A contribution to sustainable management of integrated material/energy networks in process industries
- Autores: Shabnam Morakabatchiankar
- Directores de la Tesis: Antoni Espuña Camarasa (dir. tes.), Moisès Graells Sobré (codir. tes.)
- Lectura: En la Universitat Politècnica de Catalunya (UPC) ( España ) en 2021
- Idioma: español
- Tribunal Calificador de la Tesis: Mariano Martín Martín (presid.)
- Materias:
- Enlaces
- Tesis en acceso abierto en: TDX
- Resumen
Towards sustainability forces process industries to change their traditional patterns. Therefore, efficient retrofitting has been a significant challenge and raised several issues, motivating the process system engineering (PSE) to develop models. These models mainly aim to optimize profitability, cost reduction, energy consumption, demand satisfaction, the environmental impact associated with the production process, and social acceptance. Nevertheless, such optimization is significantly complicated if considering the presence of uncertainty and seeking compromised outcomes.
This thesis aims to extend a general model to facilitate retrofitting in industrial processes and expedite optimization of the issues. Such a contribution based on developing efficient mathematical models allows coordinating many decision variables synchronizing the production and distribution tasks in terms of economic and environmental criteria.
This thesis presents an overview of the retrofitting requirement towards sustainable material/energy networks, describing and analyzing the current methods, tools, and models used and identifying the most relevant open issues.
The second part focused on developing current models stressing energy integration in the processing system. This part first explores how the economic performance of the network can be enhanced and environmental impacts improved simultaneously by integrating an energy generation unit into the production system. Furthermore, the network sustainability performance was explored under demand uncertainties. Additional risk indicators (including financial and environmental risk metrics) have been included to add risk management capability to the model. This part also explores the strategies that efficiently select the number of scenarios.
Consequently, a novel generalized mathematical formulation that integrates equations regarding energy generation and material production decision variables is efficiently solved. The effect of uncertainty on the economic and environmental performance is analyzed by using risk analysis. Finally, the model was extended to solve multi-renewable energy generation integrated into the multi-product production process under demand uncertainty. The importance and effect of the energy/material integration over the network configuration are analyzed through sensitivity analysis.
The third part of this thesis provides the conclusions and further work to be developed.
