Air thermal management platform assessment in centralized and decentralized air-conditioning systems

In both centralized and decentralized air-conditioning systems, the performance, sustainability, and efficiency of the systems in delivering thermal comfort within a specific area are assessed as part of the air thermal management platform evaluation process. The evaluation of air thermal management platforms entails a thorough examination of numerous elements, customized to the unique features of these systems, such as system components, energy efficiency, control systems, maintenance procedures, and environmental concerns. The study considers mathematical modeling of energy-efficient techniques based on meteorological data of cooperative centralized and decentralized air-conditioning systems for external air recirculation treatment. Three systems were considered: an independently functioning central air conditioner, a central system functioning together with a local air conditioner, and a central system operating together with an adiabatic humidifier. Technological aspects of cycle performance are shown to be dependent on the acceptable design capacity of the air cooler and the adiabatic humidifier air wet-bulb temperature limit. Increasing the setting capacities of the air cooler to 0.00786 kg m⁻² s⁻¹ and the adiabatic humidifier to 0.03864 kWh, the air flow rate decreases from 0.0072 to 0.004 kg m⁻² s⁻¹, and when the setting capacities of the air cooler are 0.01011 kg m⁻² s⁻¹ and the adiabatic humidifier is 0.04831 kWh, the air flow rate decreases to a minimum limit of 0.002 kg m⁻² s⁻¹. Comparing the annual heating, cooling, and humidification load consumption without and with utilization of the second air recirculation, for the heating load 39.48 and 5.01 kWh, the costs increased by a factor of 7.9; for the cooling load 1850 and 1320 kWh, the costs increased 1.4 times; and for the moisture load 331.5 and 1245 kg m⁻² s⁻¹, the costs decreased 3.8 times. The research conducted has led to the development of a methodology that combines the justification of energy-saving modes with formulated climatic tables and a probabilistic-statistical model. This methodology facilitates the selection of subsystem equipment’s AC setting capacities, the calculation of heating, cooling, and moisture load consumption at various times, and the technological scheme for heating and humidity air treatment. The refined AC can operate at peak efficiency and reduce energy loss thanks to this iterative approach. Moreover, this method's progressive design enables it to gradually increase in efficiency over time.