综合气候条件下现代城市住房和传统农村住房能源性能指标的比较评估,以建立预测模型

Amitava Sarkar
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引用次数: 0

摘要

在本研究中,根据 2021 年和 2022 年的家庭能源消耗数据,对位于印度喜马偕尔邦曼迪-桑德纳加尔镇及其周边地区的传统农村和现代城市房屋的能效指数(EPI)进行了评估。EPI 作为评估不同类型建筑能效的指标,为建筑设计师和其他专业人员建立了一个实用的整体基准,以减少和优化建筑的运行能耗足迹。此外,还通过回归分析,分析了各种影响因素对每年家庭能源消耗和 EPI 的影响和相关性,从而建立预测未来家庭能源消耗模式趋势的模型。经计算,现代住宅的 EPI 平均值为 39.24 千瓦时/平方米/年(范围:29.43 - 50.53 千瓦时/平方米/年)。相比之下,传统房屋的平均 EPI 值为 7.89 千瓦时/平方米/年(范围:6.34 - 10.36 千瓦时/平方米/年)。研究表明,在研究区域内,现代住宅的年平均总能耗是传统住宅的 5.4 倍;现代住宅的平均 EPI 是传统住宅的 5 倍;现代住宅的平均 EPI/人是传统住宅的 5 倍。线性回归分析表明,建筑面积、家庭年平均收入和不同电器的总数可以很好地预测家庭年总能耗和 EPI。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
COMPARATIVE EVALUATION OF THE ENERGY PERFORMANCE INDEX OF MODERN URBAN AND TRADITIONAL RURAL HOUSING IN COMPOSITE CLIMATE FOR DEVELOPING PREDICTING MODEL
In this present study Energy Performance Index (EPI) of the traditional rural and modern urban houses located in and around Mandi – Sundernagar town at Himachal Pradesh, India, having composite climate, are assessed based on the household energy consumption data for the year 2021 and 2022. The EPI plays pivotal role as an indicator to assess the energy efficiency of different kind of buildings by setting up a practical holistic benchmark for building designers and other professionals to reduce and optimize the operating energy footprint of the building. Further, the effect and correlation of various influencing factors on the annual household energy consumption and EPI are also analyzed through regression analysis to develop models for the prediction of future trend of household energy consumption pattern. The calculated average EPI value of modern houses is found as 39.24 KWH/m²/year (range: 29.43 – 50.53 KWH/m²/year). In contrast, average EPI value of traditional houses is calculated as 7.89 KWH/m²/year (range: 6.34 – 10.36 KWH/m²/year). The study shows that the mean total annual energy consumption of modern houses is 5.4 times higher than that of the traditional houses; the mean EPI of modern houses is 5 times higher than that of the traditional houses; and the mean EPI/person of modern houses is 5 times higher than that of the traditional houses in the study area. Linear regression analysis has shown that total annual household energy consumption and EPI can be well predicted by the factors – floor area, annual average household income, and total number of different appliances.
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