现有建筑结构的环境和社会监测——若干历史建筑案例研究的结果

A. Redlein, L. Thrainer
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引用次数: 1

摘要

一年前,欧盟制定了环境、社会和治理(ESG)指令,以促进对可持续性的投资。本指令要求能源监测/优化和行动,以促进人类福祉。为了满足这一需求,特别是欧洲的历史建筑需要在这些方面解决方案,以提高能源效率,同时保障其用户的福祉。这些建筑物几乎没有安装楼宇自动化设备。因此,识别高能耗消费者的基本前提是无法获得有效的使用数据。为此,必须回答以下研究问题:哪些数据是达到环境和社会目标所必需的?如何以有效和有效的方式捕获数据?如何提供数据以优化能源使用和福祉?为了回答这些问题,我们进行了文献研究,以确定相关参数。首先,根据该步骤的结果和先前的混合方法研究项目,定义了相关的工具和IT体系结构。其次,根据esg报告需求,定义数据结构和相关构建结构。第三,进行了案例研究,该研究基于先前定义的IT架构,使用物联网测量设备,两个不同的数据库和两种分析工具。因此,本文根据案例研究的用户互动和反馈,提出了对数据库和分析工具的最终决策。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Environmental and Social monitoring in existing building structures – results of a case study within several historical buildings
One year ago the European Union defined the Environmental, Social and Governance (ESG) directive to foster investment in sustainability. This directive asks for energy monitoring / optimization and actions to foster human well-being. To cover that demand especially historical buildings in Europe need solutions in these respects, to be more energy efficient and at the same time to safeguard the well-being of its users. These buildings have almost no building automation installed. So, the basic prerequisite to identify high energy consumers valid usage data is not available. For that, the following research questions have to be answered: Which data is necessary to reach both, the environmental and social goals? How can data be captured in a valid and efficient way? How can data be made available to optimize energy usage and well-being? To answer these questions, a literature research was executed to define the relevant parameters. Firstly, based on the results of that step and a previous mixed-methods-research project, the relevant tools and the IT architecture were defined. Secondly, based on the ESG-reporting demands, data structure and relevant building structures were defined. Thirdly, a case study was conducted, which is based on the previously defined IT architecture, using IoT measuring devices, two different databases and two analytic tools. As a result, this paper presents the final decision on the database and the analytics tool, based on the users’ interaction and feedback of the case study.
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