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This article was originally published in the September/October 1997 issue of Home Energy Magazine. Some formatting inconsistencies may be evident in older archive content.

 

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Home Energy Magazine Online September/October 1997


Energy-10


by Rick Clyne and Steven Bodzin

Rick Clyne is a freelance technical writer living in Denver, Colorado. Steven Bodzin is Home Energy's associate editor.


There are many software packages available to evaluate residential energy conservation measures. Energy-10 is among the new generation of easy-to-use programs that have been helping architects and engineers evaluate the details of building energy use at every step in the design process.
Energy-10 provides the user with a variety of graphic displays to help quickly analyze alternative designs.

In the past two decades, many energy analysis software packages have appeared on the market. Most of these have been time-consuming, complicated to use, or unable to handle a sufficient number of variables. Consequently, these packages have seen little use in the design field. Their applications have been mostly limited to the latter stages of the design process, when design details are being finalized and modifications are increasingly expensive to incorporate.

Recent improvements in energy analysis software have brought about significant increases in their speed and comprehensiveness, while also making them much more user friendly. Energy-10 is one such new software package developed by the National Renewable Energy Laboratory.

Developed as a simulation-based design tool for architects and designers, Energy-10 has a fairly good track record in the world of small commercial construction. Although it can also handle residential buildings, it has not yet seen widespread use in that sector. Doug Balcomb, the leader of the Energy-10 design team based at the National Renewable Energy Laboratory (NREL) in Golden, Colorado, says, there are few restrictions. [The system] is fully capable of dealing with the issues that are important in residential applications.

Energy-10 helps designers assess how a building will use energy and identify which energy-efficient strategies are the most effective. It simulates a year of building energy use to determine heating and cooling loads, and ranks the most cost-effective efficiency improvements. With Energy-10, energy analyses can be accomplished in just half a day at the beginning of the design process. Before the first elevation is sketched, a designer using Energy-10 can simulate many of the energy performance characteristics of the building and determine how to maximize energy efficiency.

Energy-10 gets its name from its ability to analyze buildings with up to 10,000 ft2 of floor area. Seventy percent of the commercial structures built today are under 10,000 ft2, and they consume 25% of the total energy used in the commercial building sector. Energy-10 was specifically developed to analyze these small, commercial building designs.

Quick Analysis In the earliest stages of the design process, Energy-10 requires only five preliminary design descriptors. The program uses these descriptors to create a simple shoebox version of the building. Using the shoebox, users can begin running simulations to evaluate energy performance.

Balcomb says he wanted to make the program quick and easy to use. In the design process, time is essential. Say a designer has an idea, and they sketch it out. They need to know the energy implications of that design idea right away--in ten minutes, not ten days. Our goal was to compress all of the energy analysis, which includes dozens of calculations, into an afternoon's worth of time. It has to happen that quickly if it is going to be done at all.

After the shoebox analysis, the simulation evolves with the building design. From the predesign to the final building plan, the user can set or modify hundreds of building descriptors, allowing the simulated building to reflect the growing level of detail. In this way, the user can gain an in-depth understanding of how each change in the design affects energy use.

The program evaluates building energy use through a year of simulated performance in one-hour increments, relying on detailed weather data for all climatic regions in the United States. The simulation speed depends heavily on the computer being used. The program is available only for a PC Windows-based operating system, and the minimum hardware requirements are a 66-MHz 486 processor with 16 megabytes of RAM. Simulations run on this configuration take about 12 minutes. As usual, bigger is better--simulations run on a 200-megahertz Pentium Pro take only 18 seconds.

Energy-10 can evaluate the effect of a specific energy efficiency strategy or a set of strategies on the building's overall efficiency. Version 1.2, the current release, can evaluate a wide range of components, including insulation, passive solar heating, air leakage control, shading, high-efficiency HVAC, energy-efficient lighting, glazings, thermal mass, daylighting, economizer cycles, and HVAC controls.

The user selects one or more strategies and uses the program's Apply function to modify the design with those strategies. As part of this process, the user can specify strategy characteristics. For example, before selecting the insulation strategy, the user can define the R-values for the walls, ceiling, perimeter, and doors. Within a few minutes, Energy-10 simulates a year of energy use in the house. It then displays graphics that quantify the effect of the selected strategy on energy use.

Heat and Light--Finding the Balance One key to a comfortable, energy-efficient building is balance among heating, cooling, and lighting systems. Finding this balance for a specific design in a specific location accounts for much of the complexity in the design process. For example, a house that has overdesigned passive solar features may save on heating bills, but may not be particularly comfortable, even in winter. Also, the characteristics of a well-balanced, energy-efficient home designed for New Orleans will differ considerably from those in Salt Lake City.

