4.7 Article

Electricity consumption and household characteristics: Implications for census-taking in a smart metered future

期刊

COMPUTERS ENVIRONMENT AND URBAN SYSTEMS
卷 63, 期 -, 页码 58-67

出版社

ELSEVIER SCI LTD
DOI: 10.1016/j.compenvurbsys.2016.06.003

关键词

Census; Smart meter; Transactional data; Big data; Households

资金

  1. EPSRC [EP/J017698/1] Funding Source: UKRI
  2. ESRC [ES/L00318X/1] Funding Source: UKRI
  3. Economic and Social Research Council [ES/L00318X/1] Funding Source: researchfish
  4. Engineering and Physical Sciences Research Council [EP/J017698/1] Funding Source: researchfish

向作者/读者索取更多资源

This paper assesses the feasibility of determining key household characteristics based on temporal load profiles of household electricity demand. It is known that household characteristics, behaviours and routines drive a number of features of household electricity loads in ways which are currently not fully understood. The roll out of domestic smart meters in the UK and elsewhere could enable better understanding through the collection of high temporal resolution electricity monitoring data at the household level. Such data affords tremendous potential to invert the established relationship between household characteristics and temporal load profiles. Rather than use household characteristics as a predictor of loads, observed electricity load profiles, or indicators based on them, could instead be used to impute household characteristics. These micro level imputed characteristics could then be aggregated at the small area level to produce 'census-like' small area indicators. This work briefly reviews the nature of current and future census taking in the UK before outlining the household characteristics that are to be found in the UK census and which are also known to influence electricity load profiles. It then presents descriptive analysis of a large scale smart meter-like dataset of half-hourly domestic electricity consumption before reviewing the correlation between household attributes and electricity load profiles. The paper then reports the results of multilevel model-based analysis of these relationships. The work concludes that a number of household characteristics of the kind to be found in UK census-derived small area statistics may be predicted from particular load profile indicators. A discussion of the steps required to test and validate this approach and the wider implications for census taking is also provided. (C) 2016 The Authors. Published by Elsevier Ltd.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据