Добірка наукової літератури з теми "Optimization of HVAC energy consumption"

Directional airflow has been utilized to enable targeted air conditioning in cars and airplanes for many years, where the occupants could adjust the direction of flow. In the building sector however, HVAC systems are usually equipped with stationary diffusors that can only supply the air either in the form of diffusion or with fixed direction to the room in which they have been installed. In the present thesis, the possibility of adopting directional airflow in lieu of the conventional uniform diffusors has been investigated. The potential benefits of such a modification in control capabilities of the HVAC system in terms of improvements in the overall occupant thermal comfort and energy consumption of the HVAC system have been investigated via a simulation study and an experimental study. In the simulation study, an average of 59% per cycle reduction was achieved in the energy consumption. The reduction in the required duration of airflow (proportional to energy consumption) in the experimental study was 64% per cycle. The feasibility of autonomous control of the directional airflow, has been studied in a simulation experiment by utilizing the Reinforcement Learning algorithm which is an artificial intelligence approach that facilitates autonomous control in unknown environments. In order to demonstrate the feasibility of enabling the existing HVAC systems to control the direction of airflow, a device (called active diffusor) was designed and prototyped. The active diffusor successfully replaced the existing uniform diffusor and was able to effectively target the occupant positions by accurately directing the airflow jet to the desired positions.<br>M.S.<br>The notion of adjustable direction of airflow has been used in the car industry and airplanes for decades, enabling the users to manually adjust the direction of airflow to their satisfaction. However, in the building the introduction of the incoming airflow to the environment of the room is achieved either by non-adjustable uniform diffusors, aiming to condition the air in the environment in a homogeneous manner. In the present thesis, the possibility of adopting directional airflow in place of the conventional uniform diffusors has been investigated. The potential benefits of such a modification in control capabilities of the HVAC system in terms of improvements in the overall occupant thermal comfort and energy consumption of the HVAC system have been investigated via a simulation study and an experimental study. In the simulation study, an average of 59% per cycle reduction was achieved in the energy consumption. The reduction in the required duration of airflow (proportional to energy consumption) in the experimental study was 64% per cycle on average. The feasibility of autonomous control of the directional airflow, has been studied in a simulation experiment by utilizing the Reinforcement Learning algorithm which is an artificial intelligence approach that facilitates autonomous control in unknown environments. In order to demonstrate the feasibility of enabling the existing HVAC systems to control the direction of airflow, a device (called active diffusor) was designed and prototyped. The active diffusor successfully replaced the existing uniform diffusor and was able to effectively target the occupant positions by accurately directing the airflow jet to the desired positions.

The primary purpose of the current research was to implement a numerical model to investigate the interactions between the energy consumption in Heating, Ventilating, and Air Conditioning (HVAC) systems and occupants’ thermal comfort in commercial buildings. A numerical model was developed to perform a thermal analysis of a single zone and simultaneously investigate its occupants’ thermal sensations as a non-linear function of the thermal environmental (i.e. temperature, thermal radiation, humidity, and air speed) and personal factors (i.e. activity and clothing). The zone thermal analyses and thermal comfort calculations were carried out by applying the heat balance method and current thermal comfort standard (ASHRAE STANDARD 55-2004) respectively. The model was then validated and applied on a single generic zone, representing the perimeter office spaces of the Centre for Interactive Research on Sustainability (CIRS), to investigate the impacts of variation in occupants’ behaviors, building’s envelope, HVAC system, and climate on both energy consumption and thermal comfort. Regarding the large number of parameters involved, the initial summer and winter screening analyses were carried out to determine the measures that their impacts on the energy and/or thermal comfort were most significant. These analyses showed that, without any incremental cost, the energy consumption in both new and existing buildings may significantly be reduced with a broader range of setpoints, adaptive clothing for the occupants, and higher air exchange rate over the cooling season. The effects of these measures as well as their combination on the zone thermal performance were then studied in more detail with the whole year analyses. These analyses suggest that with the modest increase in the averaged occupants’ thermal dissatisfaction, the combination scenario can notably reduce the total annual energy consumption of the baseline zone. Considering the global warming and the life of a building, the impacts of climate change on the whole year modeling results were also investigated for the year 2050. According to these analyses, global warming reduced the energy consumption for both the baseline and combination scenario, thanks to the moderate and cold climate of Vancouver.