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An Agent-based Model for Sustainable Development of Optimal Industrial Symbiosis Networks

Saghafi, Zohreh | 2023

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 56009 (46)
  4. University: Sharif University of Technology
  5. Department: Energy Engineering
  6. Advisor(s): Roshandel, Ramin
  7. Abstract:
  8. Industrial symbiosis(IS) is a promising approach toward sustainable development goals. Among common modeling techniques, agent-based modeling holds a special place in IS simulation due to its bottom-up nature. However, the role of essential technologies in supply chain of IS has been poorly studied in the literature. In this work, first, an agent-base model is developed based on economic and environmental incentives of IS stakeholders employing optimization and non-cooperative game theory. Then, essential technologies in each potential symbiotic relation are integrated into the model to investigate their impact. The result suggests, to facilitate IS through environmental policy making, on one hand, pricing regulations are the priority in compare with quantitative restraints, on the other hand, the status of both sides must be acknowledged. Also, technologies show diverse effects, a technology may boost, constrain or reshape IS. Moreover, as expected, performance indicators of industrial symbiosis network (including saved input and recovered waste) declines in the presence of technologies specially, in the case of waste heat recovery. Precisely, while percentage of recovered biomass remains fairly steady at 7%, waste heat recovery decreases from 86% to only 3% which leads to 90% drop in overall saved input. At last, to follow current study, it is recommended to consider various prospective technologies in a symbiotic relation, optimizing the technological/technical parameters alongside considering other IS stakeholders as new agents in the presented model
  9. Keywords:
  10. Industrial Symbiosis ; Heat Recovery ; Waste Heat Recovery Power Generation (WHRPG)Technology ; Anaerobic Digestion ; Agent Based Modeling ; Multiagent System ; Sustainable Development ; Energy Symbiosis

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