Multi-objective optimal control of multi-zone VAV systems for adaptive switching between normal and pandemic modes
李炳绪，王盛卫
摘要：
The recent COVID-19 pandemic has highlighted the need to adapt the control of building HVAC systems to limit disease transmission in indoor environments. However, such operational adjustments may significantly increase energy use, creating a complex trade-off problem between infection risk mitigation and energy efficiency. Moreover, practical constraints, such as maintaining comfortable temperature and humidity levels for occupants and limited system equipment capacity, can limit the flexibility of operational adjustments, further exacerbating the challenge of finding optimal operational solutions. This paper therefore proposes an optimal control strategy for multi-zone VAV systems that adapts to switching between normal and pandemic modes. The strategy considers dual optimization objectives: minimizing system energy use and disease transmission risk, while also considering all practical constraints. Optimal operational parameters can be determined to achieve the best trade-off between these objectives based on pandemic conditions. Additionally, a new metric called “effective fresh air factor” is proposed to quantify the impact of multi-zone VAV systems on disease transmission in building zones. The effectiveness of the proposed strategy is evaluated in a simulated building and air-conditioning environment. Results show that the VAV system has superior ability to reduce transmission risk through operational adjustments, achieving a decrease in disease transmission risk by 25% to 75% compared to normal operation.
论文绘图：
Fig. 1. Outline of the proposed optimal control strategy.
Fig. 3. Illustration of the Pareto optimal set and relationships between objective A and B.
Fig. 8. Results of system energy consumption and EFAF values with different supply air temperature and different fresh air ratios.
Fig. 13. Maximum infection risk reduction (MIRR) which can be achieved by VAV systems under different indoor load conditions and different outdoor weather.
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