Residential energy consumption and conservation

Abstract

a b s t r a c tThe Swedish energy performance certificates for single-family housing provide rich information on energy consumption and various physical attributes. They also include estimates of the energy conservation potentials resulting from implementing cost-efficient energy saving measures. By matching the certificates issued for single-family houses in 2009 and 2010, with socio-economic data about the residents, local climate data and information about recent improvements of the building we have created a unique database, which can be used to explore a wide variety of questions related to energy consumption and conservation.One aim of this paper is to assess the role for energy consumption played by socio-economic characteristics of the residents as compared to physical attributes of the house. Another is to estimate the influence of housing attributes and climate on the "engineering estimates" of the conservation potentials.Our results show that while the quantitative impact of physical attributes dominate the energy use for heating and cooling, the opposite holds for household electricity. The assessed conservation potential, amounting to 15% of the energy consumption, is significantly related to both the housing attributes and the use of energy. The results also indicate a need to improve the information provided by the performance certificates.

Characterisation of domestic hot water end-uses for integrated urban thermal energy assessment and optimisation

“…In case measured data are not available, the total heat consumption can be conveniently determined using multiple regression analysis out of a sample of measured consumption data. Multiple linear regression is one of the dierent techniques available to predict the energy consumption of buildings based on measured consumption data as well as a series of predictors and has been used by several authors (Guerra Santin et al [29], Howard et al [30], Mastrucci et al [31], Wahlstrom and Harsman [32], Schueler et al [33]). Compared to other techniques, linear regression is particularly promising for this goal due to reasonable accuracy and relatively simple implementation (Fumo and Biswas [34]).…”

城市居民低碳行为认知失调的成因——“知识—行为”的双中介模型

“…而， 2018 年 《公民环保行为调查报告》 [2] 却显示： 仅有 55%左右的居民实施了低碳行为。这种认知与行为 的 "缺口" 成为推进绿色低碳生活方式的障碍之 一。是什么原因导致了这种居民低碳行为上的认 知失调？如何减少这种认知失调就成为亟待解决 的问题。 居民低碳行为的认知失调是指在低碳消费上 认知、 态度等和实际行为的不一致。Festinger 的认 知失调理论 [3] 指出： 当人们对事物的态度与实际行 为不一致时的状态是认知失调， 认知失调会产生焦 虑， 在没有外部诱因和行为可控的情况下， 个体会 通过改变态度或改变行为等途径减少失调。但是， 个体减少认识失调的倾向取决于导致失调因素的 重要性。学者们尝试从行为感知 [4] 、 从众心理 [5] 、 环 境关注 [6] 、 自我调节倾向 [7] 等方面分析绿色消费中的 认知失调。但是， 这些研究无法解释为什么宣传教 育促进了居民低碳意识的提高， 却没有带来实际行 为的同步改善？ "知识-态度-行为" 理论 [8] 认为知识是形成态 度的前因， 并通过态度驱动实践行为。Gyberg 等 [9] 的 研究发现， 由于缺乏充分的知识， 即使居民具有环保 意识， 却未必能有效落实到实际行为上； Jasmin 等 [10] 收稿日期： 2018-11-05 修订日期： 2018-12- 16 基金项目： 中国矿业大学双一流建设文化传承专项 "能源矿业经济智库" 项目 (2018WHCC01) 。 [17][18][19][20] 、 人口特征因素 [21][22][23][24] 、 家庭特征因素 [16,[25][26][27] ， 以 及外部情境因素 [28][29][30][31] 等 4 个方面。虽然少数研究中 也提及了环保知识对低碳行为的作用， 然而在知识 作用上却存在较大争议。一类观点认为知识对行 为具有显著促进作用 [22,[32][33][34][35][36][37] ； 另一类观点则认为知识 对行为的作用不显著 [13,19,[38][39][40][41]…”

Impact of the Surrounding Built Environment on Energy Consumption in Mixed-Use Building

“…Despite these difficulties, previous researchers have developed various modeling techniques for identifying residential sector energy consumption and finding effective energy conservation strategies. One of the dominant approaches in those studies has been a disaggregated method used to investigate the impact of different housing attributes and household characteristics on the energy consumption of a residential building unit using statistical or engineering techniques [4,5]. These studies have found that the insulation of walls, roofs or windows [6,7], the shape of buildings [8] and household characteristics, such as number of family members or income [9][10][11] were significantly associated with residential energy consumption.…”

“…These non-residential building studies have examined the energy consumption of religious facilities [12], bank [13], public buildings [14] and commercial buildings [15,16] and building attributes associated with energy consumption. While the energy consumption intensities of these buildings varied based upon their structural features, the occupants' characteristics and attitude, the weather conditions and the study's context [4,[17][18][19][20], studies of building energy consumption, commonly, have defined a specific building use of interest and analyzed the associations between building attributes and energy consumption using statistical or engineering techniques.…”