To balance these systems properly for a given climate, Energy-10 has a weather database containing a full year of hourly meteorological data for 239 locations in the United States. These data are used in conjunction with the program's thermal and lighting simulation engines. The software uses the California Nonresidential Engine (CNE), which calculates a multizone, thermal network solution that lets Energy-10 simulate two HVAC zones. When the user runs a simulation, Energy-10 transfers the building description to the CNE, where it is transformed into a thermal network model. The CNE iterates to find a consistent solution to the loads and systems calculations, using 15-minute time steps (for numerical accuracy); finding an energy balance at every step; and taking into account heat storage in each material layer. This energy balance is crucial, especially for the highly interactive energy efficiency strategies used in a balanced passive-solar design. CNE reports results hourly, monthly, or annually.

The daylighting simulation engine was written at the Lawrence Berkeley National Laboratory and incorporates the split-flux routine used in the DOE-2 computer program. During a simulation, the analysis routine first calculates daylighting illuminance at a control sensor location for each of 20 sun angles for each aperture. Illuminance values are then calculated for each lighting zone. For buildings wider than 30 ft, Energy-10 creates five lighting zones within each thermal zone.

Energy-10 integrates the hour-by-hour daylighting calculations into the thermal analyses run by the CNE, accounting for the heating effects of both natural and artificial lighting.

Figure 1. The input screen for the basic building descriptors: our Salt Lake City home is a one-story, 2,700-square-foot structure that has central air conditioning and a gas furnace.
Establishing Performance Goals with AutoBuild Let's say we are designing a 2,700 ft2 home in Salt Lake City. The initial input screen requests the five basic building descriptors--geographic location, building function, HVAC system, floor area, and number of stories (see Figure 1). With the basic information, the program's AutoBuild feature creates two simple shoebox buildings in the computer. One is a reference case that uses standard construction and incorporates few, if any, energy-efficient strategies. The other is a low-energy version of the same building that incorporates a range of energy-efficient features and construction techniques. Although these simplified shoebox buildings bear little stylistic resemblance to the actual building, they provide a representative initial picture of how the design will use energy.

When building descriptors are not initially specified by the user, the software defaults to user-definable standard construction practices based on the specified building use. For example, in our Salt Lake home, we specified residential as the building use, 2,700 ft2 as the floor area, a conventional heating and cooling system, and one-story construction. The program defaulted to standard 2 x 4 external wall framing, R-19 ceiling insulation, uninsulated foundation walls, and 12% of the floor area in wall glazing. If standard construction in the designer's area is different, the defaults can be changed. As the design evolves, the user can replace these and other default values with actual values and specifications. The defaults simplify initial input requirements to produce energy use comparisons quickly. The default reference case reflects widespread building practice, rather than best practice. For example, the default case has supply and return ducts in the attic, resulting in combined conduction and air loss leakage of 18%. After defining the reference case description, the program defines an alternative low-energy case using another set of defaults for the strategies selected and simulates both buildings.

The lack of initial detail might seem like a fatal problem, but Balcomb maintains that the simulations are accurate. Many people believe that the detail of the building layout is the vital factor influencing energy use, he says. In reality, it is not vital to many energy-efficient strategies. User experience has shown the energy performance of the shoebox version is quite similar to that of the detailed building layout that eventually takes shape. However, for some strategies, such as shading, window placement, and daylighting, design detail does affect performance, and so the user should adjust the building description in the computer to more and more accurately characterize the actual building as the design evolves.

Once the reference case and low-energy buildings are created, the software runs a climate-specific simulation of energy use for each hour of the year. It then prints out side-by-side comparisons of how both structures use energy. It is possible to change assumptions about either the reference case or the low-energy case. By specifying almost identical buildings, the user can simulate the incremental savings from one or a few design changes.

Figure 2. Energy-10 can automatically rank individual energy improvements by their potential energy savings. These bars represent possible savings for the Salt Lake home. Note that these savings are not additive-the ranking considers each improvement individually, but in reality some strategies will affect the savings from others.
Entering the initial data and running this simulation takes 10 to 15 minutes. The output produced by this simulation for the Salt Lake City house is shown in Figure 2. Note how energy performance changes dramatically when nine energy efficiency strategies are applied to the design, as reflected in the performance of the low-energy case. Daylighting with dimmers and an economizer cycle were not applied because these are not typically used in residential applications.

This initial analysis gives the designer a realistic set of energy performance targets to shoot for as the design process moves forward. If the right mix of energy-efficient strategies is incorporated, the performance of the actual building should approach the performance of the low-energy AutoBuild simulation. Unfortunately, there are few controlled comparisons to validate how close the simulation comes to reality. The most comprehensive test for simulations is BESTEST, which has been approved by the U.S. Department of Energy and is being used by home energy rating systems. It compares various simulation programs to ensure that they are consistent with one another. There is no comprehensive test suite based on measured data, partly because of the inherent variability introduced by occupants (see Home Energy Rating Systems: Actual Usage May Vary).

