Spatial Agent-Based Modelling and Simulation to Evaluate on Public Policies for Energy Transition

Abstract

The manuscript describes the development of a spatial Agent-based Simulation to model the effect of public policies on private houseowner’s decisions concerning their heating system. The methodology utilized comprises of an empirical survey to determine the (location-based) behaviour and motivation of homeowners. In addition, spatial data on the houses can be used to implement renovation and thermal refurbishment in the simulation. In addition, the system is able to model and simulation the effect of public policies on the actions of homeowners. Hence, based on their decisions the system can estimate the carbon footprint of the houses over the simulation period. Hence, decision makers can select the best policy (e.g. funding, motivation) to reduce the carbon footprint of communities.