After careful analysis and consultation, an energy manager at a large corporation has set an energy reduction target of 190 ekWh/m2 (18 ekWh/ft2) in her regional portfolio, a goal to be achieved within the next four years. Her team has prepared a comprehensive plan that includes yearly targets for each facility as well as a detailed approach to monitor progress. The facility teams in each of those buildings fully support this sustainability effort and have been working hard to formulate operational plans to achieve those energy reduction goals. To move forward, the energy management team recognizes the need for an Energy Information System (EIS) to provide regular metrics to track progress and evaluate energy savings. The facility management group also believes an Automated Fault Detection and Diagnostics (AFDD) tool is needed to identify faults, opportunities for optimization, and prioritize action.
“Can’t the Building Automation System alone provide such information?”, asks the management team, not fully understanding the need for yet another software platform. “How would an AFDD help achieve sustainability goals?” And, “wouldn’t both an EIS and AFDD conflict with one another?”
We approach the end of our current blog series examining how an Energy Information System profits from actionable information thanks to Automated Fault Detection and Diagnostics. To understand the value of an analytics solution comprised of an EIS and an AFDD system, it is helpful to differentiate between the specific roles, the kinds of measures, and the analytic approaches that characterize them.
Energy Information Systems are most often viewed as playing a strategic role using whole and dis-aggregated building energy consumption data as lag measures in a top-down approach. In contrast, Automated Fault Detection And Diagnostics tools are typically viewed as playing an operational role using data from building automation systems as lead measures in a bottom-up approach. Let’s look at these in more detail.
Strategic Roles Versus Operational Roles
In energy and facility management, strategic planning sets the direction for the organization. This, however, needs to be coupled with a clear and solid operational plan detailing the activities that need to be executed for the strategic goals and targets to be realized. Recall our earlier story? The organization’s strategy is to achieve a sustainability milestone across its entire building portfolio within four years, and they plan to use an EIS to monitor their progress. With an AFDD system in place, the facilities’ team would be able to implement a Monitoring-based Commissioning (MBCx) program to continuously monitor, supervise, and optimize their buildings. According to a Natural Resources Canada article on Building Commissioning and Recommissioning, this process, “could be the single-most cost-effective strategy for reducing energy costs and greenhouse gas (GHG) emissions in buildings today.” A comprehensive study resulted in 13% median energy savings in new buildings and 16% in existing buildings. [1]
Lag Measures Versus Lead Measures
The authors of The 4 Disciplines of Execution, a #1 Wall Street Journal Business Bestseller, urge us to “Act on the Lead Measures”, calling this the “discipline of leverage” [2]. They go on to explain that whatever the strategy, progress and success are based on two kinds of measures: lag and lead. In our story, the energy reduction target of 190 ekWh/m2 is a lag measure because the data used to calculate it is already in the past. So what can the organization do to achieve such a performance target? The key is not to forget the lead measures, and here is where an AFDD implementation is essential. Its supervisory nature will allow facility teams to measure system performance, detect and diagnose faults, and – this is vital – prioritize based on the most “high-impact” activities. Because in reality, buildings have hundreds of things that should be fixed or improved, an intentionally focused approach will drive success on the lag measures. So whether the ultimate goal is to improve energy efficiency, regulatory compliance or occupant satisfaction, clearly define the lag measures and take action on the lead measures.
Top-Down Versus Bottom-Up Approaches
In the paper, “An Overview of Building Diagnostics”, presented at the National Conference of Building Commissioning in Kansas City, the authors described two approaches to diagnostic reasoning, calling them ‘top-down” and “bottom-up”. While an EIS would typically focus on the higher levels of the hierarchy, an AFDD would focus on the lower levels.
Using performance measures from higher levels of the hierarchy, the top-down approach attempts to reason about possible lower-level causes affecting higher-level performance. The bottom-up approach, in contrast, measures performance at lower levels of the hierarchy and attempts to reason about the higher-level impact on building performance. Back to our story one more time, if the whole-building energy usage monitored by the EIS is not as expected, the top-down approach is used to navigate down the hierarchy and attempt to find the most probable explanation from the lower-level systems. Alternatively, when the AFDD finds under-performing zone systems, the bottom-up approach is used to navigate up the hierarchy to identify primary ventilation systems with the worst performance, and further up the ladder to determine the impact these systems are having on the overall building performance. All this information would be crucial to prioritize the impending corrective actions.
To summarize, facility and energy management teams often have different expectations on how analytic results ought to be presented. But one thing is clear, the information presented needs to be actionable. And this is one important reason why Automated Fault Detection and Diagnostics tools are a necessary complement to Energy Information Systems.
We hope that our fundamental questions and ensuing answers shared throughout this series have helped you navigate the vast realm of building analytics. Our passion acts as a catalyst that we hope leads to analytic-driven organizations. Get in touch with us to learn more about achieving continuous improvement with our Kaizen software.
[1] Natural Resources Canada. 2012. ecoEnergy Efficiency for Buildings. Building Commissioning and Recommissioning
[2] McChesney, C., Covey, S., Huling, J. 2012. The 4 Disciplines of Execution. Free Press.
[3] House, J., Kelly, G. 2000. An Overview of Building Diagnostics. National Conference of Building Commissioning, Kansas City, MO.
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CopperTree Analytics
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