Coordinate Temperature Control in Large-scale Spaces Based on Wireless Sensor Network


Student thesis: Doctoral Thesis

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Awarding Institution
Award date22 Aug 2017


A large-scale indoor space characterized by a high height and a large indoor area, thus presenting an uneven load distribution, may consume significant energy for air conditioning in a subtropic climate region such as Hong Kong. To improve the energy efficiency of the air-conditioning system, one needs to monitor the temperature distribution accurately and adopt a proper control strategy to handle the uneven and complex load distribution. However, in most conventional control designs, a single thermostat is used to manipulate the operation of all of the air terminals synchronously, where the temperature sensor is always located in the return air head duct. Thus, this type of control design does not control the temperature at the occupied level and neglects the uneven load distribution. Therefore, the temperature control might not be acceptable in terms of thermal comfort because overcooling or undercooling might occur in a large-scale space as a result of uneven load distribution. Simultaneously, energy may be wasted because of overcooling. Therefore, this thesis presents a study to overcome this problem by developing a coordinated temperature control strategy with the aid of a wireless sensor network (WSN). A WSN was used to deal with the measurement problem, and a coordinated temperature control strategy was developed to cope with the dynamic variations in load distribution and to improve the energy efficiency of the air-conditioning system.
Firstly, the energy-saving potential of using a WSN was investigated. It is believed that by deploying multiple wireless temperature sensors in the occupied zone, the temperatures around the occupants can be measured accurately, which can in return improve the temperature control performance and the energy efficiency of the air-conditioning system. To this end, numerical simulation and experimental studies were carried out, where multiple temperature sensors were used to replace a single sensor in conventional control design. Two types of ventilation were considered—mixing ventilation (MV) and displacement ventilation (DV)—and two types of load conditions—fully and half-occupied conditions.
Secondly, the installation and management of a WSN were investigated in a real large-scale indoor environment, with the objectives of monitoring the dynamic manner of temperature profiles online and studying the stability and reliability of the data identified for further consideration in the control system. A WSN testbed was constructed, and more than 30 wireless sensor nodes were installed in the breathing zone of this space. The phenomenon of uneven temperature distribution was analyzed and identified after almost one year of online monitoring. A that combined the utilization of numerical simulations. Abnormal data identification and data reconstruction methods were carried out to preprocess the raw data from the site measurements. An optimized airflow rate allocation algorithm was developed, and the temperature homogeneity of the whole space was improved. The stability and reliability of the WSN from the network itself were analyzed and appropriately enhanced measurements were conducted at the end. The results proved that a WSN could be used to effectively improve the operation of air conditioning systems in large-scale spaces.
Thirdly, a new temperature modeling method for large-scale open spaces to model the uneven temperature distribution for the control application was developed. The major problem for the developed model was to identify the heat transfer coefficient (HTC) between adjacent zones. Thus, a numerical method using computational fluid dynamics was introduced to identify the HTCs by implementing user-defined functions (UDFs) into a Fluent solver. A real chamber with two subzones was selected to calculate the HTCs. A momentum method for describing square ceiling diffusers was modeled with UDFs. Fifty cases with different combinations of supply airflow rate and heat load were numerically solved. The relationship between the heat exchange and zonal temperature difference was obtained finally, which could be utilized in control simulations with coordinated control strategies. To this end, the thermal coupling effect between adjacent zones in a large-scale space was modeled and verified.
Finally, a coordinated temperature control strategy based on a WSN is proposed. This strategy divides a large-scale space into a number of zones (according to minimum controllable units of air terminals), and each subzone is controlled independently based on the zonal temperatures detected by the WSN. The proposed control strategy, combined with the thermal coupling effect, could be applied to achieve the temperature dynamics of large-scale open spaces while keeping the zonal temperature in each subzone at its temperature set-point. The proposed method for the control application was investigated using the commercial software TRNSYS; the coordinated control strategy was programmed in MATLAB and then linked to TRNSYS. The results from the case studies showed that the introduction of a heat transfer coefficient between adjacent zones was able to improve the accuracy of describing the temperature dynamics of large-scale open spaces. The proposed temperature model could be used to develop or investigate control methods used in multiple zone control modes for large-scale spaces. Compared with a conventional control strategy, a 10% energy saving in the consumption of supply fans was achieved during the period of simulation. Thus, the proposed coordinated temperature control for large-scale spaces based on WSN could be used for energy reduction in HVAC systems.

    Research areas

  • Wireless Sensor Network, Large space, HVAC system, Temperature control, Uneven load distribution, Thermal coupling