New approach to determine the optimal control of fresh air systems in urban China residences
It is a critical task for sustainable development in urban China to reduce energy consumption in residences while maintaining a healthy and comfortable indoor air environment. With the popularization of fresh air systems, it becomes important to optimally control them. Previous studies usually set t...
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Veröffentlicht in: | Building and environment 2022-01, Vol.207, p.108538, Article 108538 |
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Sprache: | eng |
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Zusammenfassung: | It is a critical task for sustainable development in urban China to reduce energy consumption in residences while maintaining a healthy and comfortable indoor air environment. With the popularization of fresh air systems, it becomes important to optimally control them. Previous studies usually set the control strategies first, and then evaluate the resulting indoor air quality and energy consumption. A control strategy for a fresh air system that yields acceptable indoor air quality with minimum energy consumption, that is “optimal control,” has not yet been identified. In this study, we developed an inverse problem approach using a variation method to solve this problem. For multiple target indoor pollutants, the principle of the optimal control strategy was to ensure the max [Ci,in/Ci, st ] = 1 (i = 1,2, …m), where Ci,in and Ci,st are the concentrations of indoor air pollutant i and the corresponding threshold in the standard. As an illustrative example, we compared our optimal control strategy to the traditional constant air flow rate strategy in a Beijing reference bedroom. The optimal control strategy guaranteed acceptable indoor air quality during hazy days while the traditional strategy did not. Moreover, the optimal strategy can be projected to save 8.7% annual energy consumption and 15% of the operation cost.
•We present an inverse problem approach to determine optimal control of fresh air systems.•This strategy yields acceptable indoor air quality with minimum energy consumption.•The non-steady condition and time-averaged concentration standards are considered.•An example shows that the optimal strategy saves 8.7% annual energy consumption. |
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ISSN: | 0360-1323 1873-684X |
DOI: | 10.1016/j.buildenv.2021.108538 |