行为干预能否优化自我消费?来自德国消费者实地实验的证据

IF 5.4 Q2 ENERGY & FUELS
Sabine Pelka , Anne Kesselring , Sabine Preuß , Emile Chappin , Laurens de Vries
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引用次数: 0

摘要

使消费者的用电量与自发自用的电力供应相匹配,可以减少二氧化碳排放并降低成本。有人提出 "暗示"(Nudges)作为一种行为干预措施来协调这种变化。与此同时,文献中零散的研究结果使得为特定家庭和环境确定合适的行为干预措施--特别是优化自我消费的行为干预措施--具有挑战性。我们在一项针对 111 户德国屋顶光伏家庭的实地实验中,测试了数字工具提供的三种依次应用的干预措施(反馈、基准和默认)。实验设计包括对照组、基线测量和高频智能电表数据,使我们能够检验每种干预措施对增加自我消费的因果效应。虽然反馈和基准会带来较小的自我消费增长(3%-4%),但智能改变默认值会使积极参与者的自我消费增长 16%。一般来说,拥有可控电动汽车的家庭比没有可控电动汽车的家庭显示出更强的效果。为了扩大对其他消费者的行为干预,我们建议采取只需少量互动和能源知识的干预措施,因为即使是自主选择的积极样本也很少与数字工具互动。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Can behavioral interventions optimize self-consumption? Evidence from a field experiment with prosumers in Germany

Can behavioral interventions optimize self-consumption? Evidence from a field experiment with prosumers in Germany

Aligning prosumers' electricity consumption to the availability of self-generated electricity decreases CO2 emissions and costs. Nudges are proposed as one behavioral intervention to orchestrate such changes. At the same time, fragmented findings in the literature make it challenging to identify suitable behavioral interventions for specific households and contexts - specifically for optimizing self-consumption. We test three sequentially applied interventions (feedback, benchmark, and default) delivered by digital tools in a field experiment with 111 German households with rooftop-photovoltaics. The experiment design with a control-group, baseline measurements, and high-frequency smart-meter-data allows us to examine the causal effects of each intervention for increasing self-consumption. While feedback and benchmark deliver small self-consumption increases (3–4 percent), the smart changing default leads to a 16 percent increase for active participants. In general, households with controllable electric vehicles show stronger effects than those without. For upscaling behavioral interventions for other prosumers, we recommend interventions that require little interaction and energy literacy because even the self-selected, motivated sample rarely interacted with the digital tools.

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来源期刊
Smart Energy
Smart Energy Engineering-Mechanical Engineering
CiteScore
9.20
自引率
0.00%
发文量
29
审稿时长
73 days
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