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Understanding usage patterns of electric kettle and energy saving potential

机译:了解电热水壶的使用方式和节能潜力

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摘要

The availability of smart metering and smart appliances enables detecting and characterising appliance use in a household, quantifying energy savings through efficient appliance use and predicting appliance-specific demand from load measurements is possible. With growing electric kettle ownership and usage, lack of any efficiency labelling guidelines for the kettle, slow technological progress in improving kettle efficiency relative to other domestic appliances, and current consumer attitudes, urgent investigation into consumer kettle usage patterns is warranted. From an efficiency point of view, little can be done about the kettle, which is more efficient than other methods of heating water such as the stove top kettle. However, since a majority households use the kettle inefficiently by overfilling, in order to meet energy targets, it is imperative to quantify inefficient usage and predict demand. For the purposes of scalability, we propose tools that depend only on load measurement data for quantifying and visualising kettle usage and energy consumption, assessing energy wastage through overfilling via our proposed electric kettle model, and predicting kettle-specific demand, from which we can estimate potential energy savings in a household and across a housing stock. This is demonstrated using data from a longitudinal study across a sample of 14 UK households for a two-year period.(1) (C) 2016 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http:// Ereativecommons.orgilicenses/by/4.0/).
机译:智能电表和智能设备的可用性可以检测和表征家庭中的设备使用情况,通过高效使用设备来量化节能量,并可以通过负载测量预测特定于设备的需求。随着电水壶拥有量和使用量的增长,水壶的效率标签指南缺乏,相对于其他家用电器而言,提高水壶效率的技术进步缓慢以及当前的消费者态度,有必要对消费者水壶的使用方式进行紧急调查。从效率的角度来看,水壶几乎没有什么可做的,比其他加热水的方法(例如炉灶水壶)更有效。然而,由于大多数家庭为了满足能源目标而通过过量填充来低效地使用水壶,因此必须量化低效的使用并预测需求。为了实现可扩展性,我们提出了仅依赖于负载测量数据的工具,以量化和可视化水壶的使用和能耗,通过我们建议的电水壶模型通过过量填充评估能源浪费,并预测水壶的特定需求,由此我们可以估算一个家庭和整个房屋的潜在节能量。使用一项针对14个英国家庭的样本进行为期两年的纵向研究得出的数据可以证明这一点。(1)(C)2016 The Authors。由Elsevier Ltd.发布。这是CC BY许可下的开放获取文章(http://Ereativecommons.orgilicenses/by/4.0/)。

著录项

  • 来源
    《Applied Energy》 |2016年第1期|231-242|共12页
  • 作者单位

    Univ Strathclyde, Dept Elect & Elect Engn, 204 George St, Glasgow G1 1XW, Lanark, Scotland;

    Univ Strathclyde, Dept Elect & Elect Engn, 204 George St, Glasgow G1 1XW, Lanark, Scotland;

    Univ Strathclyde, Dept Elect & Elect Engn, 204 George St, Glasgow G1 1XW, Lanark, Scotland;

    Univ Strathclyde, Dept Elect & Elect Engn, 204 George St, Glasgow G1 1XW, Lanark, Scotland;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Appliance modelling; Appliance use prediction; Energy savings;

    机译:设备建模;设备使用预测;节能;
  • 入库时间 2022-08-18 00:08:14

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