Abstract
Households are responsible for a third of the final energy consumption in Germany in 2018 with the average household meeting 60% of household energy service needs with fossil fuels. Energy transition targets to increase renewables and energy efficiency will require high upfront capital investments into building renovations, heater and appliance upgrades. Overall less than 17% of households have sufficient capital and are in the decision-making power to undertake investments. The household sector is disaggregated into 56 profiles by key socio-economic parameters (income, building type, tenure status, urbanization) and, together with a budget constraint limiting the total available capital on all investments and consumption per profile, incorporated into an energy system optimization model to account for the differentiated needs and financial capabilities of diverse household types. This method provides a platform from which to evaluate the impact of various policies and measures. Selected scenarios include a comparison between a reference case and two carbon revenue redistribution schemes. The results yield insights into the energy-related investment and consumption patterns for different household types emphasizing fuel types, emissions and quantification of suppressed demand (expressed through household budget deficit for unmet household service demands), and show that to evaluate the energy welfare of lower income households several aspects must be considered.
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Dobbins, A., Fahl, U. (2023). A Decision Support Method to Assess Energy Policy Impacts on Different Household Types for a Socially Just Energy Transition in Germany. In: Grothe, O., Nickel, S., Rebennack, S., Stein, O. (eds) Operations Research Proceedings 2022. OR 2022. Lecture Notes in Operations Research. Springer, Cham. https://doi.org/10.1007/978-3-031-24907-5_12
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