Zhihong Pang, Xing Lu, Pingfan Hu, Zheng O’Neill, Qingsheng Wang
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SIREN – smart ventilation for infection risk mitigation and HVAC energy efficiency: a case study amid the COVID-19 pandemic
The COVID-19 pandemic has underscored the need for effective ventilation control in public buildings. This study develops and evaluates a smart ventilation control algorithm (SIREN) that dynamically adjusts zone and system-level HVAC operation to maintain an acceptable COVID-19 infection risk and HVAC energy efficiency. SIREN uses real-time building operation data and Trim & Respond control logic to determine zone primary and system outdoor airflow rates. An EnergyPlus and CONTAM co-simulation framework was developed to assess its performance across various control scenarios and US climate zones. Results show that SIREN can flexibly control infection risk within a customized threshold (e.g. 3%) for every zone, while traditional controls cannot. At the building level, SIREN’s HVAC energy consumption is comparable to a fixed 70% outdoor airflow fraction scenario, while its infection risk is lower than the 100% outdoor airflow scenario, illustrating its potential for safe and energy-efficient HVAC operation during pandemics.
期刊介绍:
The Journal of Building Performance Simulation (JBPS) aims to make a substantial and lasting contribution to the international building community by supporting our authors and the high-quality, original research they submit. The journal also offers a forum for original review papers and researched case studies
We welcome building performance simulation contributions that explore the following topics related to buildings and communities:
-Theoretical aspects related to modelling and simulating the physical processes (thermal, air flow, moisture, lighting, acoustics).
-Theoretical aspects related to modelling and simulating conventional and innovative energy conversion, storage, distribution, and control systems.
-Theoretical aspects related to occupants, weather data, and other boundary conditions.
-Methods and algorithms for optimizing the performance of buildings and communities and the systems which service them, including interaction with the electrical grid.
-Uncertainty, sensitivity analysis, and calibration.
-Methods and algorithms for validating models and for verifying solution methods and tools.
-Development and validation of controls-oriented models that are appropriate for model predictive control and/or automated fault detection and diagnostics.
-Techniques for educating and training tool users.
-Software development techniques and interoperability issues with direct applicability to building performance simulation.
-Case studies involving the application of building performance simulation for any stage of the design, construction, commissioning, operation, or management of buildings and the systems which service them are welcomed if they include validation or aspects that make a novel contribution to the knowledge base.