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University of Ontario Institute of Technology

Design and evaluation of integrated waste to energy multigenerational systems

Abstract

dc:description.abstract

This thesis study develops three renewable energy-based waste-to-energy multigeneration systems and examine them thermodynamically and economically. The first system uses solar-based energy and animal manure waste, and the second system utilizes waste tires with geothermal energy. Finally, the third system is an underground coal gasification system in which low-grade lignite is considered waste and used as fuel. Hydrogen, ethanol, electricity, heating, cooling, and sulfuric acid are produced for the communities in Konya in Turkey, Tuscany in Italy, and Kutahya in Turkey. All suggested systems are developed, modelled, and analyzed using thermodynamic-based sensitive simulations and software. According to the calculations, multigeneration system 2 provides the best performance results, and the overall system energy and exergy efficiencies are 71.45% and 69.87%, respectively. Integration of waste-to-energy systems with renewable energy sources leads to the prevention of waste generation and the development of more environmentally benign systems.

Degree

thesis:*
Name thesis:degree_name
Master of Applied Science (MASc)
Discipline thesis:degree_discipline
Nursing
Grantor
University of Ontario Institute of Technology
Year dc:date.issued
2022

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Kahraman, Ugur
Advisor dc:contributor.advisor
  • Dincer, Ibrahim

Subjects

dc:subject × 5

Rights

Language dc:language.iso
en

Identifiers

dc:identifier.*
Handle dc:identifier.uri
https://hdl.handle.net/10155/1443
OAI identifier oai:identifier
oai:ontariotechu.scholaris.ca:10155/1443

Chain of custody

source
Harvested from
Ontario Institute of Technology
Base URL
ontariotechu.scholaris.ca/server/oai/request
Last updated
2026-07-24
Source record
OAI-PMH GetRecord
citation

Kahraman, Ugur. Design and evaluation of integrated waste to energy multigenerational systems. University of Ontario Institute of Technology, 2022. https://hdl.handle.net/10155/1443