A preliminary study of an Agent-Based Model of a complex adaptive socio-techno-economic system in energy technology diffusion

The diffusion of energy technologies in the cities of the future is the key towards a more sustainable community. The increasing use of renewable energy sources, efficient energy conversion machines, storage systems and ICT solutions, thanks to increasing amount of energy data, will require methodologies to support the decision-making process in long-term urban energy planning. To reach the goal, these technologies have to be integrated and interconnected between them, especially in the urban context, as well as encourage their use, considering the consumer's energy choices end environmental constraints. This preliminary study aimed to develop an Agent-Based Modelling (ABM) infrastructure to simulate a complex adaptive socio-techno-economic system in energy technology adoption. The model creates an environment with a GIS space representing the San Salvario’s district of Turin in which agents are households, and they decide whether to adopt rooftop PV. Following theories of human behaviour on making decisions, social network interactions and techno-economic feasibility the model predicts the diffusion of PV systems, finding what could be the socio-economic parameters that modify the likely emergent diffusion trend of the whole system. ABM allows representing a complex adaptive system in a flexible and detailed way describing the decision-making process of agents and the physical and economic environments surrounding them. The agents are entities like individuals or also a group of people like the households, and they could live in the same apartment building as a condominium. They make actions individually considering their states and decision rules, interacting with their social networks, resources and with the environment. The results of the preliminary study showed that the diffusion of the energy technology is not only dependent on technical and economic variables. What is also relevant are the opinions of the consumers and how these change in time due to network influence, social norms, advertising and environmental awareness. This first approach to ABM is a Proof of Concept to develop a validated model at urban-scale using real data. The model can be used to energy policy design and evaluation, knowing how the spatial and temporal diffusion pattern changes acting on parameters like economic incentives, publicising of the technologies on their benefits and costs and more else. Besides, knowing where and when the technologies spread is fundamental to system design and smart infrastructure planning.