Effect of Price Dynamics in the Design of Eco-Industrial Parks: An Agent-based Modelling Approach

Even though eco-industrial parks (EIP) models have proved to transform industrial areas by strengthen the emergence of sustainable EIP, there is a noticeable lack of research addressing the economic returns of the participating companies in the network which fluctuates according to prices offered for the resource exchange over time. In this paper, we develop an agent-based model sometimes refer to as bottom-up approach for the design of EIP in which price fluctuation and demand variability are emergent properties of the interaction among the agents. Agent-based modelling (ABM) is a computational methodology used in social science, biology, and other fields. It represents autonomous entities, each with dynamic behaviour. The agents within the eco-industrial park are the factories, market buyers and market sellers. The computational development was performed in Réseau.py, which was built in Python (a programmable modelling environment) from scratch. Based on the autonomy of each of the agents and their individual objectives, simulations were carried out on a bio-energy based EIP (BBEIP) system in order to study the influence of price fluctuation between the agents. The results show that variability in price is a factor for establishing symbiotic relationship among the symbiotic agents in the EIP.