Optimal decarbonisation pathway for mining truck fleets

dc.contributor.authorYu, Gang
dc.contributor.authorYe, Xianming
dc.contributor.authorYe, Yuxiang
dc.contributor.authorHuang, Hongxu
dc.contributor.authorXia, Xiaohua
dc.contributor.emailxianming.ye@up.ac.zaen_US
dc.date.accessioned2025-03-20T11:56:06Z
dc.date.available2025-03-20T11:56:06Z
dc.date.issued2024-09
dc.descriptionDATA AVAILABILITY : Data will be made available on request.en_US
dc.description.abstractThe fossil fuel powered mining truck fleets can contribute up to 80% of total emissions in open pit mines. This study investigates the optimal decarbonisation pathway for mining truck fleets. Notably, our proposed pathway incorporates power generation, negative carbon technologies, and carbon trading. Technical, financial, and environmental models of decarbonisation technologies are established, capturing regional variations and time dynamic characteristics such as cost trends and carbon capture efficiency. The dynamic natures of characteristics pose challenges for using the cost-effective analyses approach to find the optimal decarbonisation pathway. To address this, we introduce a mixed-integer programming optimisation framework to find the decarbonisation pathway with minimum life cycle costs during the planning period. A case study for the optimal decarbonisation pathway of truck fleets in a South African coal mine is conducted to illustrate the applicability of the proposed model. Results indicate that the optimal decarbonisation pathway is significantly influenced by factors such as land cost, annual budget, and carbon trading prices. The proposed method provides invaluable guidance for transitioning towards a cleaner and more sustainable mining industry.en_US
dc.description.departmentElectrical, Electronic and Computer Engineeringen_US
dc.description.librarianam2024en_US
dc.description.sdgSDG-07:Affordable and clean energyen_US
dc.description.sdgSDG-09: Industry, innovation and infrastructureen_US
dc.description.sdgSDG-12:Responsible consumption and productionen_US
dc.description.sponsorshipNational Key R&D Program of China, National Natural Science Foundation of China, National Research Foundation China/South Africa Research Cooperation Programme and Royal Academy of Engineering Transforming Systems through Partnership grant scheme.en_US
dc.description.uriwww.keaipublishing.com/en/journals/journal-of-automation-and-intelligence/en_US
dc.identifier.citationYu, G., Ye, X., Ye, Y. et al. 2024, 'Optimal decarbonisation pathway for mining truck fleets', Journal of Automation and Intelligence, vol. 3, pp. 129-143. https://DOI.org/10.1016/j.jai.2024.03.003.en_US
dc.identifier.issn2949-8554
dc.identifier.other10.1016/j.jai.2024.03.003
dc.identifier.urihttp://hdl.handle.net/2263/101628
dc.language.isoenen_US
dc.publisherKeAi Communicationsen_US
dc.rights© 2024 The Authors. This is an open access article under the CC BY-NC-ND license.en_US
dc.subjectCoal mineen_US
dc.subjectTruck fleeten_US
dc.subjectCarbon emissionen_US
dc.subjectOptimal decarbonisation pathwayen_US
dc.subjectSDG-07: Affordable and clean energyen_US
dc.subjectSDG-09: Industry, innovation and infrastructureen_US
dc.subjectSDG-12: Responsible consumption and productionen_US
dc.titleOptimal decarbonisation pathway for mining truck fleetsen_US
dc.typeArticleen_US

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