Fine-tuning energy efficiency subsidies allocation for maximum savings in residential buildings

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Abstract

Energy consumption in buildings accounts for more than a third of European CO2 emissions. The existing building stock shows the most potential for energy savings but at the expense of costly renovations. Thus, public intervention is decisive in driving transformation in this sector. However, policymakers mostly rely on heat estimates to develop energy-saving policies, limiting the possibility of aligning renovation support policy with environmental gain, slowing down the decarbonization effort. This study explores the benefits of using metered heat demand data with detailed building archetypes for impactful renovation subsidy allocation. We quantify the missed CO2 emissions due to inaccuracies in heat demand estimates and develop an optimization model to quantify the impact of such inaccuracies on subsidy allocation. For the case study of Lyngby-Taarbæk municipality in Denmark, we find systematic bias in heat demand estimates that attribute higher heat demand to older houses than reality and inversely to newer family houses. Such bias results in the misallocation of 39% of total CO2 emissions and distortion of 40% of the total subsidy. Ultimately, our results help policymakers identify buildings that should be prioritized for a maximum decarbonization impact.

Original languageEnglish
Article number124810
JournalEnergy
Volume258
Number of pages13
ISSN0360-5442
DOIs
Publication statusPublished - 2022

Bibliographical note

Funding Information:
The authors acknowledge financial support from the project FlexSUS: Flexibility for Smart Urban Energy Systems (Project No. 91352 ), funded within the framework of the joint programming initiative ‘ERA-Net Smart Energy Systems’ with support from the European Union's Horizon 2020 research and innovation programme under grant agreement No. 775970 . The authors are also grateful to the municipality of Lyngby-Taarbæk for its support and guidance with the acquisition of metered data on heat consumption for buildings located in the municipality.

Publisher Copyright:
© 2022 The Authors

Keywords

  • Energy policy
  • Energy savings
  • Renovation
  • Residential heat consumption
  • Targeted subsidies

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