Tesis doctoralsDepartament d'Enginyeria Mecànica

Amine-free Ionic Liquid Materials for Carbon Dioxide Capture

  • Datos identificativos

    Identificador:  TDX:4723
    Autores:  Yousefe, Mohammad
    Resumen:
    optimizados. En resumen, proporciona herramientas para diseñar y operar comunidades energéticas y sistemas de calefacción distrital, apoyando las decisiones hacia los objetivos de sostenibilidad de la UE. This PhD thesis investigates the pivotal roles of Energy Communities (ECs) and District Heating Systems (DHS) in significantly reducing greenhouse gas emissions and enhancing sustainable energy practices within residential areas. As the global energy landscape shifts towards low-carbon sources in response to growing environmental concerns and escalating energy demands, this research addresses urgent needs for innovative solutions. The research commences with an extensive literature review utilizing bibliometric techniques and science mapping, enabled by a sophisticated data analysis tool developed in the R programming language. This foundational phase discerns emerging trends and obstacles in the integration of renewable energy, providing a basis for subsequent inquiries. Following this, the thesis introduces a multi-objective optimization model designed to minimize life cycle costs and environmental impacts while maximizing the adoption of green energy. This model is enhanced by a multi-criteria decision-making framework employing the Weighted Sum Model (WSM), which facilitates stakeholders in overcoming traditional barriers by selecting optimal solutions for energy communities. Moreover, the study integrates machine learning with life cycle assessment (LCA) and life cycle cost (LCC) analyses to advance the design of renewable energy systems.
  • Otros:

    Editor: Universitat Rovira i Virgili
    Fecha: 2026-10-30T01:00:00Z, 2024-10-30, 2024-12-16T11:58:11Z
    Identificador: http://hdl.handle.net/10803/692857
    Departamento/Instituto: Departament d'Enginyeria Mecànica, Universitat Rovira i Virgili.
    Idioma: eng
    Autor: Yousefe, Mohammad
    Director: Puga Vaca, Alberto
    Fuente: TDX (Tesis Doctorals en Xarxa)
    Formato: application/pdf, 205 p.
  • Palabras clave:

    LCA and LCCA
    Machine learning
    Mathematical programming
    Aprendizaje automático
    ACV y ACCV
    Aprenentatge automàtic
    Programació matemàtica
    Enginyeria i arquitectura
  • Documentos:

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