Computational platform for optimal design of biorefineries using energy and mass integration

Diminishing petroleum reserves, uncertainties in energy supplies, rising demand for transportation fuels, requirement for sustainable economic growth together with global warming and stringent environmental restrictions has promoted our society to explore alternative, renewable processes such as biorefinery processes. The objectives of this work are development of an early stage design decision making approach by implementing optimal mass and energy integration algorithms for process synthesis and unit designs in large scale biorefining systems to identify most promising technologies and optimum configuration and sizes of process units and to make a competitiveness comparison in terms of economic performance and environmental impact. To be able to achieve these goals, a systematic process design methodology is applied to a lignocellulosic biorefinery which utilizes the wood feedstock to produce C5, C6 and lignin platforms of different bio-based fuels and chemicals. An algorithm that allows different conversion pathways to be evaluated inside the superstructure and ordered according to the objective function values is developed. This methodology is used to select and rank different technologies to convert biomass according to objective function