Analysis and optimization of sustainable transport processes of biomass for power plants

• Main Author: Cienfuegos, Bernardo
• Format: Others
• Language: en
• Published: 2020
• Online Access: https://tuprints.ulb.tu-darmstadt.de/12211/1/Diss_Cienfuegos_TUprints_2020.pdf; Cienfuegos, Bernardo <http://tuprints.ulb.tu-darmstadt.de/view/person/Cienfuegos=3ABernardo=3A=3A.html> (2020): Analysis and optimization of sustainable transport processes of biomass for power plants.Darmstadt, Technische Universität, DOI: 10.25534/tuprints-00012211 <https://doi.org/10.25534/tuprints-00012211>, [Ph.D. Thesis]

This work addresses the transport planning of raw material supply chains for biomass power plants. It considers the need of generating sustainable solutions by analyzing relevant sustainability frameworks to propose a novel approach. It proposes a novel approach which consists of an architecture to tailor a proposed base model, and to process the relevant data needed to generate sustainable solutions. The special characteristics of the biomass transport problem and power plant requirements are captured in a formal problem definition in the form of a data model. The architecture consists of five combined models (called modules). Each module contributes with methods from different disciplines to enrich the solutions with distinct perspectives. The considered modules include elements from the social, weather, geographic information systems (GIS), life cycle impact assessment (LCIA), and mathematical optimization disciplines. An integrated solution is generated combining the results of all the modules. Important implementation elements for specific potential users are discussed to support a system prototype. A case study in Chile is used to gain related primary information of a real supply chain, test the architecture, and provide results about the performance, and allows a deeper discussion. The architecture generates optimized transport plans that make impacts visible in the considered sustainability dimensions and give the decision makers a better understanding of the effects of the considered solutions.