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The Energy Edge project provides conservation planners with information about how energy-efficiency measures perform in actual, occupied commercial buildings. The goal of Energy Edge was to redesign new commercial buildings to achieve energy consumption 30 percent below a hypothetical baseline. Baseline energy use was generally determined by simulating a baseline building that met the Model Conservation Standards (MCS). The primary objective of the impact evaluation was to assess the overall performance of the Energy Edge buildings and examine the energy savings and cost-effectiveness of individual energy-efficiency measures. Over 200 individual energy-efficiency measures were tracked. This report summarizes the performance data for all 28 buildings and results from 18 buildings that were evaluated using post-occupancy Tuned simulation models. Three key findings are as follows:
  • Commissioning and Improved operations and maintenance (O&M) are needed to ensure delivery of energy savings. A primary reason the energy-efficiency measures did not save as much energy as assumed during the design stage was poor commissioning and O&M. Improved performance measurement techniques are needed to identify and correct ongoing operational problems using enhanced data management and visualization tools.
  • Reducing building energy use by 30% beyond code is a feasible target, but difficult to achieve. Most of Energy Edge buildings consumed significantly less energy than comparable new buildings, though not achieving the 30% savings target. The greatest savings were found in the small office buildings, which used about 40% less energy than comparison buildings without compromising building quality or occupant satisfaction.
  • Lower-cost analysis techniques are needed, with special attention to developing better information on common building practice in new construction. The accuracy of the evaluation, based on expensive and time consuming monitoring and modeling, was hampered by difficulties in defining baseline conditions.

Key findings listed below are organized by subject corresponding to five chapters: program evaluation, building performance, measure performance, ensuring optimal performance of measures, and methodology assessment. The recommendations that follow from the findings are oriented toward improving future demand-side management programs, evaluations, and research and demonstration efforts.

1. Program Evaluation

Total annual energy savings were predicted to be about 17 GWh for all 28 buildings. Estimates of the achieved savings range from 13 to 71 percent of predicted savings. The range in estimates of achieved savings is based on the different methods used to extrapolate from incomplete results for some of the buildings to total savings for all 28 buildings. The lower savings estimates are dominated by the poor performance of the largest buildings. Several of the smaller buildings saved more than predicted and consumed less energy than predicted.

The main reason for the reduced savings is the change in the actual building systems and energy-efficiency measures. A second reason is that many measures, especially control measures, did not operate as well as predicted because of pool commissioning and ongoing operations and maintenance (O&M) problems. Average energy use was about 40% greater than predicted, with the greatest increase from heating, ventilation, and air-conditioning (HVAC) equipment. Longer hours of operation and poor O&M conditions are the likely cause for the increase.

Only one of the buildings met the program objective of reducing energy use by 30% below the code baseline, while meeting the cost-effectiveness criterion target of 5.6 cents/kWh. However, in reviewing the Design-phase estimates of measure cost-effectiveness, one-third of the buildings did not meet the target when they entered the program.

Energy-efficiency and Demand-Side Management (DSM) programs need to ensure that careful tracking and archiving of building and measure characteristics is conducted to evaluate how installed systems compare with design specifications. Changes in building operating conditions should also be carefully tracked, with special attention to typical HVAC operating conditions. Perhaps the most significant opportunity to reduce energy use in actual buildings is to turn off devices (e.g. fans, pumps, heat, or lights) when they are not needed. Analysis of hourly whole-building data from in-place utility meters or energy management and control systems should be exploited to identify and correct off-hour energy waste.

2. Building Performance

Most of the Energy Edge buildings consumed significantly less energy than comparable new buildings. The Energy Edge small office buildings (which consume about 12 kWh/sqft-year) have lower energy use than similar new buildings, with savings between 30 and 50%. The lighting and shell characteristics reflect energy-efficient design principles, and are significantly different than common practice, which partly explains their low energy use.

On average, energy use for all 28 buildings increased during the last four years of operation, though the rate of growth slowed each year. Fourth year energy use was six percent greater than third year, and almost 40% greater than predicted.

