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A model-based dynamic optimization strategy for control of indoor air pollutants

机译:一种基于模型的动态优化策略,用于控制室内空气污染物

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The American Society for Heating, Refrigeration, and Air Conditioning Engineers (ASHARE) prescribes fixed ventilation rates for the operation of heating, ventilation, and air conditioning (HVAC) systems, which is sub-optimal in terms of controlling indoor air pollutants and energy consumption. This paper relies on a physics-based model of a residential house to predict the concentrations of indoor pollutants such as ozone, formaldehyde (HCHO), and particulate matter (PM) as function of time, outdoor conditions, and indoor emissions. The model captures real-world scenarios such as pollutants entering the house from ambient air through an air handling unit (AHU) and pollutants emitted in the house. A dynamic optimization problem is then formulated and solved to calculate the optimal ventilation rate at each time instant, that minimizes the total energy consumption, while maintaining the indoor pollutant concentrations below or as close as possible to their respective acceptable thresholds. For the considered example day, operation under optimized conditions reduces the peak pollutant concentration by 31%, time of exposure to undesirable concentrations by 48%, and energy consumption of the AHU by 17.7%. (C) 2019 Elsevier B.V. All rights reserved.
机译:美国加热,制冷和空调工程师(ASHARE)规定了用于运行供暖,通风和空调(HVAC)系统的固定通风率,这在控制室内空气污染物和能量消耗方面是次优。本文依赖于住宅房屋的物理学模型,以预测室内污染物如臭氧,甲醛(HCHO)和颗粒物(PM)的浓度,如时间,室外条件和室内排放的函数。该模型捕获了现实世界的情景,如污染物通过空气处理单元(AHU)和房屋排放的污染物从环境空气进入房屋。然后制定动态优化问题并解决以计算每次瞬间的最佳通风率,这最小化总能量消耗,同时保持下面的室内污染物浓度或尽可能接近它们各自可接受的阈值。对于所考虑的实施例日,优化条件下的操作将峰值污染物浓度降低31%,暴露于不希望的浓度的时间48%,并且ahu的能量消耗17.7%。 (c)2019 Elsevier B.v.保留所有权利。

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