As the user provides more detail, the computer keeps two simulated buildings in memory at all times to facilitate comparisons. Originally, these are the reference case building and the low-energy case building. Thus as the user updates the building description he or she has an accurate, up-to-date indication of the combined effect of design improvements. It is also possible to examine the effect of a single change by changing only one feature, such as wall insulation, in one of the buildings.

Ranking Energy-Efficient Strategies One of Energy-10's most powerful features is its ability to estimate which measures will result in the lowest operating costs. (This is not yet an evaluation based on life cycle costs. A life cycle cost analysis would require estimating first costs, a feature not available in the current version of Energy-10.) A user who knows how much a measure will cost to install can use the simulation's estimate of operating cost savings to evaluate cost-effectiveness. Assumptions about thermostat setpoints and other occupant variables are easy to change within the program, providing a customized estimate of operating cost savings.

Early on in the design process--shortly after the initial AutoBuild comparison is run--the user can select the Rank function. This function identifies which energy-efficient strategies have the greatest effect on reducing energy use. The user can then ensure that the most effective strategies are incorporated into the building design.

When the Rank function is run, Energy-10 applies a single strategy to the reference building, puts it through a year of simulated performance, and saves the results. It then removes that strategy, applies the next strategy, and reruns the simulation. This automated process continues until simulations have been run on all desired strategies. The user can specify the ranking criterion used to compare the strategies, such as lowest annual energy use or lowest annual operating cost.

Figure 3. The program automatically analyzes the difference between a reference case and a low-energy case, and provides this graph showing differences in energy use. For the building shown in Figure 1, the improvements for the low-energy case include bringing ductwork from the attic into the conditioned envelope, improving furnace efficiency from 80% to 90%, and increasing cooling EER from 8.9 to 13. The improved walls are 2 inch x 6 inch with 1-inch foam sheathing (R-23.1) instead of 2 inch x 4 inch (R-12.6); the ceiling is R-38 instead of R-19; and the foundation perimeter is insulated with 2-inch foam. Effective leakage area is reduced from 254 in2 to 97 in2. Glazing is changed from double (U-0.49) to double low-e (U-0.26), and frames are changed from aluminum to wood. According to the Energy-10 simulation, these energy efficiency measures would reduce total energy use from 256 million Btu to 79 million Btu annually, which would reduce annual energy costs from $3,470 to $1,564 at 11¢/kWh electricity and 80¢/therm for heat.
Figure 2 shows an example of output from the Rank function for the Salt Lake home. In this example, the strategies were ranked by annual energy cost savings. Clearly, the designer hoping to maximize energy efficiency would want to integrate improved insulation, high-efficiency equipment, air leakage control, and improved windows into the building design. With these four strategies integrated into the basic design, the simulation is rerun. The results are quite similar to those in Figure 3--total annual energy use is 84 million Btu and annual utility cost is $1,704.

The reduced heating and cooling loads also make it possible to scale down the home's mechanical systems. The heating system in the improved home requires only 29,000 Btu/h output, rather than the 97,000 Btu/h before scaling down; the cooling system is reduced from 5 1/2 tons to 2 1/2 tons; and fan flow is reduced from 2,600 CFM to 1,400 CFM. In many cases--especially in commercial buildings, where mechanical systems represent a significant portion of the total construction cost--the monetary savings realized from the scaled-down mechanical systems is sufficient to pay for the costs of incorporating the energy-efficient strategies. Thus energy efficiency is achieved without increasing construction costs.

Energy-10 can present data output in 27 graphic formats, all of which compare the two cases in the computer's memory. Bar graphs compare energy loads, operating costs, and cost breakdown by end use. Line graphs show monthly loads, average daily profiles, daylighting effectiveness, and actual hourly results for any selected periods.

An Energy-Efficient Future Energy-10, version 1.0, was released in June 1996. Software owners can upgrade to the current version, 1.2, for free at the Energy-10 Web site at http://www.nrel.gov/buildings/energy10/. The site also contains detailed information on obtaining and using Energy-10 and general information on passive solar technology and energy efficiency.

The Energy-10 project brought together building expertise from the National Renewable Energy Laboratory, the Lawrence Berkeley National Laboratory, the Berkeley Solar Group, and the Passive Solar Industries Council (PSIC). The project was funded by the U.S. Department of Energy. Energy-10 is bundled in a package called Designing Low-Energy Buildings, which also includes a user manual and a guideline book called Passive Solar Strategies. The package is available from PSIC to professionals for $250 and to students for $50. Training programs based on the theory discussed in Passive Solar Strategies and the practical application provided in Energy-10 are available throughout the United States. To learn more about the workshops or to obtain a copy of the package, contact Doug Schroeder at (202) 628-7400 Ext. 210, through e-mail at PSICouncil@aol.com, or by writing PSIC, 1511 K St. NW, Suite 600, Washington, DC 20005.
 

 

 


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