Optimizing Benchmarking Methods for Greater Energy Efficiency
By Mike Laurie, PLANiT Measuring
Informed and accurate benchmarking is the key to transitioning from a building’s current energy usage situation to its optimum energy conservation condition. Without knowing the starting point or the ultimate destination it is virtually impossible to travel in a straight line without getting lost, detoured, or wasting more resources than necessary to make the trip. That means that the first step toward energy efficiency is to figure out the best benchmarking methodology – both in terms of the current energy situation and the target goal of peak energy efficiency performance.
The Normalized Energy Usage Approach
Because blueprints, floor plans, and many other factors differ from one building to the next, no two roadmaps to energy savings follow the same route. So normalizing is generally used to achieve the greatest common denominator, build a model, and then look for deviations from the norm. If those deviations are in the direction of lesser efficiency they can be addressed to move them through the normative or average benchmark and into the area of the greatest possible efficiency – defined by the upper range of the data set.
Meanwhile new energy efficiency innovations can be implemented as they become available. That will hopefully move the entire scale or desired range of statistical possibilities and outcomes in the preferred direction toward carbon neutrality or optimum building performance and energy conservation.
Building Information Modeling can analyze the options to determine the energy performance of a building.
Predictable Knowledge Gaps
The data from the individual building being studied during the energy analysis converges around a generalized norm established by data collected from lots of other buildings in an attempt to create a close facsimile and comparable model. But using generalized benchmarks makes it inevitable that the analysis will include gaps between theoretically comparable buildings and the actual building in its real life condition and usage. The recommendations or remedies will likewise have intrinsic gaps between the theoretical and the realistic. The trick is to close that gap by populating the database with more and better samples of comparable structures and similar influential factors.
When trying to identify an unknown person, for example, it is traditional to use a generic composite sketch like those created for law enforcement purposes. Multiple witness accounts and descriptions are matched to typical or archetypal facial shapes and patterns of features to create an artistic rendering of the unknown subject. Of course detectives would rather have a recent photograph of the actual person and a set of their unique individual fingerprints. But in lieu of that kind of ideal representation they settle for a pieced-together composite image.
In terms of energy analysis for the building industry the detective work revolves around a building and unknown peak performance factors. The description or “fingerprints” of the subject are represented by such things as architectural blueprints and carbon footprint data.
But even if it were possible to populate a building model or benchmark database with every comparable building in the world it would not achieve the kind of specificity or highly representative modeling that comes from profiling the exact one-of-a-kind building being studied. That would be ideal – just as a recent photograph and set of fingerprints would be ideal tools for the detective trying to identify an unknown person. In the absence of that specific information, however, the normalized approach may be helpful when trying to identify an unknown person from vague descriptions. Similarly, it may be a great asset for helping to determine such things as the median price per square foot of comparable buildings for sale in a particular market.
But energy efficiency retrofitting or upgrading is not a one-size-fits-all proposition. Every building consists of a complex infrastructure of uniquely interdependent systems and system components. A more building-specific way to address those complexities and potential shortcomings would be to use a model of the building itself to establish benchmarks and then create another model of the same building – but in a more idealized energy efficient condition – to represent the building’s ultimate performance goal.
Improving the Odds with Statistical Sampling
In the absence of superior tools or resources, the approach of doing energy analysis based on normalization offers what appears to be the next best thing, and for that reason it has become a popular and widely used method. Simply stated, this approach involves taking samples of buildings and then comparing them to other comparably-designed buildings with similar features. These include factors such as site orientation, local geography and climate patterns, building occupancy rates and energy usage habits, the cost of buying energy from utility companies, the age and specifications of construction materials, and so forth.
But in many rather fundamental respects this is nothing more than a sophisticated form of real estate appraisal – one that is based on energy values and metrics instead of the kinds of typical market values that appraisers try to extrapolate, calculate, and predict. Appraisal methodology occupies a vitally important place and serves an essential purpose. But it is not intended to be a substitute for the kind of methodology, for instance, that is needed to perform a comprehensive mechanical and structural inspection conducted by a certified engineer.
By the same token, normalization can be entirely useful. But it is never going to deliver a detailed and customized energy analysis of an actual building based on its own unique performance footprint and real world potential. Normalization strives to approach that ideal, and in lieu of a superior method it does a commendable job.
The Parametric Modeling Approach
But what the building industry needs to realize is that there are superior solutions and more accurate alternatives. For many years the aerospace industry has, for example, addressed the limitations of normalized modeling or sampling by using parametric 3D design software. Instead of sampling the responses of lots of similar aircraft and then normalizing the data to arrive at a statistical benchmark, these engineers create a virtual model of the specific aircraft they want to test using its own particular plans and specifications. Once the model has been created and populated with its own data – not generalized data from other aircraft – they are at liberty to change various elements and parameters, watch how the model responds, and make intelligent and cost effective design or remodeling decisions.
