Achieving Projected Automation: Implementing Misfit Energy Model Recommendations


Energy performance modeling is a highly sought-after service in the facility design and construction industry, but is arguably becoming more so in the existing building renovation and upgrade industry. Whether in an energy savings performance contract (ESPC) or a large facility controls upgrade, savvy industry-participants are turning to sophisticated energy modeling to create a business case for bankable energy savings. This article explores these interdependencies in existing buildings, where they can be misconstrued, and in some instances a case of the blind leading the blind.

While energy modelers are not required to perform detailed walkthroughs of existing buildings, it is difficult to truly understand systems and control sequences without the in-field guidance of a building’s controls integrator. Modeling teams are scouring existing buildings throughout the world and are modeling savings from a known-quantity of energy conservation measures (ECM); often without really knowing what existing controllers are doing. If this is the case for one of your projects it is very likely that modelers know even less about what existing controllers are incapable of. It is also true that energy modelers are not completely aware of the capabilities of their project’s controls integration contractor, and vice versa. This is often the beginning stages of a poorly executed ESPC or controls upgrade, when bankable savings are a key component of financing or payback. As a result modelers are forced to assign a contingency factor to their analysis, which energy service companies (ESCO) then add their layer of contingency to. So what is really bankable in that scenario?

Energy modelers also rely on simulated control strategies during energy model calibration, matching models to actual weather and billing data, which is often performed in a vacuum-like digital environment. This is especially true if controls and integrator limitations are unknown, and more so when expectations of energy models are vague. If these two attributes are not understood and ECMs are simulated in a vacuum-like environment the proposed measures are unrealistic, compounding their eventual lack of bankability. Limitations and unstated expectations are not new to engineering or building controls, but they skew the fundamentals associated with ECMs (several of which will be discussed herein).

As an energy modeler and analyst I often come across new communication techniques to facilitate team-building, and modeling tools to account for the imperfect nature of facility automation. Whether we create our own tools, or use a great new development of our peers, one thing is clear: sophisticated modeling and modeled savings rely heavily on equally sophisticated building automation system (BAS) controls. Taking that interdependency one step further, these two digital sectors have something even more critical common, and aside from experienced software operators: their reliance on motivated and trained facility managers (FM). While FMs are not the focus of this article, their role is a lot like the base of a typical team pyramid; they can either create a reliable foundation for continued performance or exacerbate systems degradation.

Because modelers and integrators rely so heavily on FMs, it is important to also integrate expectations and limitations of a project’s FM. Project delivery and bankability becomes much more reliable once the entire team is able to admit what they, and the controls, cannot do. FMs do not necessarily need to know what a points-list is, but it is important for them to know which systems can talk to one another and which can only be read. It seems commonsensical, but not only will an informed FM be willing to step out of their comfort zone when they are part of the conversation, they will be less likely to raise issue about something that is an immovable weakness in a BAS.

Realistically Forecasting Controls Upgrades

When creating a business case for a controls upgrade, financial performance metrics like payback and cost/benefit ratio are highly dependent upon simulated BAS conditions, which rely further upon communication with FMs and controls integrators. As a result of these interrelations, it is the energy modeler’s responsibility to seek out conversation with other team-members. If modelers stay in their silos there is no communication loop, which leads to improper assumptions in a simulated environment and unreasonable assumptions when programming ECMs into a BAS.

Forecasting future building performance requires the input of all facility stakeholders before, during, and after a controls project’s implementation. The most common breakdowns occur between performance modeling and controller programming during implementation. As financial performance metrics for ECMs are provided to ESCOs and FMs, these forecasts are often provided with built in contingencies and disclaimers specifically regarding building operation. These contingencies are becoming good practice in the modeling industry, as more becomes known about the role of other team members when bankable savings are on the line.

Financial performance metrics like simple and discounted payback, return on investment, life cycle cost, opportunity cost, cost/benefit ratio, and annual energy cost savings rely heavily on good energy-modeling assumptions. Unfortunately many of these assumptions are products of research projects and databases, especially as related to maintenance cost impacts, when more accurate figures can be obtained from FMs and experienced contractors. Many facility managers, controls contractors, and building owners tend to forget that their roles in these assumptions are equally (or more) important than analysis predictions. If a BAS receives detrimental assumptions, annual energy savings benchmarks could easily be missed by 200%.

Maintenance costs, overhaul costs, and useful lives of equipment are key components of life cycle performance predictions; often driving a particular ECM ahead of the pack among a series of ECMs identified for a given facility. Regardless of the assumptions an energy modeler makes during an analysis, a breakdown has occurred somewhere if: Chiller 1 is predicted to be the best option over Chiller 2 on paper, but requires twice as much maintenance than predicted for Chiller 2. While controls integrators will receive the brunt of a FMs displeasure stemming from an underperforming system, the cause is sometimes traced back to performance models built without BAS communication inefficiencies.

If you do not operate in the ESPC market or in bankable energy cost savings projects, you may not yet see how deep energy savings often rely on superior performance in energy models. In most cases there are two primary factors that lead to underperformance, as compared to predicted consumption. First, facility managers are largely responsible for keeping to building management schedules, set-points, setback temperatures, building warm-up times, and other systems performance factors in the BAS. If an energy performance model is unaware of the fact that existing controls prohibit the dedicated outside air systems (DOAS) from reacting to signals from the heat-pump condenser water loop overheating or cooling will occur. Similarly if boiler pumps cannot communicate with signals from differential pressure sensors, excessive reheat may occur in VAV systems. In both of these cases models will assume everything is responsive and communicating, and an ECM to dynamically reset boiler output for varying VAV reheat loads is unknowingly not bankable during financial performance tests. The unfortunate breakdown in these scenarios lays among the modeler assuming open-protocol communication among controllers, and the contractor assuming the modeler somehow knows all of the details supporting the implementation of ECMs affected by the BAS.

