Performance Assessment of HVAC Control Strategies with Application to DR

Demand response (DR) programs have been growing in number and magnitude in the past decade to reduce load during the peak hours. Despite efforts to automate DR, we lack methods and tools to support facility/building managers with ‘how to respond’ decisions at building-scale. This is because there are multiple control strategies available at commercial buildings as response to a DR signal and quantifying the trade-off of these mechanisms for power management has remained a challenge. Hence, it is important to rigorously evaluate power performance of different heating, ventilating, and air conditioning (HVAC) control strategies under different scenarios. This cannot be achieved without quantifying performance. The authors have developed a set of quantifiable performance indicators (PIs) in their previous work by applying an engineering perspective on performance-based building design and operation. These PIs include the ratio of maximum to average power consumption, deviation of demand from nominal power use, energy consumption, and two measures of thermal comfort. This paper examines these PIs by systematically quantifying them under different scenarios of use to show how they can be used for power and energy assessment and management with application to DR. Scenarios defined were modeled and simulated in a controlled environment as a set of experiments. The platform used to model and simulate these experiments is EnergyPlus. Each PI was calculated in the post-processing stage to assess and compare performance of different control strategies. Quantification and assessment of power performance of HVAC control strategies enable development of decision support tools to facilitate building managers’ decisions in the context of DR.