Design of the optimal industrial symbiosis system to improve bioethanol production

Abstract

Abstract The emergence of environmental and sustainability regulations, such as Kyoto protocol, Energy Policy Act and the increasingly limited availability of fossil fuels has brought the notion of gradually substituting petroleum products with bioethanol into the limelight. Even though, bioethanol is one of the cleanest sources of energy, a major concern of bioethanol production is its economic feasibility. Industrial symbiosis is one of the sustainable strategies that can help to reduce bioethanol production and logistic costs. In industrial symbiosis, traditionally separate plants collocate in order to efficiently utilize resources, reduce wastes and increase profits for the entire industrial symbiosis and each player in the industrial symbiosis. This paper focuses on developing optimal configurations of bioenergy-based industrial symbiosis under certain constraints, such that the bioethanol production cost (or profit) is reduced (or increased). A decision framework that combines the Linear Programming models and large scale Mixed Integer Linear Programming model is proposed to determine the optimal configuration of bioenergy-based industrial symbiosis and to design the optimal network flows of various products in the bioenergy-based industrial symbiosis. A case study has been conducted to study the efficiency and effectiveness of the proposed model and the results suggest significant increase in profitability for biorefinery plant and the rest of the players in the bioenergy-based industrial symbiosis system. Sensitivity analysis is also conducted to provide deep understanding of the proposed bioenergy-based industrial symbiosis system and to identify the factors that might impact the performance of biorefinery plant in bioenergy-based industrial symbiosis.