Modelling household barriers to retrofits and solar energy - Quantifying the hidden cost in the Norwegian energy transition

Bibliographic Data

ID13067933
AuthorsPernille Seljom (0000-0002-3124-1056, Institute for Energy Technology, corresponding author), Eva Rosenberg (Institute for Energy Technology), Yechennan Peng (0000-0001-9831-5876, Norwegian University of Science and Technology), Christian Andreas Klöckner (0000-0003-4510-1748, Norwegian University of Science and Technology)
Year2025
Volume127
Pages104260-104260
Publication date2025-08-12
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueEnergy Research & Social Science (JOURNAL)
Journal identifiersISSN: 2214-6296 • E-ISSN: 2214-6326
PublisherElsevier BV (PUBLISHER)
DOI10.1016/j.erss.2025.104260
OpenAlexW4413103329
LanguageEN
Citations received1
References cited39

Long-term energy system models are widely used to support decision-making for policymakers and industry stakeholders. However, these models often assume households behave as techno-economic rational agents, which can lead to misleading insights for guiding the energy transition. This paper proposes a methodology on how household investment behaviour can be more accurately integrated into long-term energy system models, as well as analysing the value of overcoming barriers that prevents households from energy investments. The approach is demonstrated using a Norwegian energy system optimization model combined with data from a comprehensive survey of 2997 households. The analysis focuses on the adoption of retrofits and building-applied solar power towards 2050. The survey reveals that 85 % of the respondents face one or more barriers to implementing retrofits or PV. Results show that removing these barriers has significant monetary value for both the energy system and households, particularly in the case of retrofits. It is estimated that a socio-economic budget of up to 26 billion EURO could be allocated to overcome these barriers. Importantly, more than half of this budget would need to address non-financial barriers, highlighting the importance of broader policy measures beyond financial incentives. • Survey data informs household behaviour in energy system model. • Retrofits in households significantly benefit the low-carbon transition. • Both financial and non-financial barriers limit a cost-efficient transition. • Up to 85 % of the respondents have one or more barriers for implementation. • A socio-economic budget for retrofits and PV implementation is assessed

Electrical engineering · Energy (signal processing · Energy transition · Engineering physics · Norwegian · Physics · Solar energy · Energy Efficiency and Management · Energy, Environment, and Transportation Policies · Engineering · Environmental Science · Smart Grid Energy Management

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