Environmental and economic multi-objective optimisation of synthetic fuels production via an integrated methodology based on process simulation

Process simulation, life cycle assessment (LCA) and techno-economic analysis (TEA) methodologies are extensively used, but not well interlinked. The analyst performs LCA or TEA over a set of predefined rigid scenarios. This work proposes a novel Python framework, eco2des, which is a holistic and interoperable platform for sustainable-oriented optimisation of industrial processes. The studied system is a biorefinery for the coproduction of biofuels and electricity based on biomass gasification. Mass and energy balances are automatically generated mainly through a process simulation and used to evaluate the life cycle environmental and economic performance of the plant. Two multi-objective optimisation problems were built in the eco2des platform to minimise global warming potential and maximise the net present value and kerosene production. The results show that the economic performance is improved when the system tends to the production of excess hydrogen, while the environmental performance improves when electricity generation is prioritised.