Using an optimization model to evaluate the economic benefits of industrial symbiosis in the forest industry

In this work, a model comprising a pulp mill, a sawmill, a district heating network and a biofuel upgrading plant is used to demonstrate how the MIND method, an optimization method based on mixed integer linear programming, can be used to evaluate industrial symbiosis in the forest industry. Using this method, both energy and material flows on both the supply and the demand side can be studied simultaneously. The method can be used to find improvements in the structure of the modelled system, to find the optimal operational strategy of a given system, and to evaluate and compare different systems. The total system costs for stand-alone cases and integrated industrial symbiosis system configuration are compared, generating results that can be used as decision support when planning industrial symbiosis initiatives in the forest industry. The results of this study showed that there are financial benefits to industrial symbiosis compared to the same system operated in stand-alone mode, and that the industrial symbiosis configuration generates a more stable system. However, it is difficult to generalize the results from a case study, and the main conclusion drawn is that it is possible to show that industrial symbiosis has economical benefits, although the magnitude of these benefits needs to be evaluated from case to case.