TM54 is a new Technical Memorandum from CIBSE (the Chartered Society of Building Services Engineers) aimed at providing guidance on performing predictive energy modeling during the design stage. Here’s an overview of its recommendations and some examples of how you might put them into practice. But first, it’s worth noting the difference between predictive and comparative modeling.

Predictive vs. Comparative Modeling

As we’ve discussed in previous posts, most early-stage analysis is comparative, not predictive. Decisions about the shape and envelope of the building can be made effectively and accurately by comparing different options and using typical values for parameters like building occupancy, operating hours, and internal loads. For these comparative studies, much of TM54 is not applicable (although the idea of studying the sensitivity of different parameters can be very useful, as we discuss below).

However, there are scenarios in which architects are targeting specific performance values — a Net Zero Energy target or a specific Energy Use Intensity, for instance — and would like to know whether they’re on track to meet these goals. In these cases, TM54 is very relevant for ensuring that early estimates come as close as possible to reflecting as-built performance — and clearly articulating the uncertainty that inevitably accompanies the early stages of design.

TM54 Overview

The primary recommendations from TM54 are:

  • Use a Dynamic Simulation Model (like Sefaira) to estimate building energy use.
  • Source complete and accurate data for operational parameters such as occupancy, schedules, lighting power, and plug loads, rather than relying on typical defaults.
  • Present simulation results as a range rather than single deterministic numbers, to reflect the fact that performance depends upon variable factors such as weather, occupancy, and operation. High and low estimates can be determined by exploring multiple scenarios.
  • Compare results to existing energy use benchmarks to ensure that the results are reasonable.

Here’s how Sefaira can contribute to these objectives:

  • Use a Dynamic Simulation Model (DSM): Sefaira is a DSM that uses the ASHRAE-mandated Radiant Time Series method to generate fast and accurate energy estimates that account for not only internal and operating loads, but also all gains and losses through the building envelope. This ensures that the interaction of external and internal factors is appropriately captured.
  • Source complete & accurate data for operational parameters: First, Sefaira provides default values for occupancy and operational parameters for a variety of space uses (including defaults for parameters like plug loads, which TM54 specifically calls out). For designers performing comparative analysis, these defaults are a reasonable starting point and will provide good comparative results. Second, Sefaira allows customization of these parameters. If better information becomes available through interviews, research, or other means, the defaults can be easily changed.
  • Present results as a range: Sefaira’s rapid analysis and comparison-based interface makes it ideal for testing multiple scenarios and performing sensitivity analysis. Response Curves provides an easy way to do this for a large number of building properties — including the envelope properties for which architects are primarily responsible.
  • Compare results to benchmarks: Sefaira provides outputs in a format that is easily comparable. In addition, Sefaira for SketchUp incorporates several benchmarks directly in the user interface. These benchmarks automatically update based upon location and building use.

Exploring Scenarios and Sensitivity

One of TM54’s primary recommendations is to assess the impact on energy use of varying key operational and design parameters. These variations can be used to present high and low estimates for performance, clearly indicating the uncertainty inherent in early-stage performance calculations.

TM54 specifically mentions a number of studies for which Sefaira is ideal:

  • Building occupancy & operating hours. Designers can use Sefaira to create “high occupancy” and “extended hours” scenarios to understand the impact of these factors on performance.
  • Equipment & lighting loads. Designers can study multiple scenarios, reflecting everything from “good practice” values to “worst case” scenarios that include poor management or the addition of unintended lighting and equipment.
  • Efficiency of mechanical systems. Sefaira users can quickly test the sensitivity of mechanical system efficiency using parametric analysis.
  • Weather data. Sefaira has future weather files available for a number of locations, and designers can quickly test the impact of varying weather — helping architects design not only for the present, but also for the future.

In addition, Sefaira provides the opportunity to investigate the sensitivity of design-related parameters (for which architects are largely responsible) — items such as glazing ratios, shading amounts, building orientation, and envelope properties. While not included in TM54, these factors can have a significant impact on energy use.

Sensitivity analysis can be useful whether a designer is performing predictive or comparative modeling. Understanding the sensitivity of different parameters can help the architect focus on the factors that will have the biggest impact on performance.

Below are example scenarios and sensitivity analyses for a 100,000 sq. ft. office building in New York, NY. We explored five operational scenarios (left side of the chart) and the sensitivity of five design-related variables (right side of the chart).


The top five most sensitive parameters were: (1) plug loads, (2) lighting loads, (3) glazing ratios, (4) operating hours, and (5) glazing properties.

Notably, three of these five are clearly impacted by the building design: glazing ratios, glazing properties, and lighting loads. And previous explorations have shown 10 to 15% difference in energy use from varying building form alone. The architect’s decisions clearly have a major influence on the final performance of the building.

The remaining highly sensitive factors (plug loads and operating hours) present an opportunity for further engagement with the client, end users, and/or facilities manager to better understand and plan for the intended usage.

In line with TM54, we would present the estimated energy use as a bar graph with error bars:

estimated energy use

The error bars represent the high and low results from the sensitivity analysis. This communicates the range of likely outcomes, and can open a discussion about the factors upon which the final (measured) energy use will depend.



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