Evaluations of the energy performance of new commercial buildings should include comparisons with regional stock data, including an examination of code compliance issues. Building characteristics data should be combined with energy-use data to identify the impact of DSM or other energy-efficiency programs on improving overall building energy efficiency. Evaluations of new commercial construction cannot rely on first or second year energy use data to be representative of long term trends. Further research on persistence of savings is needed to evaluate how the measures perform over time.

3. Measure Performance

On average, post-occupancy Tuned energy savings for individual measures were slightly greater than half of Design-phase predicted energy savings. Among the 78 measures evaluated in the 18 Tuned building models, 41% met the cost-effectiveness criterion (cost-of-conserved energy [CCE] under 5.6 cents/kWh). Among the general classes of measures, the refrigeration and miscellaneous measures were the most cost-effective with median CCEs of 5.4 and 1.6 cents/kWh, respectively. Lighting measures were the next most cost effective at 7.5 cents/kWh (median), followed by shell measures at 7.8 cents/kWh. The HVAC measures were the least cost-effective, with a median CCE of 12.7 cents/kWh.

The most important reason energy savings were not as great as predicted is that measures changed. For example, the installed insulation levels were often less than the design values, and lighting power densities higher than initially specified. A second important reason for lower savings was the problems associated with dynamic measures, such as control measures. These measures were often poorly commissioned, that is, they were not correctly set-up for proper control, calibration, and operation. Analysis of specific measures, such as energy-efficient heat pumps and economizers, revealed that the energy savings from ensuring proper operation and control of building equipment could save as much, or more energy than installing more efficient equipment.

Careful tracking of measure characteristics is needed to ensure that the energy-efficiency measures installed in a building are the same as those specified in the design. Or, if a measure changed, the post-occupancy performance evaluation methodology should be able to account for the change. Verifying that installed equipment operate correctly is crucial to ensure energy savings. These factors should be considered when evaluating the cost-effectiveness of an energy-efficiency measure.

4. Ensuring Optimal Performance of Measures

Commissioning of energy-efficiency measures during building start-up is crucial to ensure that energy savings are achieved. Over two-thirds of the problems with measures in the Energy Edge buildings would likely have been caught and corrected with proper commissioning. Energy savings from the pilot commissioning study at the Director building resulted in reducing energy use by 8%. Further opportunities for another 4% in energy savings were identified.

Commissioning procedures are needed to ensure optimal performance of energy-efficiency measures and whole-building systems. These procedures include verifying proper equipment installation and calibration, functional and diagnostic testing, and preparation of O&M guidelines supported by O&M training. Further compilation and analysis of commissioning case studies is needed to evaluate the costs and benefits of commissioning. Careful tracking of deficiencies corrected by commissioning is needed to identify how to reduce the need for this extra step in building start-up, or retrofit start-up.

5. Methodology Assessment

Although it took about 400 hours to develop each Tuned model, develop the baseline model, and evaluate the energy performance of each measure, the energy savings and cost estimates are uncertain for some energy-efficiency measures because of difficulties in defining baseline assumptions that reflect the building code and current practice. Measures that were most difficult to model are HVAC and lighting controls, and infiltration measures. Furthermore, shortcomings in the project documentation hampered comparisons of building characteristics, measure definitions, costs, and O&M problems. Continuous end-use monitoring was expensive and often did not provide suitable information for the analysis of measure performance. Direct test, combined with functional and diagnostic testing for commissioning, could have been useful to determine the impact for many measures.

Future program evaluations should consider lower-cost, simplified methods for developing post-occupancy estimates of the performance of energy-efficiency measures using short-term monitoring, building characteristics, hourly whole-building energy use, and information from energy management and control systems. In many cases a direct test, rather than continuous end-use monitoring, is best (or only) way to determine a measure's impact. These tests should be combined with functional and diagnostic testing for commissioning during building start-up. Ongoing annual check-ups revising the energy-efficiency measures, building conditions, and control sequences would help maintain energy savings over time. Increased standardization in modeling guidelines and data reporting formats would greatly increase the ability of evaluations to track changes in building and measure characteristics. Further analysis of common practice regarding HVAC control sequences is needed to improve modeling of these systems.

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