Helping low-income families with energy transition
NWO funds research by multidisciplinary team of four scientists led by TU/e to study the effects of energy transition
To increase energy efficiency, over the coming decades some 2 million social housing dwellings in the Netherlands will undergo a radical upgrade in the way their homes are insulated and heated. This will affect the low-income families living in these homes, especially those who already have difficulty paying their energy bills. To study the environmental, financial and social impact of this energy transition, a team of scientists from three universities led by TU/e has joined forces with four social housing providers to launch a five-year research program.
The project goes under the name BEL (Behaviour, Energy transition, Low income) and is supported with an NWO grant of 0.5 million euros. It will try to answer questions like: Does the consumption of energy and other goods by low-income families change during the energy transition and in what direction? What happens to the number of households already facing energy poverty? Do people adjust their behaviour and what are the underlying motives?
Unique combination of academic and practical knowledge
BEL exploits a holistic approach based on a unique combination of academic and practical knowledge in the research team. Joint expertise of empirical economist Ioulia Ossokina, behavioural scientist Theo Arentze (both from the department of the Built Environment at TU/e), theoretical economist Vladimir Karamychev (Erasmus University Rotterdam) and data scientist Suzan Verberne (Leiden University) is enriched with practical knowledge and data of four social housing providers: Woonbedrijf from Eindhoven, Elan Wonen and Pré Wonen from Haarlem and Woonlinie from Zaltbommel.
BEL will cover two main research lines. The first one involves empirical big-data-based measurement of behavioral responses of low income tenants and their underlying motives. In the second research line researchers will build and apply a structural model to analyse and predict effects of energy efficiency improvements for low-income households. In the end the aim is to develop practical tools to optimize energy efficiency packages and aftercare in social housing.