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The structuring of air source heat pumps’ prices in a retrofitting residential buildings market: what did I pay for?

机译:在改造后的住宅建筑市场中构建空气源热泵的价格:我要付多少钱?

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The recent European energy proposals for the revision of the Energy Efficiency and the Energy Performance of Buildings Directives emphasize the importance to drive investments into the renovation of building stocks and to stimulate the refurbishment demand. Moreover, the challenge of acquiring data about retrofitting is reasserted because the lack of reliable data is detrimental to the perception of cost-effectiveness. Especially it is well known that refurbishment prices are, according to various papers, subject to large uncertainty and can sometimes be controversial even if public subsidies are available.In this paper, we evaluate the main determinants of prices. Their structuring is a complex phenomenon blending technical, economical and organizational sides. For such purpose, we analyzed hundreds of invoices concerning the installation of heat pumps in existing buildings.In order to model the influence of the different variables on the up-front cost paid by the households, we developed general linear statistical models (ANCOVA) blending qualitative and quantitative variables. The variables taken into account are:1. Technical: living area, type of building (multi or single family), coefficient of performance, installed power;2. and economic: company description (number of employees, main activity and sales network), average household’s income linked to location, brand of equipment installed.Our results confirm the importance of economic variables (such as brand or sales network) beside the technical variables in the explanation of prices. Our results also quantify the relative role of each variable. Half of the prices’ variation is explained by the models and it is a huge step in the understanding of retrofit prices in order to better orientate the public subsidies.
机译:欧洲最近提出的有关修订《建筑物能效和能效指令》的能源提案,强调了推动投资进行建筑存量翻新和刺激翻新需求的重要性。此外,由于缺乏可靠的数据不利于人们了解成本效益,因此重新获得了有关改造的数据的挑战。特别是,众所周知,根据各种论文,翻新价格存在很大的不确定性,即使有公共补贴,翻新价格有时也会引起争议。 在本文中,我们评估了价格的主要决定因素。他们的结构是一个复杂的现象,融合了技术,经济和组织方面。为此,我们分析了数百张有关在现有建筑物中安装热泵的发票。 为了模拟不同变量对家庭支付的前期成本的影响,我们开发了混合定性和定量变量的通用线性统计模型(ANCOVA)。考虑的变量是: 1。 技术方面:居住面积,建筑物类型(多户或单户),性能系数,装机功率; 2。 经济:公司说明(员工人数,主要活动和销售网络),与位置相关的平均家庭收入,所安装设备的品牌。 我们的结果证实了在解释价格时,除了技术变量之外,经济变量(例如品牌或销售网络)的重要性。我们的结果还量化了每个变量的相对作用。这些模型解释了一半的价格变动,这是对改造价格的理解迈出的一大步,以便更好地确定公共补贴的方向。

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