Physicians do essentially the same thing when they examine a patient. Rather than using normalized data to create a facsimile profile of the patient based on other people of similar age, weight, and medical history they test the actual person who comes to them with a health complaint. The patient and doctor know that the goal is perfect health and well being, so using that as their model or benchmark they then examine discrepancies between that state of excellent health and the current condition of the sick patient. If a broken bone is discovered it is mended; if a disease is depleting the patient’s energy then it is cured to restore optimum energy levels.
Even when doing an appraisal the professional appraiser doesn’t arrive at a definition of “highest and best use” by comparing buildings that are similar. Like a good physician the appraiser first determines the highest possible potential and ideal for a specific property and then works from that premise and benchmark to suggest ways that the property’s performance might be improved.
But until recently the kind of software used by the aerospace and automotive industries was not practical for the real estate industry. Not only did it require highly developed technical proficiency as a prerequisite for anyone who wanted to use the software, but it was extraordinarily expensive. Plus it required accurate drawings and plans of existing buildings – and most of the data on architectural structures comes from the original blueprints or hand-drawn plans. These are notoriously error prone because each time plans are transferred to a computer program or even copied by a photocopy machine the accuracy of the measurements is compromised.
Meantime, the building depicted in those blueprints or plans is constantly changing. Floor plans are altered, occupants and the way they use the building change, equipment either deteriorates or is upgraded and replaced, and even the basic formulas used to make drawings and measurements evolve. Using a conventional measurement may, for instance, generate a completely different set of calculations than will be derived from performing a BOMA-certified measurement.
Building Information Modeling Energy Analysis
Fortunately, Building Information Modeling (BIM) technology has eliminated virtually all of these obstacles and pitfalls by bringing the most sophisticated modeling and analysis software to the real estate industry at a highly affordable price point.
The way it works is that the existing building in question is rebuilt in a virtual way using that same kind of state-of-the-art software. The benchmark is established by ensuring optimum performance according to the specific potential of that particular building. That means that, for example, all the windows are sealed properly and the power plant is functioning as it should. The real world conditions of the building site are also realistically simulated – including factors such as weather conditions obtained from the local weather station, the cost of fuel used to power building equipment, and even the solar impact on the building depending upon site orientation, the presence of shade trees or reflective buildings next door, and the thermal impact of such things as nearby highways or cars radiating heat off metal surfaces in a full parking lot.
Data is collected on an hour by hour, day by day basis to generate real world date for an entire year. Then the reconstructed building is analysed to show the breakdown of energy usage, water usage, thermal zones, and other variables. Once the model is completely populated with real world information it becomes the benchmark for the building it represents. There is no guesswork involving “similar buildings” because the existing building being studied is analyzed only in comparison to itself under various conditions that are strategically modified by the BIM operator. The gaps that are discovered between the ideal model and the real building have a direct correlation to the green health of that unique building.
BIM as a Scalable Resource
By simply experimenting with such things as retrofits that are applied to the virtual model in a multitude of combinations and permutations it is possible to correctly, instantly, and affordably increase the energy efficiency of the building.
Everything from daylight studies to rain water harvesting to solar and wind potential are available at the touch of a computer key.
Reface the façade. Add an insulation jacket. Put on new window film. Calculate how fast rain cisterns will become filled. Chart the impact of solar heat and sunlight on windows to identify problems areas for occupant comfort to ways to leverage available natural light to reduce lighting bills or enhance the ambience of a space.
Experiment with filtering light through window film to heighten the visibility of computer screens or study the productivity of workers as it relates to such variables as room temperatures or acoustics. Find out if an investment in solar panels will generate a solid return or not. Experiment with using recycled water instead of piped water to keep landscapes healthy.
The BIM provides other interesting benefits, too, because it continues to serve as an interactive, updatable visual database and archive of all building components. Manufacturer warranties, construction material specs, lease contracts, and other pertinent data can be imbedded into the BIM “smart plans” and accessed with the click of a computer mouse via handy pop-up menus or screens. Print out the exact square footage of all the painted wall surfaces whenever they are needed for maintenance quotes without the need for contractors to make site visits and charge to do their own measuring. Eliminate the need for third parties to generate or update paper plans that have been accumulating for years, and print out AutoCAD drawings of any slice of the building including floor plans, 3-D views, cross sections, and elevations – all in-house without any special technical expertise.
A Direct Path to Sustainable Returns
As energy costs rise, resources dwindle, and the incentive for reduced carbon emissions becomes greater, knowing how to accurately predict the energy efficiency potential of existing buildings becomes increasingly valuable. The most direct path to practical solutions is a customized, site-specific BIM approach.
Rather than trying to beat the averages, it is now possible to leverage the full potential of a particular asset and maximize value with precise solutions that can be tested and proven beforehand in a realistic environment.
by Michael Laurie, P.Eng., President of PLANiT Measuring which provides onsite building measuring and BIM services. He can be reached at mike@planitmeasuring.com or 1-800-933-5136.
Tags: BIM, building information modeling, commercial energy audits, Energy Efficiency with BIM, PLANiT Measuring
