Fuzzy optimization of multi-period carbon capture and storage systems with parametric uncertainties |
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| Institution: | 1. Chemical Engineering Department, De La Salle University, 2401 Taft Avenue, Malate, Manila, 1004, Philippines;2. Center for Engineering and Sustainable Development Research, De La Salle University, Manila, 1004, Philippines;1. Department of Industrial Engineering, Faculty of Mechanical Engineering, University of Yildiz Technical, 34349 Yildiz, Istanbul, Turkey;2. ASAP Research Group, School of Computer Science, University of Nottingham, NG8 1BB Nottingham, UK;1. Department of Energy Science and Engineering, Indian Institute of Technology, Bombay, Powai, Mumbai 400076, India;2. Department of Chemical and Environmental Engineering/Centre of Excellence for Green Technologies University of Nottingham Malaysia, Broga Road, 43500 Semenyih, Selangor, Malaysia;3. Chemical Engineering Department, De La Salle University, Manila, 2401 Taft Avenue, 1004 Manila, Philippines;1. Centre of Excellence for Green Technologies/Department of Chemical and Environmental Engineering, University of Nottingham Malaysia, Broga Road, 43500 Semenyih, Selangor, Malaysia;2. Center for Engineering and Sustainable Development Research/Chemical Engineering Department, De La Salle University, 2401 Taft Avenue, 1004 Manila, Philippines;1. Center for Engineering and Sustainable Development Research, De La Salle University, 2401 Taft Avenue, 0922 Manila, Philippines;2. Chemical Engineering Department, De La Salle University, 2401 Taft Avenue, 0922 Manila, Philippines;3. Biology Department, De La Salle University, 2401 Taft Avenue, 0922 Manila, Philippines;4. Chemistry Department, De La Salle University, 2401 Taft Avenue, 0922 Manila, Philippines |
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| Abstract: | Carbon capture and storage (CCS) is an important technology option for reducing industrial greenhouse gas emissions. In practice, CO2 sources are easy to characterize, while the estimation of relevant properties of storage sites, such as capacity and injection rate limit (i.e., injectivity), is subject to considerable uncertainty. Such uncertainties need to be accounted for in planning CCS deployment on a large scale for effective use of available storage sites. In particular, the uncertainty introduces technical risks that may result from overestimating the limits of given storage sites. In this work, a fuzzy mixed integer linear program (FMILP) is developed for multi-period CCS systems, accounting for the technical risk arising from uncertainties in estimates of sink parameters, while still attaining satisfactory CO2 emissions reduction. In the model, sources are assumed to have precisely known CO2 flow rates and operating lives, while geological sinks are characterized with imprecise fuzzy capacity and injectivity data. Three case studies are then presented to illustrate the model. Results of these examples illustrate the tradeoff inherent in planning CCS systems under parametric uncertainty. |
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| Keywords: | Carbon capture and storage Technical risk Fuzzy mixed integer linear programming Data uncertainty Source-sink matching Optimization |
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