Data-Driven Co-optimization of Energy Efficiency and Indoor Environmental Quality in Commercial Buildings

S. A. R. Naqvi, V. Chandan, S. Bhattacharya, Na Luo, K. Kar, C. Sivaraman, Nikitha Radhakrishnan
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Abstract

In this paper, we use publicly available data of a highly instrumented office building to estimate how zonal temperature and carbon dioxide (CO2) concentration are related to some key operational and environmental measurements. Subsequently, we have developed, simulated, and evaluated an optimization framework for minimizing the energy consumption of the central heating, ventilation and air conditioning (HVAC) unit while meeting zonal temperature and indoor air quality (IAQ) standards. Finally, we have evaluated the achievable energy savings for our proposed approach as compared to a baseline approach and reported significant savings potential.
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数据驱动的商业建筑能效与室内环境质量协同优化
在本文中,我们使用一个高度仪器化的办公大楼的公开数据来估计区域温度和二氧化碳(CO2)浓度如何与一些关键的操作和环境测量相关联。随后,我们开发、模拟和评估了一个优化框架,以最大限度地减少中央供暖、通风和空调(HVAC)单元的能耗,同时满足区域温度和室内空气质量(IAQ)标准。最后,与基线方法相比,我们已经评估了我们提出的方法可实现的节能效果,并报告了显著的节能潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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