An Agent-Based Model (ABM) for the Evaluation of Energy Redevelopment Interventions at District Scale: An Application for the San Salvario Neighborhood in Turin (Italy)

The optimization of mobility connections, the use of renewable energy resources and the retrofit of buildings are only some of the aspects that affect urban transformations and planning. Decision maker and urban planners must be faced with multi-dimensional aspects and objectives in a long-term vision. In that context, different methods have been developed in order to consider these multi-dimensional perspectives. However, only a few approaches try to simulate the effects in a multi-temporal way. Agent-based model (ABM) try to do exactly this, considering, in particular, the interactions among agents through a bottom-up approach. Aim of this research is to apply an ABM to a real case study in the San Salvario neighborhood in Turin (Italy), simulating a complex socio-economic-architectural adaptive system to study the temporal diffusion of energy requalification operations and the willingness of inhabitants to adopt different retrofit actions. The two applications were, firstly, built on a computer grid environment and, then, integrated with GIS maps, in order to analyse the effects in the real distribution of buildings of San Salvario. Agents are designed to choose which system adopt, based on different theories of human behaviors. We discuss limitations of the current models and we suggest future directions of this research.