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Analysis of Georeferenced Building Data for the Identification and Evaluation of Thermal Microgrids

机译:用于热微电网识别和评估的地理参考建筑数据分析

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Retrofitting the existing building stock is among the most important objectives and imperative to meet societal goals to reduce primary energy demand and anthropogenic greenhouse gas emissions. District heating systems have proven to supply heat for buildings both energy and cost efficiently. Thermal microgrids (TMGs) can be understood as a subcategory of district heating systems: small scale, bidirectional, and potentially fed by different thermal sources. Given a suitable combination of loads, the number of and distance between buildings, they can offer economic and environmental advantages compared to the supply by individual heating systems per building. We present a novel method using data analysis techniques on georeferenced building stock data to identify suitable configurations of buildings that yield a cost-efficient TMG. For the identification, both semantic and spatial data from a database are combined using fuzzy logics and cost-benefit analysis. We apply the method using a case study featuring a database of 306 buildings potentially to be retrofitted. As a result, we can identify nine groups of 25 buildings that would form a microgrid featuring up to 17.4% cost benefits compared to an individual heat supply. This would save approximately 30% of the building-induced CO emission of the community.
机译:改造现有建筑群是最重要的目标之一,也是实现减少一次能源需求和人为温室气体排放的社会目标的当务之急。事实证明,区域供暖系统可为建筑物提供能源和成本效益。热微电网(TMG)可以理解为区域供热系统的一个子类别:小规模,双向且可能由不同的热源供热。给定负载,建筑物的数量和建筑物之间的距离的适当组合,与每个建筑物的单个供暖系统的供电相比,它们可以提供经济和环境优势。我们提出了一种对地理参考建筑存量数据使用数据分析技术的新颖方法,以确定可产生具有成本效益的TMG的建筑物的合适配置。为了进行识别,使用模糊逻辑和成本效益分析将来自数据库的语义和空间数据进行组合。我们通过案例研究应用该方法,该案例研究包含可能要改造的306座建筑物的数据库。结果,我们可以识别出九组,每组25座建筑物,这些建筑物将构成一个微电网,与单个供热系统相比,微电网的成本效益高达17.4%。这将节省大约30%的建筑引起的社区CO排放。

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