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A bottom-up spatially explicit methodology to estimate the space heating demand of the building stock at regional scale

机译:一种自下而上的空间显式方法,用于估算区域规模的建筑用地的空间供热需求

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The paper presents a spatially explicit and "bottom-up" methodology for the building stock analysis of the residential sector. It integrates different input data in a Geographical Information System (GIS), without using the "archetypes approach" and simulation tools. In particular, the energy balance at the building level (BL) for the whole Valle d'Aosta region (Italy) is addressed, using the Italian Ministerial Decree 26/06/2009 and the UNI/TS 11300-1:2014 standard. Main outputs are the estimation of the geo-referenced heating demand of the residential buildings for the case study area (almost 42,000 buildings), and the development of a methodology that can be applied at different scales. The application of the methodology to the case study slightly overestimates the total thermal demand of the residential building stock, especially referring to the more energy demanding buildings. However, being the method influenced by data availability, the quality is expected to improve with newly available data. The proposed GIS-based methodology is designed to be part of a broader Spatial Decision Support System (SDSS) for sustainable energy plans that integrate renewable sources in the building stock energy renovation. (C) 2019 The Authors. Published by Elsevier B.V.
机译:本文提出了一种空间明确的“自下而上”的方法,用于住宅部门的建筑存量分析。它将不同的输入数据集成到地理信息系统(GIS)中,而无需使用“原型方法”和模拟工具。特别是,通过意大利部长令26/06/2009和UNI / TS 11300-1:2014标准解决了整个瓦莱达奥斯塔地区(意大利)在建筑物级别(BL)的能量平衡问题。主要输出是对案例研究区域(将近42,000栋建筑物)的住宅建筑物的地理参考供暖需求进行估算,并开发可在不同规模下应用的方法。该方法在案例研究中的应用略微高估了住宅建筑群的总热需求,尤其是对能源需求更高的建筑。但是,由于该方法受数据可用性的影响,因此随着新获得的数据质量有望提高。提议的基于GIS的方法被设计为更广泛的空间决策支持系统(SDSS)的一部分,用于可持续能源计划,该计划将可再生能源整合到建筑节能中。 (C)2019作者。由Elsevier B.V.发布

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