Common to many LEED projects is to produce an energy model on a completed design for the sole purpose of estimating points. This is the “how lucky did we get” approach. Thus, the energy model tool is not fully utilized, the modeling costs become an overhead, and opportunities for performance improvements are lost. It is under this scenario that the energy model gets labeled as having no value.
However, the energy model is remarkable when used as a decision making tool, deployed early, and integrated fully into the design process. At the early stages, a relatively simple model can be developed using the in-built default values for building types (space use, occupancy, process loads, etc.) and, from that, elements such as building massing, window selection and sizes, orientation, and lighting and HVAC system types can be optimized. Here, “optimized” implies the assessment of the value of a building feature balanced between first costs and its influence on whole building performance.
It is the whole building performance aspect that makes energy modeling so compelling and a tool that should be utilized on all building designs, regardless of certification goals. The long-established approach to building delivery was to make critical cost decisions on a line-by-line basis. For instance, glass cost, lighting power densities, and HVAC system efficiencies were assessed singularly with very little or no consideration for their interactions. Modern analysis, using the energy model as a decision-making tool, reveals the effect that individual measures have on whole building performance.
Window selection and lighting power affect HVAC size. Building orientation affects annual energy costs and is a critical consideration for using available daylight to illuminate indoor spaces. All of these elements interact. An example would be a museum project in Atlanta, Georgia, USA where code minimum glass values were originally specified for southwest facing windows. However, since the glass under analysis was shaded by retaining walls and overhangs, it was not necessary to buy such high performing glass. The energy model, through several iterations, demonstrated that less-expensive glass had no change in operating costs or HVAC system size. The result was a $50,000 first cost savings.
In most instances, when properly applied, the energy model can reduce first costs by optimizing the physical interactions between seemingly unrelated building elements.
