Design optimization of single mixed refrigerant LNG process using a hybrid modified coordinate descent algorithm

• Published in: Cryogenics (Guildford) Vol. 89; pp. 131 - 140
• Main Authors: Qyyum, Muhammad Abdul, Long, Nguyen Van Duc, Minh, Le Quang, Lee, Moonyong
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier Ltd 01.01.2018; Elsevier BV
• Subjects: Algorithms; Descent; Design modifications; Design optimization; Energy conservation; Energy efficiency; Exergy loss analysis; Hybrid modified coordinate descent optimization; Liquefaction; Liquefied natural gas; LNG; Mathematical models; Natural gas; Natural gas industry; Natural gas liquefaction; Refrigerants; Single-mixed refrigerant; Visual programming languages; Hybrid modified coordinate descent optimization; Natural gas liquefaction; LNG; Single-mixed refrigerant; Design optimization; Exergy loss analysis
• ISSN: 0011-2275; 1879-2235
• DOI: 10.1016/j.cryogenics.2017.12.005

[Display omitted] •A hybrid modified coordinate descent algorithm is proposed for LNG process.•An optimal design of SMR process is presented.•The compression energy for NG liquefaction is reduced up to 44.3%.•The coefficient of performance (COP) of SMR cycle is improved up to 34.7%.•Exergy loss analysis of optimized SMR process is performed. Design optimization of the single mixed refrigerant (SMR) natural gas liquefaction (LNG) process involves highly non-linear interactions between decision variables, constraints, and the objective function. These non-linear interactions lead to an irreversibility, which deteriorates the energy efficiency of the LNG process. In this study, a simple and highly efficient hybrid modified coordinate descent (HMCD) algorithm was proposed to cope with the optimization of the natural gas liquefaction process. The single mixed refrigerant process was modeled in Aspen Hysys® and then connected to a Microsoft Visual Studio environment. The proposed optimization algorithm provided an improved result compared to the other existing methodologies to find the optimal condition of the complex mixed refrigerant natural gas liquefaction process. By applying the proposed optimization algorithm, the SMR process can be designed with the 0.2555 kW specific compression power which is equivalent to 44.3% energy saving as compared to the base case. Furthermore, in terms of coefficient of performance (COP), it can be enhanced up to 34.7% as compared to the base case. The proposed optimization algorithm provides a deep understanding of the optimization of the liquefaction process in both technical and numerical perspectives. In addition, the HMCD algorithm can be employed to any mixed refrigerant based liquefaction process in the natural gas industry.