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Non-Invasive Personalized Normative Messaging Intervention for the Reduction of Household Energy Consumption

用于减少家庭能源消耗的非侵入性个性化规范信息干预

基本信息

批准号：
1705273
负责人：
SangHyun Lee
金额：
$ 33万
依托单位：
Regents of the University of Michigan - Ann Arbor
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2017
资助国家：
美国
起止时间：
2017-08-15 至 2021-07-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1705273&HistoricalAwards=false
关键词：
Non Invasive Personalized Normative Messaging

项目摘要

1705273 (Lee). Household fossil fuel consumption in the U.S. is responsible for approximately 22% of primary energy consumption and CO2 equivalent emissions. Consequently, it is an objective of this project to identify widely applicable intervention methods potentially capable of promoting environmentally responsible behaviors. The goal of this research is to advance understanding of how personalized normative comparison groups influence the effectiveness of normative feedback interventions through the development and validation of a non-invasive data mining-based behavior intervention framework, with field experiments conducted in homes in Holland, Michigan. Successful implementation of the research would significantly contribute to reducing harmful emissions from the built environment through the enhancement of pro-environmental feedback intervention design by providing a detailed first look into personalized normative feedback. Specific research objectives are: 1) to classify households into several meaningful groups sharing similar consumption patterns on the basis of hourly energy usage data, using non-invasive techniques; and 2) to generate and then empirically evaluate the effectiveness of personalized normative energy use feedback created with the use of readily available consumption data. The research is targeted to provide an in-depth understanding of both the reliability of personalized normative messages, and how and where energy use behavior changes. Further, it seeks to discover long-term effects of personalized normative feedback on household energy consumption and identify the effect of descriptive norm reference groups on energy consumption norm adherence and energy use. All of these could contribute to residential energy use reduction by advancing the theories for normative energy feedback. The findings on how and where personalized normative messaging changes occupant behavior in both the short and long term have important implications for energy reporting, policy making, and meeting of state and national energy reduction goals. In addition, lessons learned on personalized normative messaging on energy use can be readily applied to other pro-environmental behaviors (e.g., water consumption). Particularly, the proposed non-intrusive personalized feedback messaging framework may be capable of wide-scale deployment in advanced utility networks.

1705273（李）。在美国，家庭化石燃料消耗占一次能源消耗和二氧化碳当量排放的约22%。因此，本项目的一个目标是确定可能能够促进对环境负责的行为的广泛适用的干预方法。本研究的目标是通过开发和验证一个基于非侵入性数据挖掘的行为干预框架，在密歇根州荷兰的家中进行实地实验，以促进对个性化规范性比较组如何影响规范性反馈干预措施有效性的理解。该研究的成功实施将通过提供对个性化规范反馈的详细初步研究来增强环保反馈干预设计，从而大大有助于减少建筑环境的有害排放。具体的研究目标是：1）使用非侵入性技术，根据每小时的能源使用数据，将家庭分为几个有意义的群体，共享类似的消费模式;以及2）使用现成的消费数据，生成个性化的规范能源使用反馈，然后根据经验评估其有效性。该研究旨在深入了解个性化规范信息的可靠性，以及能源使用行为如何以及在何处发生变化。此外，它旨在发现家庭能源消费的个性化规范反馈的长期影响，并确定能源消费规范遵守和能源使用的描述性规范参考组的影响。所有这些都可以通过推进规范的能量反馈理论来减少住宅能源使用。关于个性化规范信息如何以及在何处改变短期和长期居住者行为的研究结果对能源报告，政策制定以及州和国家能源减排目标的实现具有重要意义。此外，关于能源使用的个性化规范信息的经验教训可以很容易地应用于其他环保行为（例如，用水量）。特别地，所提出的非侵入式个性化反馈消息收发框架可以能够在高级公用事业网络中进行大规模部署。