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Multi-objective Process Parameter Optimization of Integrated SCV-IFV LNG Regasification System Using Genetic Algorithm
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DOI：10.1007/s11814-025-00622-x.png)
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Abstract
En 中文
LNG regasification technology in natural gas applications mostly involves vaporizers heating liquefied natural gas and converting it into gaseous natural gas. Accurate evaluation of heat transfer characteristics is of great value for the optimal design of advanced regasification devices such as submerged combustion vaporizer (SCV) and intermediate fluid vaporizer (IFV). It is observed that the submerged combustion vaporizer (SCV) system has the problems of high energy demand and high operating cost. In contrast, the intermediate fluid vaporizer (IFV) system has lower energy consumption and cost, but is greatly affected by environmental factors. Considering the advantages and disadvantages of these two methods, this paper proposes a hybrid operation method combining IFV and SCV to reduce the energy consumption and operation cost of LNG regasification. In addition, the process simulation model is established by HYSYS software, and combined with genetic algorithm, some operating parameters are optimized by using unit energy consumption, unit cost and total natural gas output as objective functions. The results show that the combination of IFV and SCV can significantly reduce energy consumption and cost compared with the use of SCV alone. This study provides a new idea for understanding the LNG regasification system and provides a reference for the efficient operation of SCV and IFV.
Keywords:
LNG regasification
Submerged combustion vaporizer
Intermediate fluid vaporizer
Hybrid operation mode
Energy consumption optimization