A new method for household energy use modeling: A questionnaire-based approach
A new method for household energy use modeling: A questionnaire-based approach
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DOI：
10.1016/j.enbuild.2017.12.032
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发表时间：
2018-03-01
影响因子：
6.7
通讯作者：
Yoshida, Yoshikuni
中科院分区：
文献类型：
--
作者：
Ozawa, Akito;Kudoh, Yuki;Yoshida, Yoshikuni
日本需要提高住宅能源效率以减少能源消耗，从而实现温室气体（GHG）减排目标。了解家庭行为和能源使用的差异对于评估节能措施的效果非常重要。在这项研究中，作者提出了一种基于家电和热水使用问卷调查的家庭能源使用建模新方法。根据调查结果获得不同季节、家庭结构和生活方式的15分钟居民用电和热力需求曲线，并与现有统计数据进行比较。使用计算的能源需求来评估冰箱、电视和照明对住宅节电、净现值 (NPV) 和温室气体减排的替代影响。考虑不同家庭结构变化情景下家庭能源使用的变化，并基于蒙特卡罗方法进行不确定性分析。结果表明，购买新冰箱可以减少温室气体排放，在客厅/餐厅安装 LED 灯可以减少电费。研究还发现，由于不同家庭看电视的时间长短不同，更换电视后的 NPV 和 GHG 减排量存在很大的不确定性。 (C) 2017 Elsevier B.V. 保留所有权利。
Japan needs to improve its residential energy efficiency to reduce energy consumption and thus achieve its greenhouse gas (GHG) emissions reduction targets. Understanding the differences in household behavior and energy use is important to evaluate the effect of energy conservation measures. In this study, the authors propose a new method for household energy use modeling based on questionnaire surveys on home appliances and hot water use. Fifteen-minute residential electricity and heat demand profiles with different seasons, household structures and lifestyles are obtained from the survey results, and compared with available statistical data. The replacement effects of refrigerators, TVs and lighting on residential electricity savings, net present value (NPV) and GHG reductions are evaluated using calculated energy demand. Variations in household energy use are considered under different change scenarios in household structure and by conducting an uncertainty analysis based on the Monte Carlo method. The results indicate that GHG emissions can be reduced by purchasing a new refrigerator, and electricity costs can be reduced by installing LED lamps in the living/dining room. It is also found that there is a wide range of uncertainty for NPV and GHG reductions after replacing a TV because different households watch TV for different lengths of time. (C) 2017 Elsevier B.V. All rights reserved.