Scale & Integrate Disparate Building Management Systems
Every building occupant creates energy demand requiring ventilation, thermal comfort, lighting and in some cases electrical power. Aligning energy use to actual, real-time building occupancy would seem to be a key energy strategy. Yet, how many building owners or managers even know how many people actually occupied their building yesterday, last week or last month? Unless the buildings are retail stores, theme parks, museums or stadiums where the number of occupants directly translates to financial revenue and business intelligence, the answer is probably “next to none”. Sure, some building owners and managers may have a general average of typical building occupancy. Do they have real time or granular data on space occupancy? No.
Projected or scheduled occupancy plays an important role in facility programming, space planning and the development of life safety plans. These tend to be one time projections, design guidelines or estimates however that do not reflect actual occupancy and building use. Building occupancy fluctuates and predicting such numbers in large commercial buildings is difficult if not impossible. For example, studies have shown that office buildings occupied by service-sector companies are oftentimes less than 50 percent occupied – clearly one doesn’t lease or own office space knowing or projecting that only half of the space is really needed.
Occupancy data has several uses. Real time occupancy data is important during life safety events or alarms where people need to be accounted for. For example, knowing how many people are in a building can help first responders at an emergency in a building, such as a fire. Occupancy data can also be used for determining staffing requirements, scheduling maintenance and cleaning work and for security purposes.
Energy and Occupancy
Many current buildings do use some real time occupancy sensors related to energy systems; occupancy sensors used with lighting systems, CO2 sensors with HVAC systems to indicate or estimate the occupancy in a space, access control systems which can provide metrics on people entering or leaving controlled doors, and generalized system scheduling based on projected occupancy. While this is good start, it still doesn’t get us all of the granular, accurate occupancy data we really need. Occupancy sensors may reflect if space is occupied – but not how many occupants; the CO2 sensors are indicators of occupancy-not accurate counting devices; access control may be able to reflect how many people enter a space but also must require people to badge out of the space if real time occupancy counts are to be accurate.
What we need to know to align energy use and occupancy is how many people enter a building, what spaces they go to within the building and how long they stay in the building or space. The relevant energy areas to be affect by this type of occupancy data would be HVAV systems, the process of measurement and verification, and demand response.
Measurement and Verification (M&V) - M&V is the process of accurately measuring and verifying energy and water savings. When you measure and verify the effect of an energy conservation measure you need to account for occupancy changes between the benchmark or base year and the post-retrofit time period. Obviously, inaccurate occupancy data skews the adjustments and the conclusions or perceived results of the energy conservation measure.
HVAC Systems – Occupants in an HVAC zone will affect the cooling and ventilation loads, which in turn determine the amount of conditioned air delivered to the space. CO2 sensors indicate occupancy and are generally used in larger spaces and meeting rooms. The HVAC strategy of Demand Controlled Ventilation (DCV) is focused on spaces or zones that have variable occupancy rates. Accurate occupancy data has the potential to optimize the cooling and ventilation requirements in building spaces.
Demand Response – Planning for demand reduction or demand response can be tricky. Adding accurate occupancy data into the process allows for another key variable to be considered: how many occupants will be affected by the demand reduction scheme.
Gathering Occupancy Data
So how do we go about getting this data? The most accurate occupancy data involves doorways where people enter or exit the building or the building spaces. The most popular technology for counting people at the doorway appears to be thermal sensors or imaging, infrared and video analytics.
Thermal imaging devices sense a person’s body heat,
and compare the thermal image of a body’s heat to the background thermal image.
Thermal imaging is not affected by lighting or other conditions. Typically
devices are mounted from 8 to 15 feet high and contain a sensor, imaging optics,
a signal processor and some type of networking interface to connect to other
devices or the main administration terminal.
Infrared technology creates beams across a doorway. When the beams are broken by a person passing through the doorway a person is counted and the timing of when they break the second beam indicates direction, entering or exiting.
Video imaging typically uses small cameras mounted overhead of a doorway and video analytics to count and differentiate between people entering and exiting a building or space. The video analytics creates two lines, similar to the infrared using two beams and detects motion as to when the line are broken. It is not unusual to find the people counting capability as an add-on module of a video surveillance system.
There are other ways to count people but they require slight changes in the behavior of the occupants. For example, you can use access control to identify when people enter a space. Usually people are not badging out of a space though so you may not be able to get data on actual occupancy and timing. You can require people to badge out, but to many people it may seem unnecessary as they see access control focused on control of people entering spaces not exiting.
Another potential way of measuring real time occupancy is with RFID technology.
This requires an RFID system throughout the building and occupants carrying an
RFID key FOB. The key FOB could be used for access control and with an embedded
RFID tag, be tracked on the occupant throughout the building. So much like
access control, tracking occupancy via RFID would require a slight behavior
change; the occupant would need to be carrying the key FOB at all times. The
upside to this is that an RFID system throughout a building can have multiple
uses. At the top of that list would be asset management and additional security
measures. In short, the RFID system can effectively track both people and
Utilization of the Occupancy Data
Eventually we want to use accurate data on people entering and exiting doorways to buildings and certain spaces as a means to align the building’s optimum energy use. The granularity of occupancy data that will be useful is based on the layout of the energy related building systems. The lighting systems will have zones, the VAVs will support specific spaces or zones and the electrical circuits and distribution will also serve specific spaces or rooms. The layout of a people counting system should be strategic and mapped to the lighting, HVAC, electrical distribution and metering zones. With that overall approach you have accurate occupancy data, can correlate it to granular “energy consuming zones” and receive valuable information on how the building is really performing and where improvements may lie.
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