Association for Public Policy Analysis & Management

Household energy consumption in the transport and residential domains tends to be analysed separately, failing to recognise interlinkages between households' preferences, choices and behaviours expressed in different areas of everyday life. As a result, our understanding of the collective outcome of household actions on society, infrastructure and climate lacks behavioural realism, which makes it difficult to shape policies to reduce energy consumption and mitigate climate change in these domains. In response, we extended an agent-based land use-transport model (SelfSim) to incorporate a domestic energy consumption model and an energy-related technology adoption model. The resulting integrated model simulates the emergent development of an urban system comprising heterogeneous households making interlinked choices in domestic, transport, and energy domains. This allows us to explore how different policies (e.g., incentives) and technologies (e.g., smart appliances and electric vehicles) in these domains interact, generating new insights on the social, infrastructural and climate impacts of inter-dependent behaviours. We used a Chinese medium-sized city, Baoding, as a test case for this pioneering new model development work. Both the aggregate and disaggregate outcomes, such as the spatial distribution of electricity demand and total amount of GHG emissions, provide essential information for local authorities, urban planners, and energy utilities when designing investment and policy strategies for low-carbon cities.