Modelica, integrated control, ventilation, model-based design
The accelerating decarbonization of energy systems to address climate change and the increasing recognition of the role that buildings play in occupants' health have served to further emphasize two long-standing trends in the buildings and HVAC industries: the pursuit of ever-higher energy efficiency for buildings, and the proper management of the overall indoor environment. These two objectives, which are often at odds, are becoming ever more linked due to the emergence of new practices in the buildings industry that require both reductions in energy intensity and the improved management of temperature, humidity, and ventilation. In seeking to improve thermal comfort while reducing power consumption, the dynamics due to interactions between coupled subsystems, such as ventilation systems and VRF systems, become increasingly important, and must be properly designed and managed to achieve the desired system-level performance. We explore one approach to address these challenges by using a model-based process to design an HVAC system for a building including both a multi-zone variable refrigerant flow (VRF) system and a ventilation system. Such an approach is essential because the dynamics of both the VRF system and the ventilation system affect the thermal conditions of each zone; as each system acts as a disturbance to the other, the overall dynamical system can either develop limit cycles or can evolve toward an operating point which consumes more power than is necessary while satisfying specified setpoints. We use the equation-oriented language Modelica to construct detailed multiphysics models of the individual VRF, ventilation, and building systems, and then couple these models together to analyze the overall system properties. We then design a method for coordinating the control of these systems to maintain system performance while minimizing the energy consumption, and demonstrate the efficacy of these methods using realistic dynamic building inputs, such as time-varying occupancy and weather data. While these models have significant advantages in their use for control design, their modularity also provides a promising path for the rapid evaluation of alternate system architectures. This is particularly useful for the system under study, as multiple ventilation systems with different costs and energy performance can be used to provide fresh air to the occupied space. We thus study the performance of the building with the VRF system with three alternate ventilation approaches: a simple fan, an energy recovery ventilator (ERV), and a dedicated outdoor air system (DOAS). Such an methodology illuminates the potential energy impact of each ventilation approach on the overall HVAC system; because the use of the DOAS significantly reduces the load on the VRF system, the total system energy consumption can be reduced by over 50% by using the DOAS as opposed to a simple fan. The final paper will describe and elaborate on such results, providing a concrete demonstration of the benefits of model-based system and control design for HVAC systems in buildings.