Identificador: TDX:4257
Autores: Brunet Solé, Robert
Resumen:
The society is every day more conscious about the scarce of resources, the global economy, and the environmental changes. Hence, chemical companies have the necessity to be adapted and develop more sustainable processes. There is a clear demanding to the scientific community to develop systematic tools to achieve reductions in the production costs as well as the associated environmental impact in order to develop decision support tools for the design of chemical plants.
This thesis introduces a novel framework for the optimal design of sustainable chemical processes. Our approach combines process simulation, multi-objective optimization tools (MOO), economic analysis, life cycle assessment (LCA) and decision support systems (DSS). The developed strategy will be used to solve very complex problems. For that it will be necessary to develop new algorithms and decomposition strategies to divide the original problem in more manageable sub-problems, to obtain the optimum design of the process. The capabilities of the methodology have been tested in different processes along the Ph.D Thesis.
This PhD dissertation is presented using six articles that have been published in international peer reviewed journals. The first part, which includes two publications, is focused in the development of sustainable bioprocesses, as these processes have recently gained wider interest for their potential to produce high-value products. In the first work, we studied the maximization of the Net Present Value (NPV) in the production of the amino acid L-lysine. The design task is mathematically formulated as a mixed-integer dynamic optimization (MIDO) problem, which is solved by a decomposition method that iterates between primal and master sub-problems. The dynamic optimization primal sub-problems are solved via a sequential approach that integrates the process simulator SuperPro Designer® with an external non-linear programming (NLP) solver implemented in Matlab®, while the task of the master problem is to decide on the value of the integer variables. In the second paper, the optimization allows for the simultaneous consideration of economic and environmental concerns. We optimize in this case the economic (NPV) and different environmental indicators. The solution is given by various bi-objective Pareto sets, and then we applied principal component analysis (PCA) in order to find redundant objective functions between the environmental indicators.
Because the energy demand has drastically increased over the last few years, the energetic analysis of industrial processes has gained wider interest. Hence, we focused in the second part of the thesis in the optimal design of thermodynamic cycles. In this section, we published two papers. In the first article of the second part we present a method for the optimal design of ammonia-water absorption cycles for cooling and refrigeration applications with economic and environmental concerns. The design task is posed as multi-objective mixed-integer non-linear programming (MINLP). In the second article, we expand our work to different thermodynamic cycles. We demonstrate the capabilities of the approach with a 10 MW Rankine cycle simulated in Aspen Hysys® and a 90 kW ammonia-water absorption cycle in Aspen Plus®.
Biofuels production worldwide is continuing to grow at very rapid pace. Hence, in the third part of the thesis, we applied the techniques developed in different biofuels production processes. This third part includes two publications. In the first work
we address the problem of reducing the environmental impact of biodiesel plants through their integration with a solar thermal energy system that generates steam. A mathematical model of the solar energy system that includes energy storage is programmed and coupled with a rigorous simulation model of the biodiesel facility developed in Aspen Plus®. The solar energy system accounts for the simultaneous minimization of cost and global warming potential. In the second work, we address MOO of a corn-based bioethanol plant coupled with solar assisted steam generation system with heat storage. Our approach relies on the combined use of process simulation, rigorous optimization tools and, economic and energetic plant analysis.
Overall, we can consider that this thesis presents a promising framework for the optimal design of sustainable chemical processes. Numerical results show that it is possible to achieve environmental and cost saving using this rigorous approach. Additionally, this approach has been applied in very different type of processes, such as: bioprocesses, thermodynamic cycles and biofuels. This methodology will be very useful for decision-makers in order to evaluate the topology and operating conditions in process system engineering
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