[论文解读] Does disaggregated electricity feedback reduce domestic electricity consumption? A systematic review of the literature

Jack Kelly, William J. Knottenbelt|arXiv (Cornell University)|May 3, 2016

Environmental Education and Sustainability参考文献 17被引用 48

一句话总结

本篇系统性综述评估了细分化电能反馈是否能减少家庭用电量，共分析了12项研究。研究发现，尽管细分化反馈平均可使用电量减少0.7%–4.5%，但仅使用汇总反馈即可实现3%的节能量，且其效果通常与细分化反馈相当，表明对于一般人群而言，精细化细分可能并非实现节能所必需。

ABSTRACT

We examine 12 studies on the efficacy of disaggregated energy feedback. The average electricity reduction across these studies is 4.5%. However, 4.5% may be a positively-biased estimate of the savings achievable across the entire population because all 12 studies are likely to be prone to opt-in bias hence none test the effect of disaggregated feedback on the general population. Disaggregation may not be required to achieve these savings: Aggregate feedback alone drives 3% reductions; and the 4 studies which directly compared aggregate feedback against disaggregated feedback found that aggregate feedback is at least as effective as disaggregated feedback, possibly because web apps are viewed less often than in-home-displays (in the short-term, at least) and because some users do not trust fine-grained disaggregation (although this may be an issue with the specific user interface studied). Disaggregated electricity feedback may help a motivated sub-group of the population to save more energy but fine-grained disaggregation may not be necessary to achieve these energy savings. Disaggregation has many uses beyond those discussed in this paper but, on the specific question of promoting energy reduction in the general population, there is no robust evidence that current forms of disaggregated energy feedback are more effective than aggregate energy feedback. The effectiveness of disaggregated feedback may increase if the general population become more energy-conscious (e.g. if energy prices rise or concern about climate change deepens); or if users' trust in fine-grained disaggregation improves; or if innovative new approaches or alternative disaggregation strategies (e.g. disaggregating by behaviour rather than by appliance) out-perform existing feedback. We also discuss opportunities for new research into the effectiveness of disaggregated feedback.

研究动机与目标

• 评估细分化电能反馈是否能在一般人群中减少家庭用电量。
• 比较细分化反馈与汇总反馈在减少能源消耗方面的有效性。
• 探究是否必须采用细粒度细分才能实现显著节能，或粗粒度反馈是否已足够。
• 识别现有实地研究中关于能源反馈的科研空白与方法论缺陷。
• 通过突出反馈系统在设计、部署与报告方面的最佳实践，为未来研究提供指导。

提出的方法

• 使用 Google Scholar、ACM 数字图书馆和 IEEE Xplore 进行系统性文献回顾，采用明确的搜索关键词。
• 基于预设标准筛选出12项聚焦于家庭用电反馈干预措施的研究。
• 提取反馈类型（汇总 vs. 细分）、传递方式（智能电表、网页、应用程序、纸质报告）、用户参与度及节能效果等数据。
• 对结果进行定量综合分析，包括效应量估计及汇总反馈有效性的元分析。
• 评估方法学质量，包括是否使用对照组、随机化处理以及统计分布的报告情况。
• 识别出诸如“自愿参与偏差”及用户对细分数据准确性的信任度等关键局限性。

实验结果

研究问题

• RQ1 细分化电能反馈是否能减少一般人群的家庭用电量？
• RQ2 细分化反馈在减少能源消耗方面的有效性与汇总反馈相比如何？
• RQ3 是否必须采用细粒度细分才能实现显著节能，还是粗粒度反馈已足够？
• RQ4 哪些因素会影响用户对细分化能源数据的信任度与参与度？
• RQ5 未来哪些研究设计可提供更有力的证据，证明细分化反馈的有效性？

主要发现

• 12项使用细分化反馈的研究中，平均节电量为4.5%，但可能因‘自愿参与偏差’而存在正向偏倚。
• 仅使用汇总反馈即可实现3%的节能量，表明其效果可能与细分化反馈相当。
• 四项直接比较汇总与细分反馈的研究发现，汇总反馈至少同样有效，可能因用户对室内显示装置的参与度更高所致。
• 用户通常不信任细粒度细分数据，这可能降低其感知效用与实际影响。
• 细分化反馈可能对特定积极群体——即‘节能爱好者’——有益，但对一般人群实现显著节能并非必要。
• 未来提升反馈有效性的关键可能在于增强用户信任、改进行为细分、实现实时反馈，或采用集成式智能电表-网页交付系统。