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

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