Optimal airconditioning system operating strategies for combined temperature and humidity control in buildings

This thesis describes the research and development of the simulation-optimization of building Heating, Ventilation, and Air-Conditioning (HVAC) systems focusing on both temperature and humidity control. Adequate humidity control is critical for the energy-efficient operation of buildings, human comfort and health, building materials, and product quality. With the increased demand for fresh air in buildings, it becomes apparent that much more research is needed in humidity control and thermal comfort issues. In many air-conditioning applications, humidity has been controlled indirectly by forcing the air temperature below the dew-point temperature, coincidental providing dehumidification as a side effect. Thus, the system operates inefficiently demanding high costs.; This study emphasizes this humidity control issue through an investigation of various promising HVAC equipment operating techniques. The main goal of the study is to provide a systematic framework and guideline for optimal operation of HVAC systems focusing on air-side. There has been no such comprehensive information available in the open literature.; One 30-ton rooftop unit was modeled to provide adequate cooling capacity. A computer simulation model of a direct expansion (DX) system was developed to simulate various operational techniques for improving part load air-conditioning performance. They are cooling coil face-split circuit control condenser fan control, compressor cylinder unloading, bypass air around cooling coil and variable airflow rate control. A numerical optimization technique, the direct search method of Golden Complex, was applied to search optimal solutions. Two commercial building types, retail store and supermarket building, under humid climate were analyzed. Building loads were predicted by least squared linear equations as a function of indoor and outdoor temperature and humidity differences. HVAC equipment capacity was matched to building sensible and latent loads through the optimization procedure. Because space setpoint problem is critical it was systematically investigated with several phases: a fixed set point, a variable setpoint with ASHRAE comfort zone, a variable setpoint with Predicted Mean Vote (PMV) constraint, a variable setpoint with a penalty function of PMV.; A combination of realistic DX air-conditioning system simulation and numerical optimization techniques were successfully performed with reasonable and consistent results. Complete tests under various outdoor conditions were successful by the extended bin analysis of the Typical Meteorological Year (TMY) data. Desired space setpoint conditions were also found through evaluating the trade-offs between comfort and energy consumption. The results show that variable setpoint optimization strategies with various HVAC equipment controls produces lower indoor humidity levels requiring less power consumption which will be of benefit for building applications of the humidity problem.