Value of prediction in realizing DSM new construction savings - by Chris Baker

July 18, 2017 - Front Section

Chris Baker,
Weidt Group

For more than two decades, energy modeling, often as part of new construction energy design assistance programs offered by utilities around the country, has been used to assist architects and engineers during design. Although use of energy modeling to inform design has become significantly more prevalent, some skepticism remains about its accuracy and, therefore, long-term value. To address this accuracy question, The Weidt Group assembled a team to analyze 160 completed buildings that have all been in operation for a minimum of two years. 

It is well known that, during operation, individual buildings may be used differently than expected in design—from changes in space use, to occupancy and weather. This acknowledges that some buildings may use more or less than expected due to changes in occupant needs. Thus, over a portfolio of work, how close are design models to their operating buildings? To answer this question, the analysis compared metered energy consumption data to design energy model expectations, looking at the overall performance of the portfolio of buildings.  

Analysis Values and Realized Savings 

Energy modeling is best suited for comparative analysis, or assuming the value of implementing one strategy over another relative to energy code guidelines or energy savings capacity. This is what makes modeling during design so valuable, as building owners and design teams can understand the relative value of one design option versus another. Despite this, a desire often exists to compare design models to actual building performance to indicate if the comparative analyses are sound. The challenge is that factors, such as hours of operation, weather and the final as-built conditions of the building, may vary between the model and the operated building. 

In collectively analyzing this group of projects, the value lies in the average savings over the portfolio. This means that some projects will likely be higher energy users than expected, while some are lower.

In all the data, the key variable is building occupants’ capacity to do whatever they please.  There is no accurate way to factor actual occupant loads, equipment use or even the weather during design—models can only make educated assumptions. For these reasons, energy model accuracy can be questioned. However, this recent analysis shows that accuracy is achieved at a level that benefits both utility companies and their customers. In fact, over the entire portfolio of 160 buildings analyzed, the actual buildings used only four percent more electricity and one percent less natural gas than the design models predicted. Thus, when looking at a new construction utility program, for example, the design models accurately estimate the savings to the utilities grid, demonstrating that the programs are having the desired impact. 

The overall accuracy of the portfolio demonstrates that design teams and owners can provide information that accurately represents how they expect to use and operate new buildings. However, the data also shows that some building types have more variation in actual occupancy that is difficult to predict. Retail buildings, for instance, host an irregular number of customers per day. Office building tenants may work irregular hours, unlike the typical 8 a.m.-3 p.m. schedule of the average school. Irregular schedules equal unpredictable energy usage. 

Energy modeling should first be used to inform energy efficiency strategies during the design process. Taking the time during design to understand how the building is going to be used leads to more accurate models and better savings predictions. Using modeling empowers architects, engineers and building owners to invest in strategies that will have the greatest economic and environmental impacts for their particular buildings. 

This data combines a comprehensive analysis of 160 buildings of various types. Despite slight variations—often due to weather, occupant behavior and operational decisions—when considered as a portfolio, total electricity consumption fell within four percent of the models, and total natural gas consumption fell within one percent of the models. Although the primary purpose of energy modeling during design is not to predict energy bills, the data reveals that the value proposition of energy modeling extends to utilities, building owners, building tenants, energy policy makers and manufacturers. Energy modeling can, in fact, guide us in creating more energy-efficient commercial buildings. 

Chris Baker AIA, PE, BEMP, BEAP, LEED AP BD+C, is senior principal, energy analyst at Weidt Group, Albany, N.Y.


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