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  4. Can behavioral interventions optimize self-consumption? Evidence from a field experiment with prosumers in Germany
 
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2024
Journal Article
Title

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

Abstract
Aligning prosumers' electricity consumption to the availability of self-generated electricity decreases CO 2 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.
Author(s)
Pelka, Sabine  orcid-logo
Fraunhofer-Institut für System- und Innovationsforschung ISI  
Kesselring, Anne  orcid-logo
Fraunhofer-Institut für System- und Innovationsforschung ISI  
Preuß, Sabine  orcid-logo
Fraunhofer-Institut für System- und Innovationsforschung ISI  
Chappin, Emile
Delft University of Technology, Faculty of Technology Policy and Management
Vries, Laurens de
Delft University of Technology, Faculty of Technology Policy and Management
Journal
Smart energy  
Open Access
File(s)
Download (9.21 MB)
Rights
CC BY-NC-ND 4.0: Creative Commons Attribution-NonCommercial-NoDerivatives
DOI
10.1016/j.segy.2024.100140
10.24406/publica-2880
Language
English
Fraunhofer-Institut für System- und Innovationsforschung ISI  
Keyword(s)
  • Default

  • Nudge

  • Demand response

  • Smart meter data

  • Smart charging

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