Adoption of renewable home heating systems: An agent-based model of heat pumps in Ireland

• Published in: Renewable & sustainable energy reviews Vol. 169; p. 112853
• Main Authors: Meles, Tensay Hadush, Ryan, Lisa
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.11.2022
• Subjects: Agent-based model; Heat pumps; Home heating; Ireland; Technology adoption; Technology adoption; Home heating; Heat pumps; Ireland; Agent-based model
• ISSN: 1364-0321; 1879-0690
• DOI: 10.1016/j.rser.2022.112853

Consumer adoption of renewable energy technologies such as heat pumps for home heating is crucial in reducing greenhouse gas emissions and reliance on imported fossil fuels. In recognition of their potential, policymakers in several countries have introduced various financial incentives to encourage the uptake of renewable energy technologies. However, consumers' purchasing decisions and choice of a particular technology is a complex process that goes beyond financial aspects. In this paper, we examine the adoption decisions and diffusion of heat pumps for residential home heating using an agent-based modeling and simulation approach. In particular, we model the influence of three factors: economic, psychological, and social networks, on the future uptake of heat pumps. We utilize recent nationally representative Irish household survey data and historical heat pump uptake data to derive model parameters for decision rules based on empirical data and simulate the adoption of heat pumps in existing Irish homes until 2030. We further analyze the implications of those future uptakes on electricity demand, bill savings, and reduction in CO2 emissions. The findings of this research based on the case study of Ireland should be useful to policymakers and companies in devising monetary and non-monetary interventions aimed at increasing future actual uptake of heat pumps and other renewable energy technologies. •Develops an agent-based model to study the adoption of heat pumps in a market at an early stage of development.•Incorporates economic factors, psychological aspects, and social networks in adoption decisions.•Uses representative household survey data to populate and initiate model simulation with real-world preferences.•Analyzes implications of future uptake on electricity demand, cost savings, and CO2 emissions.