The second impending factor related to underperformance is a result of scope-creep. Because modelers in an ESPC or a bankable savings project often rely on contractors for access to trend-logs and points-lists, some modeling professionals may be restricted to an energy modeling scope alone. More often than not, understanding trend analysis is crucial in making informed decisions about simulated building performance, including sub-meter data where available. These datasets are important when determining to include safety factors in models that keep equipment running just a bit longer than a basis of design or shop-drawings. Regardless of the industry sector or modeling purpose, parasitic night-time and weekend loads obtained from trend-analysis can be the difference between a useful energy model and a rule-of-thumb. Without the ability to run meaningful trends in an existing building, and scope to evaluate them, an energy model can be more misleading than useful.

In many cases modeling is more than changing control temperatures and features, the “whole picture” needs to be evaluated; this is especially true as trend-analysis begins to relate to inter-zone dynamics (air-flow, reheat, etc.) when modeling with powerful industry-leading software.

Pre-Communicating Findings

In existing buildings, from audit, to analysis, to install the following best practices and considerations are precursors to communicating findings to a FM or another owner’s representative.

  • Ensure that the actual controls engineer is in the ECM discussion to verify plausibility and contingency factors, introducing actual effectiveness into the conversation (i.e. actual air distribution and limitations to comfort and control).
  • Energy models assume that the BAS has complete ability to flawlessly control building systems and need to be told that older existing buildings do not recover as quickly as a new construction, more infiltration is likely, and ECMs often change a building’s stability as a result of affects to its mass-balance.
  • Bring light to the fact that some analysis tools are sometimes flawed, especially with VFDs, is important to diagnose complicated systems in hourly output reports (in lieu of default monthly or annual reports). Teams should be asking questions like: “Can a pump or fan realistically turn down that low? Is building pressure going to become an issue with a new sequence? Is a terminal unit’s control damper really able to be that dynamic?
  • In digital-pneumatic hybrid facility or in a partial upgrade project, before qualitative implications from ECMs are discussed, specific and fundamental questions such as “How can our controller go from analog to digital, on a legacy version, of a marginally open protocol? And are there enough points in the controller module to accomplish this new sequence?
  • Performance curves for major pieces of existing equipment should be modified to reflect existing power draws, efficiencies, and outputs; simulation programs should not be allowed to use default performance – which assumes that equipment is functioning like new. Systems degradation and fouling/scaling factors are important in areas with poor water quality or poor preventative maintenance practices.

Prior to project implementation a successful team should take the time to review assumptions and limitations of the proposed controls system, as well as the means used to calculate energy savings. If an energy modeler is using a dynamic load reset schedule to achieve cooling-plant savings, each of the inputs should be clearly stated and either accepted or adjusted by the controls integrator. Many times a single measure in an energy model involves more than a dozen field implications, some of which may not be possible. In this regard it is helpful to create a how-to-guide framework for communicating project hand-off.

A successful example of handoff documents should include the following five parts. (1) A brief explanation of a proposed measure, to be used as initial conversation with the building owner in order to obtain authorization to proceed, (2) A list of temperatures, schedule-implications, and power-demand savings, (3) a list of all affected equipment associated with the measure, (4) known limitations or approximations of the energy modeling software or calculation, and (5) a written review of how to implement the measure by the controls integration engineer. While it is ideal for the individual responsible for implementing the savings measure to provide the review in step five, many ingrained workflows do not allow for this type of interaction. Many times automation contractors rely on project managers to interface with a project team, and be a liaison to the building owner and installation team.

When communication is perfect traditional workflows are acceptable, but perfect communication is rarely the case and controls-project managers often juggle more than one project at a time. For this reason, a written five or six step guide is a tangible piece of documentation to refer to, and more importantly is a basis of design. A recommend sixth step would be a post-implementation trend-analysis by the energy modeler to confirm successful implementation. When written plans are not presented and agreed upon, the field-integrator responsible for programming new or existing controls may be forced to assume a set-point or schedule in order to finish his or her work on time.

While it does not necessarily make sense for modelers to follow controls integrators into the field to observe the installation of new controls, a project close-out procedure should take place. Should scope-creep or tight budgets be a concern it may be difficult for the energy modeler to generate post-installation trend-logs, and communication breakdowns occur at the end of an ESPC or bankable controls upgrade. When a modeler is able to observe post-installation trends, systems adjustments are typically necessary, which is especially helpful to know before the controls contractor receives a punch-list or final payment. A post-install facility walkthrough will also help confirm installed conditions as compared to the basis of design, closing the loop of bankability.

Matthew Higgins, CEM, ASHRAE-HBDP, LEED-AP (BD&C), MBA

Founder & Chief Analyst


Vibrantcy: Collaborative Engineering for Mechatecture

Mr. Higgins founded Vibrantcy after experience working in both a specialty sustainability consulting firm and a large commercial and government M/E/P engineering firm. Mr. Higgins has worked on over 300 new and existing building energy modeling projects, over 100 of which had an associated LEED certification goal. His expertise also includes extensive energy measurement and verification studies, Energy Star building certifications, life cycle cost analysis, creation of specialize analysis tools, and a breadth of public speaking experience throughout the southwest.