Agent-based modelling approach to explore efficacy of policies for heat pump uptake

Decarbonising residential heating is essential for the UK to meet its climate targets, as home heating remains a major carbon emitter. This study employs an agent-based model (ABM), integrating logistic regression and utility theory, to simulate UK household adoption of heat pumps from 2021 to 2050. The model captures economic, psychological, and social factors, calibrated with national survey data and historical adoption trends to align long-term diffusion trajectories. Under a business-as-usual scenario reflecting 2025 policies and prices, the model projects 8.7 million households (30.8 %) will adopt heat pumps by 2050. Increasing government grants to £11,500 could raise adoption to 54 %, while a 20 % electricity price reduction may yield a further 12.2 % increase. Logistic regression identifies homeownership, age, cost awareness, and social influence as key predictors. While financial incentives accelerate uptake, they are insufficient alone to meet net-zero targets. Policies must also address behavioural barriers—such as limited awareness, negative perceptions, or perceived hassle—and leverage social networks by promoting peer learning, showcasing early adopters, and supporting community initiatives. This research highlights the utility of ABM for designing decarbonisation strategies that integrate economic, behavioural, and social dimensions of household decision-making.