“Demand Control” an Innovative Way of Reducing the HVAC System’s Energy Consumption

Abstract

According to EIA, the Heating Ventilation and Air Conditioning (HAVC) systems account for about 25% of the U.S.’s total commercial building’s energy use. Therefore, advanced modeling and optimization methods of the system components and operation offer great ways to reduce energy consumption in all types of buildings and mainly commercial buildings. This research introduced an innovative integrated two-level optimization technique for the HVAC system to reduce the total energy consumption while improving the indoor thermal comfort level. The process uses actual system performance data collected for the building automation systems (BAS) to create accurate component modeling and optimization process as the first level of optimization (MLO). Artificial neural networks were chosen to be the tool used to serve the process of modeling. The second optimization level utilizes the whole system-level optimization technique (SLO) using a genetic algorithm (G.A.). The proposed two-levels optimization technique will optimize the system setpoints, the supply air temperature, duct static pressure, minimum zone air flowrates, and minimum outdoor air ventilation rate. The proposed technique has contributed to the field of modeling and optimization of HVAC systems through several new contributions. (1) Implementing the demand control methodology with the optimization process to modify the electricity consumption power profile when the demand signal is received. (2) Implement the occupancy schedule inputs into the optimization process to adjust the ventilation airflow rates accordingly. (3) Implement the real-time zone occupancy sensor readings and adjust the zone’s ventilation flowrates and minimum flowrates. (4) Lastly, implementing the method of zone minimum air flowrates setpoint rests to reduce reheat requirements. The proposed optimization process was tested and validated, resulting in savings in the total energy consumed by the chilled water VAV system by 13.4%, 22.4 %, followed by 31% for July, February, and October, respectively.

New Optimal Supply Air Temperature and Minimum Zone Air Flow Resetting Strategies for VAV Systems

“…For instance, Seong et al introduced a model-based method to optimize airside and waterside variables [13]. Talib and Nassif introduce a data-based optimization engine to improve the operation of chilled water and DX systems, including system-and zone-level setpoints [14]. Kim et al proposed two control algorithms considering temperature and humidity as the factors of the indoor environment to maintain the occupant comfort while lowering the energy consumption in conventional HVAC systems [15].…”

HVAC System Control Solutions Based on Modern IT Technologies: A Review Article

“…The European Commission set the goal to reduce greenhouse gas emissions by 55% by 2030 from the 1990 level [7]. Considering that the HVAC system's energy consumption is approximately 40% of total building energy consumption [8,9], efficient energy usage is an essential parameter for modern buildings. However, just using modern HVAC equipment may not be enough to reach the high requirements of energy efficiency.…”