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

Muhammad Bilal Siddique; Claire Bergaentzlé; Philipp Andreas Gunkel

doi:10.1016/j.energy.2022.124810

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

Muhammad Bilal Siddique^*, Claire Bergaentzlé, Philipp Andreas Gunkel

^*Corresponding author for this work

Department of Technology, Management and Economics

Research output: Contribution to journal › Journal article › Research › peer-review

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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 language	English
Article number	124810
Journal	Energy
Volume	258
Number of pages	13
ISSN	0360-5442
DOIs	https://doi.org/10.1016/j.energy.2022.124810
Publication status	Published - 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

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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title = "Fine-tuning energy efficiency subsidies allocation for maximum savings in residential buildings",

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-Taarb{\ae}k 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.",

keywords = "Energy policy, Energy savings, Renovation, Residential heat consumption, Targeted subsidies",

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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 {\textquoteleft}ERA-Net Smart Energy Systems{\textquoteright} 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-Taarb{\ae}k for its support and guidance with the acquisition of metered data on heat consumption for buildings located in the municipality. Publisher Copyright: {\textcopyright} 2022 The Authors",

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TY - JOUR

T1 - Fine-tuning energy efficiency subsidies allocation for maximum savings in residential buildings

AU - Siddique, Muhammad Bilal

AU - Bergaentzlé, Claire

AU - Gunkel, Philipp Andreas

N1 - 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

PY - 2022

Y1 - 2022

N2 - 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.

AB - 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.

KW - Energy policy

KW - Energy savings

KW - Renovation

KW - Residential heat consumption

KW - Targeted subsidies

U2 - 10.1016/j.energy.2022.124810

DO - 10.1016/j.energy.2022.124810

M3 - Journal article

AN - SCOPUS:85136247417

SN - 0360-5442

VL - 258

JO - Energy

JF - Energy

M1 - 124810

ER -

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

Abstract

Bibliographical note

Keywords

UN SDGs

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