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基于十年前后能耗调研的长沙地区既有住宅节能改造策略研究
Energy Saving Transformation Strategies of Existing Residential Buildings in Changsha Area Based on Energy Consumption Survey before and after Ten Years
【摘要】 长沙地区既有住宅节能改造存在居民改造意愿不强、节能改造效果不明显等问题。分别于2008年、2009年和2019年、2020年调研了湖南大学周边近35栋住宅的围护结构、家电情况与400余户居民终端用电量,采用K-means聚类法将总用电量、采暖、制冷、生活用电量分别进行聚类并计算界限值、平均值等参数,进而分析十年前后居民用电量变化规律,提出改善室内热环境与减少制冷能耗为该地区既有住宅节能改造的重要目标。对既有住宅用电量进行宏观情景预测,论证了既有住宅建筑围护结构节能改造的必要性,分析节能改造意愿不强的原因,结合目前改造现状提出适宜的相关策略。对同等气候区既有住宅节能改造具有一定参考价值。
【Abstract】 There are some problems in the existing residential energy saving reconstruction in Changsha area, such as residents’ weak intention and the effect of energy saving reconstruction is not obvious. This study investigated the envelope structure and household appliances of nearly 35 residential buildings around Hunan University in 2008, 2009, 2019, and 2020, respectively, as well as the terminal electricity consumption of more than 400 residential households. The K-means clustering method is used to cluster total electricity consumption, heating, cooling and domestic electricity consumption respectively. The study calculates parameters such as boundary value and average value as well. Then, the change rule of residential electricity consumption before and after ten years is analyzed. It is proposed that improving indoor thermal environment and reducing cooling energy consumption are important goals of existing residential energy saving reconstruction in this area. This paper makes macro scenario prediction of existing residential electricity consumption, demonstrates the necessity of energy saving reconstruction of existing residential building envelope, analyzes the reasons for weak intention of energy saving reconstruction, and puts forward appropriate relevant strategies based on the current reconstruction strategies. It has certain reference value for energy saving reconstruction of existing residential buildings in the same climate zone.
【Key words】 energy consumption survey; Changsha area; existing residential buildings; K-means clustering analysis; scenario prediction;
- 【文献出处】 建筑节能(中英文) ,Building Energy Efficiency , 编辑部邮箱 ,2024年01期
- 【分类号】TU111.195;TU241.91
- 【下载频次】52