Understanding usage patterns of electric kettle and energy saving potential
Understanding usage patterns of electric kettle and energy saving potential
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DOI：
10.1016/j.apenergy.2016.03.038
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发表时间：
2016-06-01
期刊：
影响因子：
11.2
通讯作者：
Stankovic, V.
中科院分区：
文献类型：
--
作者：
Murray, D. M.;Liao, J.;Stankovic, V.
智能计量和智能电器的可用性使得能够检测和表征家庭中的电器使用，通过有效的电器使用来量化节能，以及根据负载测量来预测电器特定的需求是可能的。随着电水壶拥有量和使用量的增加，缺乏任何关于电水壶效率标签的指导方针，相对于其他家用电器，提高电水壶效率的技术进展缓慢，以及目前的消费者态度，有必要对消费者电水壶的使用模式进行紧急调查。从效率的角度来看，水壶几乎没有什么可以做的，它比其他加热水的方法（如炉顶水壶）更有效。然而，由于大多数家庭通过过度填充而低效地使用水壶，为了实现能源目标，必须量化低效使用并预测需求。出于可扩展性的目的，我们提出了仅依赖于负载测量数据的工具，用于量化和可视化水壶的使用和能源消耗，通过我们提出的电热水壶模型通过过度填充来评估能源浪费，并预测水壶特定的需求，从中我们可以估计家庭和整个住房存量的潜在能源节约。这是证明使用的数据，在一个样本的14个英国家庭的一个为期两年的纵向研究。(1)2016年，作者。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/）。
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/).