Using energy modeling throughout process

Whole-building energy simulations guided the designs of all the buildings. Energy simulation in pre-design helped to set measurable goals, and identified areas with high potential for energy savings and peak reductions. The design team used energy models to determine the minimum energy targets, incorporate the climate and the program goals, evaluate envelope options and architectural designs, and design mechanical systems that matched the predicted loads. Finally, NREL used simulations to evaluate postoccupancy performance and verify design goals. Simulation tools used for design analysis and POEs for these buildings included DOE-2.1E, DOE-2.2, and EnergyPlus.

The energy use and costs of a building depend on the complex interaction of many parameters and variables. The problem is far too complex for rules of thumb or hand calculations. Computerized energy simulation software can thoroughly evaluate all interactions between the envelope, HVAC system, and design features. The best time to develop performance targets is at the beginning, before any design concepts have been developed, because energy analysis affects design less and less as the design

proceeds. Yet energy analysis, if done at all, typically starts about the time of design development and is typically used for code compliance or selection of HVAC type—not for designing the building envelope.

An “elimination” parametric analysis helps designers understand the sensitivity of total energy performance at specific loads. A parametric analysis is performed by eliminating loads—conduction losses, people, solar gains, and plug loads—one at a time from the simulation. As loads are eliminated, the designer determines their impact on the total energy performance by comparing energy use with and without each load. For example, if eliminating all conductive heat transfer through the envelope has little

effect on energy consumption and energy costs, there would be little reason to increase insulation levels to exceed code. Similarly, the exercise may demonstrate an upper limit to the amount of insulation before internal loads begin to increase cooling loads. The design team may discover that finding an optimal insulation level allows money otherwise spent on additional insulation to be used elsewhere, with a greater impact on the total energy picture. If, however, eliminating all solar gains greatly affects energy performance, solar-related issues such as window area, orientation, window solar heat gain coefficient, and facade shading geometry (such as window overhangs) are worth exploring. An energy goal for the climate and building type should be established based on this analysis, and all team members should agree on its feasibility.

In all cases, energy simulations played an important part in understanding the forces that drive energy performance and allowed many design alternatives to be investigated. At BigHorn, additional windows were added that vastly improved daylighting in the building. At the TTF, clerestory heights and overhangs were optimized, minimizing cooling loads while maximizing daylighting.

3.1.4.1 Setting energy baselines in the low-energy design process

A standard performance metric for low-energy buildings is often percent savings. The first problem with this is determining the baseline or reference point for comparison. Most often, baselines are based on a comparable code-compliant building. For the six buildings studied, the design predictions used baselines that included ASHRAE 90.1-1989 (ASHRAE 1989), 1999 (ASHRAE 1999), 2001 (ASHRAE 2001), and 10 CFR 435 (DOE 1995). For consistency among the case studies, actual energy savings were

determined for most of the buildings in comparison with ASHRAE 90.1-2001.

An essential element of the case studies has been defining and analyzing baseline models that are used to determine energy and energy cost savings. We used baselines to analyze energy performance for

buildings from predesign stages to postoccupancy as-built buildings. When building designs and operations change, the baseline has to evolve along with the building under consideration.

Three classifications of baselines were used depending on the design progress and purpose of the baseline (see Table 3-3). The baseline classifications used include:

• The Predesign Baseline is used in the initial stages of the low-energy design process. This is a theoretical building based on basic information known about a proposed building in the pre-design phase. Basic inputs of building function, size, and location are used to define the predesign baseline, which is then used to estimate annual loads and peak electrical demands for heating, cooling,

lighting, plug loads, and HVAC system fans and pumps. In general terms, a pre-design baseline building is “solar neutral.” For a typical commercial building, a predesign baseline design is a rectangular floor plan with an aspect ratio of 1.75 that uses a simplified zoning scheme with

windows distributed equally at all four cardinal orientations. An “elimination” parametric analysis is performed to help building designers understand the driving forces and sensitivities of energy performance and energy costs in the climate under consideration.

• A Proposed Design Baseline is used to determine the energy performance of a building during the design process. It represents a minimally code-compliant version of the proposed design. When the design of the proposed building has progressed to the point where floor plan, layout, and other physical fabric characteristics have been determined, the proposed design baseline is modeled in four orientations by rotating the baseline model 90° four times, and then averaging the results. This baseline includes features of the building design such as location, size, footprint, building use, fuel types, and expected schedules. Appendix G of ASHRAE 90.1-2004 provides a method for determining the annual energy performance of a proposed design baseline along with the proposed design (ASHRAE 2004).

• The Existing Building Baseline can be used to evaluate the energy performance of existing

buildings. The need to verify design goals during occupancy is increasing, especially for the current

generation of low-energy commercial buildings. Often, the as-built building has significantly different physical and operational characteristics than the building design. Thus, the baseline comparison for the existing building must be updated to reflect actual operation during typical occupancy. Assumptions made for the design baseline, such as occupancy schedules, equipment loads, weather, and set points, are measured in the existing building and included in the existing building baseline. Further evaluation techniques for existing buildings are discussed in Section 3.7.

Table 3-3 Baseline use in the low-energy design process Rendering of Baseline Models Design Process Baseline Use

Solar Neutral Predesign Baseline

• To develop an understanding of the building site, local climate, and functional requirements.

• To help set measurable design goals that are reasonable and attainable.

• To complete a parametric analysis to determine sensitivities to specific load components.

Proposed Design Baseline and Existing Building Baseline

• To evaluate preliminary design solutions. Energy and cost

• To verify the existing building meets the design goals.

3.1.4.2 Modeling in postoccupancy evaluations

Whole-building energy performance modeling was essential for determining energy savings and developing recommendations to address identified problems. To calculate the energy savings of a building, a model must be calibrated against actual building data. In most cases, too many changes occurred from design to occupancy to use the design-based models as accurate predictors of energy consumption. Schedules and plug loads vary widely from original assumptions. The base-case model must be modified to reflect the as-built schedules and plug loads. A calibrated as-built simulation compared to a conventional base case can provide a confident prediction of annual site, source, and cost

savings. Using typical meteorological year weather data allows long-term savings calculations with relatively short-term data.

Energy saving uncertainties can be minimized when savings are determined from the comparison of one simulation to another (e.g., base-case to as-built). Because difficult-to-know inputs are held the same in both simulations, such comparisons remove much of the uncertainty inherent in an hourly building energy simulation. Variables that change throughout the year, such as inconsistent occupancy, set point changes, and equipment performance degradation, are difficult to account for in an annual building energy

simulation. Comparing a base-case model to an as-built model with the same schedules reduces the uncertainty. Further lessons learned in using simulations for design and evaluation purposes are discussed in Section 3.7.