Energy production and consumption in cities are both inextricably linked to urban form that in itself is driven by land use planning. Yet, little is known as to how changes in land use can impact energy self-sufficiency in cities, whereby in-boundary energy production is able to satisfy in-boundary consumption needs. In this paper, we develop a workflow to model how urban energy selfsufficiency changes under various scenarios of land use change. We then apply this method to an empirical dataset for Palo Alto, a mid-size city in California, USA. Results indicate that as urban density is increased through land use change, urban energy self-sufficiency decreases, prompting the need for the joint consideration of energy efficiency and other measures with land use planning. In addition to demonstrating the importance of land use as an underexplored lever for urban energy use, our results have practical implications for the deployment of distributed energy resources (DERs) in cities, particularly solar energy.
Keywords urban energy, land use, distributed energy resources, spatial bootstrapping, data analytics