Smart Energy Research Lab

智慧能源研究实验室

• 批准号: EP/P032761/1
• 负责人: Tadj Oreszczyn
• 金额: $ 756.73万
• 依托单位: University College London
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2017
• 资助国家: 英国
• 起止时间: 2017 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FP032761%2F1
• 关键词: Smart; Energy; Research; Lab

The UK is investing £11 billion installing 53 million smart electricity and gas meters in domestic and small non-domestic properties by 2020. The ability to access reliable, high-resolution gas and electricity energy data at a national scale has the potential to revolutionise research into how we use energy in our buildings. Currently the best available domestic energy data is estimated annual consumption from infrequent and often estimated meter readings by utilities. This data has, over the last five years, been used by researchers and government to help assess the effectiveness of energy efficient technologies and help plan for a low carbon energy system. The introduction of smart meters offers the potential to examine more reliable gas and electricity data collected at least every half hour which offers great opportunities for researchers. It can help develop better methods of disaggregating energy use by appliance; produce more reliable energy labels at lower costs; help identify fuel-poor households; facilitate demand side response to help balance the electricity grid; help identify the most appropriate energy efficiency measures for a property; produce new products and services for consumers; and develop more appropriate policies for government. One of the strengths of the UK Smart Meter programme is that energy consumers own their own data. This means that nobody, not even utilities, will automatically get access to all smart meter data, and nobody will store everybody's half hourly data. Only if consent is provided by home owners can half hourly data be accessed, and then only via a highly secure gateway. While this appropriately prioritises customers' rights and security, it means that it will be much more difficult for individual researchers to access future energy data. This proposal is to provide the UK research community with a shared SMART METER RESEARCH PORTAL (SMRP) to access smart meter data (thereby saving considerable time and money) and to establish a world leading research programme using the this data. This research will be facilitated by linking smart meter data to data collected as part of national surveys, field trials, or administrative data within the highly secure UK Data Archive. For example, the UK has an annual English Housing Survey which collects information about the size and theoretical energy efficiency of buildings as well as information about the occupants. Attaching a consent form to this, would allow theoretical energy use to be linked to actual energy use, which in turn would provide the potential to improve energy models such as the National Household Model. Without a shared portal academics and government would need to build their own mechanism of accessing smart meter data at an estimated cost of £1-2m to meet the security and ethical requirements. This would prevent smaller projects, such as a few hundred house field trail of a new energy efficient technology, from being undertaken. This is because, they would have to install their own meters or read meters manually, making such projects more costly and difficult to recruit participants. In addition, many projects would double the time required for monitoring. Smart meters store data from the previous 13 months, this means that a project assessing the impact of a heating technology does not need to monitor energy use prior to the installation of the new technology. Thereby potentially saving a year of time for many research projects. This means that once the portal has been built and demonstrated to work efficiently via a sample of research projects. The relatively low future annual running costs (£300-400k) can be met by individual research projects being charged a fixed cost for the SMRP service of obtaining, linking and pre-processing data in a secure and ethical way, thereby allowing academics to focus on their research.

英国将投资110亿英镑，到2020年在国内和小型非住宅物业安装5300万个智能电表和燃气表。在全国范围内访问可靠、高分辨率的天然气和电力能源数据的能力，有可能彻底改变我们如何在建筑物中使用能源的研究。目前，最好的国内能源数据是根据公用事业不经常和经常估计的仪表读数估计的年度消费量。在过去的五年里，这些数据被研究人员和政府用来帮助评估节能技术的有效性，并帮助规划低碳能源系统。智能电表的引入提供了检查至少每半小时收集一次的更可靠的天然气和电力数据的可能性，这为研究人员提供了很好的机会。它可以帮助制定更好的方法，按电器分列能源使用情况;以较低的成本制作更可靠的能源标签;帮助确定燃料不足的家庭;促进需求方的反应，以帮助平衡电网;帮助确定最适合房地产的能源效率措施;为消费者提供新的产品和服务;为政府制定更适当的政策。英国智能电表计划的优势之一是能源消费者拥有自己的数据。这意味着没有人，甚至公用事业，将自动访问所有智能电表数据，没有人会存储每个人的半小时数据。只有在房主同意的情况下，才能每半小时访问一次数据，而且只能通过高度安全的网关访问。虽然这适当地优先考虑了客户的权利和安全，但这意味着个人研究人员访问未来的能源数据将更加困难。该提案旨在为英国研究界提供一个共享的智能电表研究门户（SMRP），以访问智能电表数据（从而节省大量时间和金钱），并使用该数据建立世界领先的研究计划。这项研究将通过将智能电表数据与作为国家调查，现场试验或高度安全的英国数据档案中的行政数据的一部分收集的数据相关联来促进。例如，英国每年进行一次英国住房调查，收集有关建筑物的大小和理论能源效率的信息以及有关居住者的信息。附上同意书，将使理论能源使用与实际能源使用相联系，这反过来又有可能改进全国家庭模式等能源模式。如果没有共享门户，学术界和政府将需要建立自己的机制来访问智能电表数据，估计成本为100万至200万英镑，以满足安全和道德要求。这将阻止较小的项目，如几百个房屋实地试验的新能源效率技术，正在进行。这是因为，他们将不得不安装自己的仪表或手动读取仪表，使这些项目更加昂贵，难以招募参与者。此外，许多项目将使监测所需时间增加一倍。智能电表存储过去13个月的数据，这意味着评估供暖技术影响的项目在安装新技术之前不需要监测能源使用情况。从而可能为许多研究项目节省一年的时间。这意味着，一旦门户网站已经建成，并通过一个研究项目的样本证明有效地工作。相对较低的未来年度运行成本（30万至40万英镑）可以通过对SMRP服务收取固定成本来满足，SMRP服务以安全和道德的方式获取，链接和预处理数据，从而使学者专注于他们的研究。

项目成果

Covid-19 lockdown: impacts on GB electricity demand and CO₂ emissions

Covid-19 封锁：对英国电力需求和 CO₂ 排放的影响

• DOI: 10.5334/bc.77
• 发表时间: 2021
• 期刊: Buildings and Cities
• 作者: Anderson B

Perspectives of Welsh social landlords on smart meter data research for assessing benefits of energy efficient housing improvements (pre-print)

威尔士社会房东对智能电表数据研究的看法，用于评估节能住房改善的效益（预印本）

• 发表时间: 2022
• 作者: Gupta, B.

Self-reported energy use behaviour changed significantly during the cost-of-living crisis in winter 2022/23: Insights from cross-sectional and longitudinal surveys in Great Britain

自我报告的能源使用行为在 2022/23 年冬季生活成本危机期间发生了显着变化：来自英国横断面和纵向调查的见解

• DOI: 10.31235/osf.io/984yh
• 发表时间: 2023
• 作者: Huebner G

Self-reported energy use in UK homes during the first COVID-19 lockdown: A survey study

首次 COVID-19 封锁期间英国家庭自我报告的能源使用情况：一项调查研究

• DOI: 10.31235/osf.io/f2xvs
• 发表时间: 2021
• 作者: Huebner G

The over-prediction of energy use by EPCs in Great Britain: A comparison of EPC-modelled and metered primary energy use intensity

英国 EPC 对能源使用的过度预测：EPC 建模和计量一次能源使用强度的比较

• DOI: 10.31219/osf.io/jn3v6
• 发表时间: 2023
• 作者: Few J