期刊
JOURNAL OF CLEANER PRODUCTION
卷 142, 期 -, 页码 3419-3436出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.jclepro.2016.10.124
关键词
Raw natural gas; Retrofit; Optimization; Mixed-integer nonlinear programming; Process modeling; Utility system
资金
- National Natural Science Foundation of China [21376277, 21276288]
- project of Guangdong Provincial Natural Science Foundation of China [2015A030313112]
The demand for natural gas is increasing in the energy market because of its lower emissions and sustainable development. This increasing demand for natural gas promotes the capacity expansion of raw natural gas refining systems (RNGRSs), resulting in parallel refining processes in a RNGRS. Optimizing the material stream network between these refining processes is very challenging because of the complex thermodynamics, unit operations and utility configurations. An optimization framework is presented for the retrofit of the material stream network between these refining processes to improve the economic performance. The retrofit framework integrates raw natural gas supply, refining processes, utility subsystems and product delivery and is formulated as a mixed-integer nonlinear programming (MINLP) optimization model to obtain an optimal material stream network to increase profit. The model presented here is applied to a Chinese industrial RNGRS and results in an optimal retrofit. A comparison before and after the retrofit demonstrates a significant increase in profit. Crown Copyright (C) 2016 Published by Elsevier Ltd on behalf of The Royal College of Radiologists. All rights reserved.
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