Multi-disruption criticality analysis in bioenergy-based eco-industrial parks via the P-graph approach

Abstract

Abstract Bioenergy-based eco-industrial parks or “bioenergy parks” are integrated networks of biomass processing industries that optimally allocate products, by-products, waste, as well as common utilities in order to further improve sustainability. This multifunctional system produces high value products such as power, biochar, biochemicals, etc. alongside with the conventional biofuels (e.g., bioethanol). However, these networks are characterized as inherently vulnerable to cascading disruptions in cases of inoperability (i.e., reduction in production levels) of one or more of its component bioenergy plants. The inoperability of bioenergy plants can be caused by supply-side disruptions due to reductions in the available biomass feedstocks (i.e., caused by climate change-induced events) as well as due to seasonal variations in the demand for bioenergy products. It is therefore essential to incorporate these factors in the systematic risk analysis prior to designing of bioenergy parks. This work thus develops an extension to the P-graph based method for criticality analysis in bioenergy parks considering multiple supply-side and demand-side perturbation scenarios. Results show that the average net output reduction in the bioenergy park is higher for multiple plant disruption scenarios and criticality of bioenergy plants is greatly influenced by variations in product demands. The proposed method can be used in the long-term planning and developing of robust bioenergy parks while considering both uncertainties in the supply and demand. A bioenergy park case study is presented to demonstrate the applicability of the P-graph based approach.