Optimizing the bioenergy industry infrastructure: Transportation networks and bioenergy plant locations

In the context of combating climate change and maintaining energy security, ambitious bioenergy development projects in emerging economies face considerable challenges, for example an overburdened bioenergy industry infrastructure due to the growing demand for bioenergy products. There are abundant studies on optimizing the bioenergy industry infrastructure. However, they fail to comprehensively simulate the interactions among the predominant actors of the infrastructure, especially the bioenergy plant operators in emerging economies. To fill this research gap, we develop a new dynamic agent-based model of optimized bioenergy industry infrastructure from the perspective of bioenergy plant operators. We then apply the model to Jiangsu Province of China to simulate the coordination of two types of bioenergy plants and project the optimal distribution of these plants and their corresponding transportation networks for the year of 2030. The model results suggest locating bioenergy plants closer to bioenergy feedstock source regions rather than to bioenergy products consumption sites, an answer to the classical facility location problem. A welfare analysis based on the extended model indicates that the biomass densification process aiming at mitigating the growing transport volumes incurred by the delivery of bulky bioenergy feedstock is not economically profitable in our case region. The experiences from this region further show that for emerging economies, a successful bioenergy industry infrastructure needs to take the benefits of smallholder farmers into consideration.