Building Simulation: An International Journal

Article Title

A novel on-off TRV adjustment model and simulation of its thermal dynamic performance


heating system, on-off valve adjustment, building thermal characteristic, indoor thermal dynamic performance, control, comfort, energy saving


Field test results show that about 15% to 40% of building heat loss in China is attributable to poor heating systems regulation. The current method for addressing this problem is to install thermostatic radiator valves (TRVs) to the ends of radiators, a method adapted from northern Europe. However, this method has resulted in poor performance from delayed controlling action due to thermal inertia as well as insufficient system control accuracy. This is further compounded by incorrect operation by system users and a lack of financial incentives to regulate the system if users are not billed for their heat consumption. We present a new method for simultaneously heat controlling and metering. The core challenge is to design a control strategy that will maintain the room’s temperature. Thus, we established dynamic heat transfer models for water flow, the radiator and the building so as to obtain the optimal heating strategy. We also simulated the indoor thermal dynamic performance of the heating system with different heating loads, supply water temperatures, and supply water flow rates using three methods: a continuously changing flow rate (Method 1), a step-change flow rate based on temperature deviation (Method 2) and an intelligent step-change flow rate (Method 3) which predicts the duty cycle of the valve in the proceeding period and controls the valve’s on-time. The simulation results indicate the performance of these three methods. For Method 1, as the room temperature is above the set point, the flow rate can be automatically reduced to a level which is proportional to the room temperature deviation. Further, the scale factor of the flow rate is designed according to the +2°C deviation, so it is accepted that the room temperature is higher than the set point by +2°C using this method. However, this low control precision is unsatisfactory. The mean temperature is higher than the set point and greatly affected by the heating load and supply water’s temperature and flow rate. For Method 2, the controlling action is delayed by thermal inertia, the room temperature fluctuates between the highest and lowest levels, and the temperature deviation can be greater than the set value. For Method 3, both the simulation and field test results showed that room temperature deviation was maintained within a ±0.5°C range under the various conditions. This method appears relatively robust and adaptable, and was the best control strategy of the three methods.


Tsinghua University Press