Systems Integrations for the Holistic Design of Second Generation Biorefineries

Abstract

The development of integrated biorefineries is a multidimensional problem, which combines the traditional process design problem with the synthesis problem of product portfolios and multiple processing paths at various technological readiness levels (TRLs). The complexity and the size of the combined problem do not allow the development of a single optimization model. However, this thesis presents an approach to systems decomposition for the design problem of second generation biorefineries. The framework combines various design scales and tools for modeling, integration, and synthesis. The main objective is to simultaneously reduce the cost and the environmental impact, while optimizing the use of the utilities. Challenges include (i) the management of the data acquired by various sources (literature or experimental) and at various accuracy levels due to different TRLs (pilot, laboratory, or theoretical stage), (ii) the systematic screening of processing paths while considering the technological attributes, (iii) the impact of alternative designs on the utility consumption (mass and energy), (iv) the endogenous symbiotic options when revamping existing installations, and (v) the integrated waste management. The approach makes use of surrogate-based optimization primarily to harmonize data coming from different sources, but also to assist in the systematic development of lower-grain models. Surrogates are employed to address deviations between the fine models and the experimental data by handling certain process and property parameters as degrees of freedom. Their use is illustrated by the synthesis of the value chain, where superstructures are developed as bipartite graphs of sinks and sources, organizing the processes as modular units that can be modified, replaced, and/or re-engineered. The synthesis problem is demonstrated in a network of twenty-one different processes, each accounted of separate surrogates. Next, the study continues with an optimization model that sets utility targets, simultaneously for mass and energy consumption, and to screen alternative technological options. The framework is applicable to both grassroots and retrofit designs. Lastly, the approach is extended for the integrated waste management and treatment. For this purpose, decision trees are proposed to classify the waste streams with criteria related to their physical state (liquids, solids and gases) and their qualitative characteristics. The optimization problem is formulated as a mixed-integer nonlinear programming problem. The objective function considers economic and environmental criteria, while the integration framework and the treatment technologies are considered as degrees of freedom. Results show that surrogates led to significant improvements, and, when assisted by the simulation models, their selections were verified on industrial scale. In the process synthesis problem, results coming from nominal screening were rejected due to the qualitative characteristics of the streams and the technological constraints. The simultaneous integration of utilities and process design options demonstrated significant cost savings by reducing the energy consumption and proposing more efficient recycling/recuse configurations. The results of the retrofit problem showed a marginal preference for bioethanol production (partly due to the maturity of technology) but with coproduction of specialties and the integration of new technologies. The integrated waste management yielded significant savings in using decentralized treatment and nonconventional solutions. Results demonstrate the immense importance of the integrated design, confirming that the industrial biorefinery cannot compete with the equivalent conventional units without sufficient integration. The research of this thesis has assisted in the industrial development of laboratory and pilot technologies, which were originally developed in France.