning Process:

  • Analysis objectives
Begin with the end in mind…
    • Structure the versions the same way as we did for Energy-10 (Versions 1.0, 2.0, 3.0)
    • Compare Energy-10 results to eQuest, examine large differences.
    • Get the heating and cooling loads for the new super insulated envelope
    • Gather load inputs and systems that deal with them
    • Get at least an idea of internal loads and how they affect energy use as reported by eQuest
    • Calculate electrical loads
    • Verify, by “sanity” checks, where results don’t make sense.
  • Limits of energy modeling:
    • We were not able to model many components of the geo-solar hybrid heating system we will be using.
      • Energy-10: Entered a best fit fixed COP heat pump and DX compressor to approximate the geo-solar system we will actually use.
      • eQuest: We were able to input a closer fit geothermal system, but not the mass thermal storage or radiant floor.
    • We were not able to model our natural ventilation, earth tubes, and some of our cooling strategies in eQuest or Energy-10.

eQuest Modeling Process Checklist:

Building site info and weather data

Got it in the model

Building shell, structure, materials, shades

Got it but have some questions

Building operations and scheduling

Got it but have some questions

Internal loads

This is harder than it looks, but I suggest we just go with “typical day” for GG for now.

I tried the LBNL link and the most recent data and articles were from 1997!! ASHRAE would of course be more current.


eQuest uses a different values for perimeter and core zones, which makes sense since you will have more infiltration through exterior walls than you will in the middle of the building. An ASHRAE value for a loose construction with an outdoor design temperature of 10F is 1.27 ACH (air changes per hour) so that's what I used for the perimeter. eQuest defaults to a 0.001 ACH for the core zone so I left that alone.

HVAC equipment and performance

Don't know how to simulate this yet

Utility rates

Worry about this later on

Economic parameters

Worry about this later on

Questions for the experts and learning community:

What is the closest HVAC system choice in eQuest?

How should we account for/input internal load info?

Where do we tell eQuest how many people are in the building?

How does eQuest figure stud spacings/percent?

Here's what the Input Screens look like:

State of the model and observations

  • Zoning is applied to both daylighting and HVAC. I kept the default 15 ft perimeter zones and added one core zone encompassing the interiors of both the historic and annex sides.
  • Conversion for kWh to Btu is 1:3413.
  • We don't know how weather data compares between Energy-10 and eQuest. What is the source and year for each?
  • Must input the building as flat roof and "fake" the ceiling heights to get the right volume because we cannot model the skylights on anything other than a flat roof. Don't know if this is a glitch or if there's a good reason why. Roof and floor tools in general are clunky.
  • Energy-10 shows a fairly heavy fan load in Version 1.0 in winter. Not sure how to adjust or if I should.
  • Setting the set points identical to setbacks avoids the energy spiking problem but does it increase total energy use?
  • We need to also look at life-cycle costs when making decisions on the HVAC system, not just energy use.

  • Supporting science:
    • US National Renewable Energy Lab (NREL) weather data is embedded within Energy-10.
    • eQuest has built in weather data, including that for Michigan and Detroit.

Proposed Materials / Suppliers

Development Story

The Energy Modeling - Development Story page contains many images and videos documenting the process used at the Green Garage to use energy modeling.

Related Internal Links


Open Points

  • What did we learn from WUFI? ...moisture build up? Tom, what was the wall design BEFORE?? (complete this thought)
  • edited by Ashleigh