Improving energy efficiency in the Heating Ventilation and Air conditioning (HVAC) systems in buildings is critical to achieve the energy reduction in the building sector, which consumes 41% of all primary energy produced in the United States, and was responsible for nearly half of U.S. CO2 emissions. Based on a report by the New Building Institute (NBI), when HVAC systems are used, about half of the zero net energy (ZNE) buildings report using a radiant cooling/heating system, often in conjunction with ground source heat pumps. Radiant systems differ from air systems in the main heat transfer mechanism used to remove heat from a space, and in their control characteristics when responding to changes in control signals and room thermal conditions. This dissertation investigates three related design and control topics: cooling load calculations, cooling capacity estimation, and control for the heavyweight radiant systems. These three issues are fundamental to the development of accurate design/modeling tools, relevant performance testing methods, and ultimately the realization of the potential energy benefits of radiant systems.
Cooling load calculations are a crucial step in designing any HVAC system. In the current standards, cooling load is defined and calculated independent of HVAC system type. In this dissertation, I present research evidence that sensible zone cooling loads for radiant systems are different from cooling loads for traditional air systems. Energy simulations, in EnergyPlus, and laboratory experiments were conducted to investigate the heat transfer dynamics in spaces conditioned by radiant and air systems. The results show that the magnitude of the cooling load difference between the two systems ranges from 7-85%, and radiant systems remove heat faster than air systems. For the experimental tested conditions, 75-82% of total heat gain was removed by radiant system during the period when the heater (simulating the heat gain) was on, while for air system, 61-63% were removed. From a heat transfer perspective, the differences are mainly because the chilled surfaces directly remove part of the radiant heat gains from a zone, thereby bypassing the time-delay effect caused by the interaction of radiant heat gain with non-active thermal mass in air systems. The major conclusions based on these findings are: 1) there are important limitations in the definition of cooling load for a mixing air system described in Chapter 18 of ASHRAE Handbook of Fundamentals when applied to radiant systems; 2) due to the obvious mismatch between how radiant heat transfer is handled in traditional cooling load calculation methods compared to its central role in radiant cooling systems, this dissertation provides improvements for the current cooling load calculation method based on the Heat Balance procedure. The Radiant Time Series method is not appropriate for radiant system applications. The findings also directly apply to the selection of space heat transfer modeling algorithms that are part of all energy modeling software.
Cooling capacity estimation is another critical step in a design project. The above mentioned findings and a review of the existing methods indicates that current radiant system cooling capacity estimation methods fail to take into account incident shortwave radiation generated by solar and lighting in the calculation process. This causes a significant underestimation (up to 150% for some instances) of floor cooling capacity when solar load is dominant. Building performance simulations were conducted to verify this hypothesis and quantify the impacts of solar for different design scenarios. A new simplified method was proposed to improve the predictability of the method described in ISO 11855 when solar radiation is present.
The dissertation also compares the energy and comfort benefits of the model-based predictive control (MPC) method with a fine-tuned heuristic control method when applied to a heavyweight embedded surface system. A first order dynamic model of a radiant slab system was developed for implementation in model predictive controllers. A calibrated EnergyPlus model of a typical office building in California was used as a testbed for the comparison. The results indicated that MPC is able to reduce the cooling tower energy consumption by 55% and pumping power consumption by 26%, while maintaining equivalent or even better thermal comfort conditions.
In summary, the dissertation work has: (1) provided clear evidence that the fundamental heat transfer mechanisms differ between radiant and air systems. These findings have important implications for the development of accurate and reliable design and energy simulation tools; (2) developed practical design methods and guidance to aid practicing engineers who are designing radiant systems; and (3) outlined future research and design tools need to advance the state-of-knowledge and design and operating guidelines for radiant systems.