Thermohygrometric modeling and control for occupant comfort in buildings

Abstract

We present a control strategy where the mass flow rates into each zone are the control inputs to the system, while the control objective is to drive the system outputs, i.e. temperature and humidity ratio, into a comfort zone set (a temperature and humidity ratio region defined on the psychometric chart) as recommended by the American Society of Heating, Refrigerating, and Air-Conditioning Engineers (ASHRAE). We first show that the interconnected dynamic system is passive, therefore any passive controller is stabilizing and able to drive both temperature and humidity to steady states within the thermal comfort region. We then propose several passivity-based controllers to regulate the outputs within the comfort region. To illustrate the effectiveness of the proposed control strategy, simulation results from implementing the controller on the lumped model are then compared with CFD simulations of the testbed. The proposed controller design approach is also shown to be robust to model parametric uncertainty, with results of the CFD simulations verifying this attribute. The control structure is finally improved through inclusion of a learned feed-forward input. Since buildings are generally subjected to repeated disturbances, such as weather conditions and specific occupancy schedules, the control performance may be enhanced through iterative learning control for increased disturbance rejection and output regulation. The feed-forward control preserves the passivity configuration of the overall system and ensures thermohygrometric convergence within the comfort set.

Higher demands for human comfort and energy efficiency have been placed on building indoor environment control systems in recent decades. These energy and comfort performance metrics are generally at odds with each other, and contemporary building control techniques tackle overall efficiency by focusing on specific aspects of Heating, Ventilating and Air-Conditioning (HVAC) control systems. Major areas of interest include improvement in modeling of building thermal behavior; advancement in design of hardware system controls; and development in intelligent control methods. In all these areas, satisfying the human comfort index needs to be factored into design improvement. The main categories of human comfort include thermal, air quality and illumination levels. For thermal comfort, the most significant parameters to be regulated are temperature and relative humidity. This is related to the strong coupling of temperature and humidity dynamics during thermal exchange between building zones. These coupled dynamics and energy interactions require adequate consideration for achieving thermal comfort and energy optimization in control implementation.

To address some of the challenges and limitations in building indoor environment control, this thesis presents a modeling and control scheme for passivity-based control of thermohygrometric (temperature and humidity) conditions in buildings. We first develop a control-oriented thermohygrometric model using lumped parameter analysis, where we characterize the inherent mass and energy interactions between dry air and water vapor. We approach the thermal comfort problem as a coupled temperature and humidity dynamical system network with an input-state bilinearity. The network of rooms/zones in the building is captured through an undirected graph, employing electrical circuit analogy, with rooms represented as capacitances and walls, doors/windows as resistances. The proposed model structure and parameters are validated through simulations on a computational fluid dynamics (CFD) model, as well as through model identification with experiments on an existing intelligent building control testbed.