Digital Twins enabled Building Automation System for comfortable, healthy and energy efficient buildings

由于欧洲人大约90%的时间都在室内度过，密闭空间的质量是欧洲健康室内环境的主要关注点，它对人们的健康、舒适和生产力有着决定性的影响。室内空气质量、热舒适性和声学舒适性以及充足的照明水平是室内环境质量（IEQ）的主要决定因素，在确保建筑居住者的生活质量和总体福祉方面发挥着重要作用。TwinBAS抓住了新修订的《建筑物能源性能指令》（EPBD）、《欧洲绿色协议》以及2019冠状病毒病（COVID-19）爆发后绿色恢复的需求所带来的及时机遇。支持向“智能”建筑的过渡，其长期目标是为居住者创造舒适、健康且节能的建筑。为了利用最近科技进步的潜在好处，建议的工作建议对第三产业建筑进行全面评估，主要基于三个支柱：(i)室内环境条件；（ii）能源表现；（iii）建筑物的智能。具体而言，Digital Twins将根据个人和协作用户的偏好，通过将真实数据处理与机器学习技术和结合物理模拟的混合模型相结合，来改善建筑空间内的IEQ。数字孪生系统将自动通知控制功能，以优化建筑操作，最大限度地提高舒适度，并在每个时间步减少能源消耗。TwinBAS将在剑桥大学（英国）工程系进行，资产管理研究小组目前正在进行扩展研究，重点是开发和利用数字双胞胎来改善资产管理。还计划在爱尔兰的综合环境解决方案研究与发展有限公司（IES R&D）借调4个月

As Europeans spend approximately 90% of their time indoors, the quality of confined spaces is a major concern for healthy indoor environments in Europe and it has a decisive impact on people's health and comfort and productivity. Indoor air quality, thermal and acoustic comfort and sufficient levels of lighting are the major determinants of the indoor environmental quality (IEQ) and play an important role in ensuring the quality of life and general wellbeing of building occupants TwinBAS seizes on the timely opportunity arising from the new revised Energy Performance of Buildings Directive (EPBD, the European Green Deal, and the need for green recovery from the COVID-19 outbreak, to support the transition towards 'smarter' buildings with a long-term objective of creating buildings that are comfortable and healthy for the occupants yet also energy efficient. In order to harness the potential benefits of recent technological advancements, the proposed work proposes a holistic assessment of tertiary sector buildings, resting on three main pillars: (i) indoor environmental conditions (ii) energy performance and (iii) the smartness of the building. Specifically, Digital Twins will be developed to improve IEQ within building spaces based on both individual and collaborative user-preferences, by using real data processing with machine learning techniques and hybrid models that combines physics-based simulations. The Digital Twins enabled system will automatically inform control functions for optimizing building operations to maximise comfort and minimize energy use at each timestep. TwinBAS will be conducted at Cambridge University (UK), Engineering Department, where the Asset Management research group is currently conducting extended research focused on the development and exploitation of digital twins to improve asset management. A secondment of 4 months is also planned at the Integrated Environmental Solutions, Research and Development Ltd. (IES R&D) in Ireland