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Numerical analysis and model-based control of energy recovery ventilator in HVAC system

机译:HVAC系统中能量回收呼吸机的数值分析和基于模型的控制

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In recent years, the energy conservation demand attracted much attention due to the depletion of energy resource and environmental impact by increasing energy consumption. In particular, heating, ventilation and air-conditioning (HVAC) systems in buildings is responsible for significant portion of global energy demand. Heat or energy recovery is one of the key energy-efficient technologies, which reveals to overcome the increase of energy consumption in building without reducing the indoor air quality. However, in the conventional heat recovery system, only the sensible heat was recovered, but the latent heat was ignored. In this work, a novel energy recovery ventilation (ERV) model is developed with semi-permeable membrane, and the performance of sensible and latent energy subject to tropical climate conditions is investigated by both numerical and experimental methods. The 3D ERV model is comprehensively studied first by CFD simulation for analysis of important parameters, such as velocity, temperature, humidity of supply and exhaust airflow. The CFD simulation results show that the sensible and latent effectiveness could be gained at 75% and 65% respectively. Moreover, preliminary experiment is also conducted to validate the simulation results for the impacts of ERV on energy consumption. The dynamic model of HVAC is then constructed and developed in Simulink. The model predictive control strategy for the control of temperature, humidity and CO2 level will be implemented in this model for optimization of ERV control integrated into the whole HVAC system to achieve much more energy saving.
机译:近年来,由于能源消耗的减少和能源消耗的增加对环境的影响,节能需求引起了人们的广泛关注。特别是,建筑物中的供暖,通风和空调(HVAC)系统占全球能源需求的很大一部分。热能或能源回收是关键的节能技术之一,它揭示了在不降低室内空气质量的情况下克服建筑物能耗增加的方法。但是,在传统的热回收系统中,仅回收显热,而忽略了潜热。在这项工作中,开发了一种新型的具有半透膜的能量回收通气(ERV)模型,并通过数值和实验方法研究了在热带气候条件下的显性和潜能性能。首先通过CFD仿真对3D ERV模型进行全面研究,以分析重要参数,例如速度,温度,供气湿度和排气流量。 CFD仿真结果表明,分别在75%和65%时可以获得明智和潜在的效果。此外,还进行了初步实验以验证ERV对能耗的影响的仿真结果。然后在Simulink中构建和开发HVAC的动态模型。该模型将实施用于温度,湿度和CO2水平控制的模型预测控制策略,以优化集成到整个HVAC系统中的ERV控制,以实现更多的节能效果。

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