To evaluate whether your building is a good candidate for DCV, determine if it fits one of the suitable facility types, then estimate potential savings using occupancy patterns and estimate the DCV implementation costs to calculate a payback period.
Select by facility type. Facilities that would likely reap energy savings with the use of DCV tend to have long operating hours, widely varying and largely unpredictable occupancy, and at least moderate annual heating or cooling loads. A very large number of facilities meet this description, including grocery stores, supermarkets, big-box stores, theaters, lecture halls and other performance spaces, places of worship, sports arenas, restaurants and bars of all types, and department stores. In fact, the majority of commercial facilities that are not now using DCV are at least potential targets for the technology (Table 2).
Table 2: Applicability of DCV by type of facility
This table, developed by HVAC manufacturer Carrier Corp., ranks the potential applicability of demand-controlled ventilation (DCV) by type of facility. Note that most facility types receive either a “recommended” rating, indicating that DCV will be advantageous for most facilities of that type, or a “possible” rating, indicating that site-specific factors must be considered and evaluated. Only a few types of facilities receive a “not recommended” rating, and the reasons are obvious for most of them. For example, the high concentration of volatile organic compounds present in an industrial painting and finishing facility would make it a poor candidate for DCV.
Among the facility types with a “recommended” rating in Table 2, some are much better candidates for DCV than others. For example, buildings that are larger, have higher occupant densities, and have higher variability in occupancy (such as auditoriums, sports arenas, large conference or meeting rooms, and ballrooms) are much more likely to yield significant energy savings and acceptable paybacks than smaller facilities (such as coin-operated laundries or dressing rooms).
Any facility designed to accommodate high occupancy—like most of those with a rating of “recommended” in the table—would be a great candidate as long as its actual occupancy is below design capacity most of the time. But there are also opportunities to implement DCV cost-effectively in facilities that have a “possible” rating. The best way to determine whether a given facility is a good candidate is to estimate potential energy savings using a computer simulation, which is referenced below.
Estimate occupancy patterns: Energy savings can be difficult to pin down, as they are highly dependent on both the maximum number of people a space is designed to accommodate (that is, the design occupancy) and the actual occupancy patterns on an average day—which can be difficult to determine. The difference between these two metrics reveals the opportunity for savings. For example, if a space is designed for 100 people, but actual occupancy falls as low as 30 people for several hours at a time, it may well be possible to dramatically reduce ventilation rates and reap savings.
So how can you determine whether your particular supermarket, restaurant, or casino is a good candidate? A good first cut would be to simply estimate occupancy on an hourly basis for a typical week in each season, and compare that data with the building’s design occupancy, which will be specified by local building codes. Even better, if you can get hourly data from cash registers, you can use it to approximate occupancy by associating a given number of shoppers, theater-goers, or diners with each register transaction. With that information in hand and with knowledge of the facility’s design occupancy, you can generate a reasonably good estimate of DCV’s energy-saving potential using one of the evaluation tools downloaded free of charge off the Internet (Table 3).
Table 3: DCV evaluation tools
Each of these programs can be used to evaluate potential energy cost savings from demand-controlled ventilation (DCV). They are all available free of charge.
Measure occupancy patterns. If actual, estimated, or proxy data (for example, receipts) on occupancy aren't available, one low-cost way to determine the applicability of DCV is to use a portable CO2 sensor to measure the effective ventilation rate for a given facility. Portable sensors coupled to dataloggers are available from several manufacturers at prices ranging from $550 to $700. These devices won’t measure occupancy directly, but they will determine the effective ventilation rate per person, based on the difference between measured interior and ambient outdoor CO2 concentrations.
To assess the viability of DCV in a particular facility, locate the portable sensor away from doors, windows, loading docks, and other potential sources of bias, and let it record for a period of at least one week. If CO2 concentrations are below 800 parts per million (ppm) much of the time, the facility is probably a good candidate for DCV. Concentrations consistently above 1,000 ppm suggest that DCV is unlikely to provide much in the way of energy savings. However, if CO2 concentrations rise above 1,500 ppm on a regular basis, DCV may be desirable for an entirely different purpose—air-quality improvement. If interior CO2 concentrations are getting this high, it's probably an indication that body odors and pollutants—such as off-gassing from building materials, furniture, or other products—are accumulating, and occupant comfort could be improved by increasing ventilation.
If the actual design ventilation per person (pp) for a given facility is known, data from a portable CO2 sensor can be used to estimate actual occupancy at any time. The CO2 concentration inside a building is given by this equation:
CO2 in = 10,600/cfmpp + CO2 out
CO2 in and CO2 out represent the internal and external concentrations of CO2 in ppm respectively, and cfmpp represents the per-person ventilation rate of the building. If you know the internal and external CO2 concentrations, you can determine the actual ventilation rate of the building per person at any given time:
cfmpp = 10,600/(CO2 in – CO2 out)
Dividing the building’s design ventilation rate per person by this actual value allows you to determine occupancy of the building as a fraction of design occupancy. The resulting hourly occupancy estimates can then be used in any of the DCV savings evaluation tools discussed above.
Estimate the cost of installing DCV. To estimate return-on-investment or payback time using a savings evaluation tool, you will need to estimate the cost of installing one or more sensors and modifying HVAC controls to implement CO2-based control. Today, individual sensors cost around $200 to $250; you will need a sensor for each RTU and/or each zone in the space—a minimum of one sensor for every 5,000 ft2 of floor space (Table 4).
Table 4: Carbon dioxide sensor placement
This guide will help you determine the number and placement of carbon dioxide (CO2) sensors that will be required to implement demand-controlled ventilation in any given facility.
Implementing DCV on a newer DCV-ready RTU with an existing economizer will cost between $300 and $900 per RTU. The lower end of this range would apply where installation amounts to no more than wiring the sensor into the existing RTU terminals. Installation costs will rise to the higher end of this range when a digital controller is needed to interface with the RTU.
If you’ve got an old economizer, it’s cheaper and more reliable to replace the electronic components than to create an interface with older technology. The cost of replacing the economizer motor, controller, and enthalpy sensors and implementing DCV ranges from $1,500/RTU for multiple RTUs to $2,000 for a single RTU. Costs will be higher if the entire economizer needs to be replaced or if the RTU is not equipped with an economizer. In either case, the added benefits from having a properly working economizer (independent of DCV) would also need to be factored into any calculation of cost-effectiveness.