Sinteza fleksibilnih in trajnostnih (bio)kemijskih procesov in mrež v pogojih negotovosti : doktorska disertacija

slovenian

doktorska dela

2021

CO2 emissions   flexibility   mathematical programming   process synthesis   stochastic optimization   supply network   sustainable development   uncertainty

Univerza v Mariboru, Fakulteta za kemijo in kemijsko tehnologijo

The doctoral thesis presents the development of robust computational methods for the design and synthesis of flexible processes and networks with large numbers of uncertain parameters. The use of more precise methods, such as the Gaussian integration method, leads to an exponential growth of the mathematical problem with the number of uncertain parameters. The main achievement of this work is the methodology we developed to avoid exponential growth. The methodology is based on a two-stage stochastic problem with recourse and divides the solution into several steps, where the first-stage variables, i.e., topology and process size or capacity, are determined first, followed by the determination of the second-stage variables, i.e., operating and control variables. As a rule, the mathematical problem is solved in only one point (scenario), but in some variants of the method simultaneously in a small number of scenarios, for example, up to ten.%The basic idea of the methodology is the following: an initial optimal, but practically inflexible process flowsheet is generated at nominal values of uncertain parameters. This flowsheet is then successively optimized at various extreme values of the uncertain parameters, so that the necessary enlargement is determined for process units already included in the flowsheet, while new units are added only when necessary to achieve a feasible solution. In this way, we determine the process topology and process unit sizes for flexible operation. When these no longer change, the flexibility index for the obtained solution is determined and a stochastic Monte Carlo simulation is performed to determine the optimal second-stage variables. At the same time, the expected value of the optimization criterion is calculated with a certain confidence level. In order to establish the flow of information between the separate steps of determining the first- and second-stage variables, a modified method was developed in which the correction factors are calculated to improve the trade-offs between the two types of variables and iteratively improve the final result.%In order to increase the efficiency of the Monte Carlo simulation in the methodology described above, an indicator has been developed to determine the minimum number of scenarios required so that the results are sufficiently accurate for practical application. This reduces the computation time. In addition, a relative optimality index was introduced to compare the developed approximate approaches with the more accurate ones.%Using the proposed methodology, syntheses of flexible networks of heat exchangers and supply network for the production of electricity from biogas upgraded by processing digestate into higher value fertilizers were carried out. It was proved that flexible solutions for large process schemes with large numbers of uncertain parameters can be generated by the proposed methodology in moderate time with manageable computational effort.%In the final part of the thesis, the approaches were developed to include the uncertain value of the CO2 emission tax in the synthesis of the flexible processes during the life cycle. A single-period and a multi-period stochastic approach were tested. A comparison of the results with those of the deterministic method confirmed the advantage of the stochastic approach.%The developed methodology represents a tool for sustainable investment decisions under uncertainty and contributes to the long-term increase of efficiency and competitiveness in the process industry. Its main advantage is that it is suitable for solving problems with large numbers of uncertain parameters. In some case studies, a sustainable objective function was used that combines the synthesis of flexible processes with sustainable development and identifies optimal long-term trade-offs between operational flexibility and economic, environmental and social aspects. By processing waste from biogas plants into useful products, a closed loop

07.08.2023