(65e) Cost and Efficiency Optimal HVAC System Operation and Design
In 2007, US commercial and residential buildings accounted for 40% of total energy consumption and 38% of CO2 emissions, with HVAC systems accounting for over 30% of total building energy consumption and 35% of building CO2 emissions . In order reduce the energy needs of a building while maintaining thermal comfort and Indoor Air Quality (IAQ), advanced HVAC control systems must be developed.
Acceptable room temperatures are specified by the ASHRAE standard 55 ?Thermal comfort for human occupancy? . Typically air flow through a heater or cooler is used to regulate to a temperature set-point using a PID temperature controller. Outdoor air is introduced to the room to maintain IAQ as specified by the ASHRAE standard 62.1 ?Ventilation for acceptable IAQ? , which specifies two approaches. The first employs a fixed ventilation rate of outdoor air to maintain contamination concentrations below a specified level using a prescribed rate of outdoor air that depends upon the room area and population. The alternative is to combine a contamination sensor with a control system to sense contaminants of interest and adjust outdoor air ventilation rates to ensure the contaminant concentration levels are within the designed limits.
The proposed model based HVAC control scheme is grounded on the notion of back-off control. The basic idea is that one would like to operate at the Optimal Steady-State Operating Point (OSSOP), typically at a corner of the feasible operating region. (In the HVAC context, process constraints represent maximum and minimum specifications with respect indoor air temperature and contaminant levels. The OSSOP is the point of least energy use, assuming no variation in heat leakage or contaminant load.) Unfortunately, operation at the OSSOP is impossible due to the influence of external disturbances. (In the HVAC case, the expected disturbances are changes in outdoor air temperature as well as the contaminant generation rate.) These disturbances will cause the system to operate, not at a single point, but within an Expected Dynamic Operating Region (EDOR). If one attempts to operate at the OSSOP, the EDOR will almost certainly extend beyond the constraint set and result in numerous constraint violations. Thus, the challenge is to select a Backed-off Operating Point (BOP) that is economically close to the OSSOP while ensuring that the EDOR is completely contained in the constraint set. While EDOR size and shape is a function of the disturbances acting on the process, the selected control system will also have an influence. This ability to manipulate the EDOR is then used to reduce the amount of back-off. In Peng et al., , such a back-off selection scheme is outlined and will form the basis of proposed Energy Efficient Controller Design scheme.
The second half of the paper extends the back-off control approach to include the notion of Market Responsive Control. The basic idea is to consider the spot price of electricity as a disturbance to the controller. Then the controller will exploit the thermal mass of the building (and the solid material within the building) to draw extra electricity when prices are low and thus reduce electricity usage during peak price periods. For cases in which the building contains little thermal mass, the cost trade-off of purchasing an external thermal storage device will be investigated.
 EIA. "Annual Energy Outlook 2009." US Department of Energy, posted at http://www.eia.doe.gov/oiaf/aeo/index.html (2009).
 ASHRAE. 55-2004, Thermal Environmental Conditions for Human Occupancy. American Society of Heating, Refrigerating and Air Conditioning Engineers (2004).
 ASHRAE. 62.1-2007: Ventilation for Acceptable Indoor Air Quality, American Society of Heating Refrigerating and Air-Conditioning Engineers (2007).
 Peng, J., A. Manthanwar and D. Chmielewski, ?On the Tuning of Predictive Controllers: Minimally Backed-off Operating Point Selection,? Ind. Eng. Chem. Res., 44, 7814-7822, (2005).