It’s well-known in energy efficiency circles that commercial building owners can significantly reduce their energy bills by installing and properly maintaining building automation systems to manage their energy use. But quantifying how much energy specific control features save in particular building types and regions can be exceedingly difficult. That’s why the Building Technologies Office (BTO) enlisted researchers from Pacific Northwest National Laboratory (PNNL) to estimate just how much energy building control systems could deliver across the entire national commercial building stock.

What is Building Automation?

Building automation systems, which depending on their capabilities, can also be referred to as building energy management systems or other similar terms, are control systems that consist of sensors and actuators that are programmed using control logic to monitor and regulate operation of building equipment and systems (e.g., HVAC, lighting, and plug loads) in a coordinated fashion to optimize performance and energy use.

Today’s sophisticated automated controls have evolved into cyber-physical systems due to the tight interconnection between the software and hardware components used. Applications ranging from large-scale industrial process plants and power systems to automotive, aerospace, and buildings, are based on fundamental automatic feedback control theory, taking its roots from ancient times and the invention of the water clock.

The Impact of Building Automation Systems

The findings of the PNNL study, published in May 2017, show that installing currently developed and properly tuned controls could cut commercial building energy consumption by approximately 29% — equivalent to 4-5 Quads, or 4-5% of energy consumed nationwide.

The report developed this estimate by modeling how 34 different building control measures implemented in 14 different commercial building types would affect both annual energy consumption and peak electricity demand. The researchers built and simulated models for each of the measures in EnergyPlus, DOE’s flagship physics-based building simulation engine. By applying the measures to 14 types of commercial buildings across 16 U.S. climate zones, the researchers were able to develop accurate estimates of how controls could reduce energy consumption and peak demand from particular buildings in particular regions.

Of the measures studied, those with the greatest energy-saving potential nationwide:

  • Adjusting setpoints (e.g., lowering daytime temperature for heating, increasing for cooling, and lowering nighttime heating) (~8% reduction)
  • Reducing minimum air flow rates through variable-air volume boxes (~7% reduction)
  • Limiting heating and cooling to when the building is most likely occupied (~6% reduction)

Although the study found all commercial buildings across all climates could have an average total energy savings of 29%, some building types were found to have the potential to save more:

  • Secondary schools (~49%)
  • Standalone retail stores and auto dealerships (~41%)

Without detailed analysis looking at the impact of individual control measures in individual buildings, it would be impossible to identify these low-hanging fruit, which offer the opportunity to save a significant amount of energy at a relatively modest cost.

"Most large commercial buildings are already equipped with building automation systems that deploy controls to manage building energy use," said report co-author and PNNL engineer Srinivas Katipamula. "But those controls often aren't properly programmed and are allowed to deteriorate over time, creating unnecessarily large power bills.”

DOE’s Goals and Roles

The findings from this study highlight the tremendous potential of sensors and controls for building energy management. According to the U.S. EIA, up to 60% of the commercial floor space in the U.S. in 2012 did not utilize a building automation system to control spacing conditioning and/or lighting. In addition, control systems in buildings are still dominated by “hand-crafted” or rules-based algorithms, which are prone to error and very labor intensive to implement and operate. Technological advancements in buildings have lagged behind other industries. This is due to several factors that include utilization in more operationally critical applications (e.g., safety and security) in other industries, the fragmented nature of the buildings market (e.g., owner owned and tenant occupied), and the diversity of system configurations and limited modeling and integration capabilities of stochastic variables (e.g., occupants, weather forecasts).

The BTO sensors and controls R&D subprogram focuses on addressing these challenges through early-stage technology development of data-driven and physics-based model predictive control approaches already established in other sectors along with the exploration of emerging approaches in machine learning and artificial intelligence. The subprogram is organized around four key areas:

  • Multifunctional wireless sensor networks
  • Occupant-centric sensors and controls
  • Advanced submetering
  • Adaptive and autonomous controls

Furthermore, BTO has invested in open execution controls platform development to advance interoperability for autonomous building energy management solutions in the less-developed residential and small commercial buildings sector. In addition to ensuring anticipated energy savings through building automation are realized, the subprogram seeks to facilitate effective integration with the evolving electric grid, reduced electricity costs for building owners and tenants, and improved comfort for occupants.