In the United States’ pursuit of sustainable sources of power, addressing buildings’ energy consumption is top priority. The U.S. building sector accounts for about 39% of the nation’s energy use, and commercial buildings are responsible for about half of that amount. Cities are struggling to find ways to make buildings more efficient, and they’re seeking solutions in their hardware, software and design tools to improve building efficiency.

Modeling and simulation

Because data is available on energy consumption, in addition to configuring parameters for buildings, it’s possible for engineers and scientists to model whole buildings and cities to draw inferences for deploying new building equipment and construction. In addition, modeling and simulation can help building owners and operators modify building performance to achieve the greatest efficiencies.

As tools become available, modeling and simulation have moved to the forefront of engineering tools that make the most efficient energy consumption possible. Specifically, the electricity demand from buildings results from a variety of different electrical loads.

The loads depend on its occupants’ overall demands. Many loads are flexible over the time of day and year, specific location and the surrounding geographic climate. Proper communications and controls enable loads to be managed so electrical consumption at different times and levels can meet occupant demand and satisfy their comfort requirements.

Working ‘behind the meter’

This has enabled efficient, grid-interactive buildings, and research is being performed with this in mind. The U.S. Department of Energy has a Building Technologies Office that seeks to incorporate all existing energy efficiency efforts and apply them to new building designs to optimize the interaction between energy efficiency, demand response and all things that go on “behind the meter” in energy generation and storage. Cumulatively, this helps to boost the flexibility of demand-side management.

Pittsburgh is one of 22 U.S. cities in the 2030 Districts Network. These cities pledge to reduce overall energy use, water consumption and transportation emissions by 50% by 2030.

Researchers at the University of Pittsburgh’s Swanson School of Engineering and Mascaro Center for Sustainable Innovation have created a model for Pittsburgh based on the designs, materials and purposes of the city’s commercial buildings. The model can estimate energy usage and emissions, and this research uses available data found in public records (data sometimes deemed unreliable and scarce) and buildings’ physical characteristics to better model them.

Researchers have found that the scale of commercial buildings make it cumbersome and sometimes impossible to find detailed information about all the buildings in urban environments. Therefore, in the past, researchers have relied on assumptions based on public records and available information about the buildings they were studying. What they found is that such data is scarce, sometimes unreliable and, in many situations, not useful.

Employing GIS with simulation

The University of Pittsburgh team tried a different approach. It developed the models using GIS (geographic information systems) that provided data from street-level images. The researchers then created 20 different building archetypes with eight different commercial use types. Buildings were sorted into groups and categorized using these archetypes and when they were built. The street-level images helped determine the building material, window-to-wall ratios and the number of floors. Data from the U.S. Geological Survey was used to determine building height, and the team was able to simulate and map the annual energy use of 209 Pittsburgh structures. They researchers validated their findings using other publicly available data and found they had just a 7% error rate using their imaging method.

The creation of urban models is on the rise as more cities are finding new and better ways to control their energy consumption and reduce their carbon footprint in an environment where climate change is taking precedence for public policy folks.