Single-Solution-Based Vortex Search Strategy for Optimal Design of Offshore and Onshore Natural Gas Liquefaction Processes

• Published in: Energies (Basel) Vol. 13; no. 7; p. 1732
• Main Authors: Qyyum, Muhammad Abdul, Yasin, Muhammad, Nawaz, Alam, He, Tianbiao, Ali, Wahid, Haider, Junaid, Qadeer, Kinza, Nizami, Abdul-Sattar, Moustakas, Konstantinos, Lee, Moonyong
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.04.2020
• Subjects: Algorithms; compression power; Computer simulation; Condensing; Design; Design optimization; Energy consumption; Energy efficiency; Genetic algorithms; Linear programming; Liquefaction; liquefaction process; Liquefied natural gas; Natural gas; Offshore engineering; Optimization; Optimization algorithms; Phase transitions; propane-precooled mixed refrigerant; Refrigerants; Simulation; single mixed refrigerant; Vortices
• ISSN: 1996-1073; 1996-1073
• DOI: 10.3390/en13071732

Propane-Precooled Mixed Refrigerant (C3MR) and Single Mixed Refrigerant (SMR) processes are considered as optimal choices for onshore and offshore natural gas liquefaction, respectively. However, from thermodynamics point of view, these processes are still far away from their maximum achievable energy efficiency due to nonoptimal execution of the design variables. Therefore, Liquefied Natural Gas (LNG) production is considered as one of the energy-intensive cryogenic industries. In this context, this study examines a single-solution-based Vortex Search (VS) approach to find the optimal design variables corresponding to minimal energy consumption for LNG processes, i.e., C3MR and SMR. The LNG processes are simulated using Aspen Hysys and then linked with VS algorithm, which is coded in MATLAB. The results indicated that the SMR process is a potential process for offshore sites that can liquefy natural gas with 16.1% less energy consumption compared with the published base case. Whereas, for onshore LNG production, the energy consumption for the C3MR process is reduced up to 27.8% when compared with the previously published base case. The optimal designs of the SMR and C3MR processes are also found via distinctive well-established optimization approaches (i.e., genetic algorithm and particle swarm optimization) and their performance is compared with that of the VS methodology. The authors believe this work will greatly help the process engineers overcome the challenges relating to the energy efficiency of LNG industry, as well as other mixed refrigerant-based cryogenic processes.