Propane pre-cooled mixed refrigerant (C3-MR) process is the most widely used process for LNG production.Nonlinear optimization of the process depends on process variables and algorithm.The refrigerant components, flow rate and process pressure of the C3-MR process are optimized by HYSYS with particle swarm optimization (PSO) embedded in MATLAB.The results show that optimized parameters in PSO converge after 20 iterations for the C3-MR process.The resultant theoretic energy consumption is lower than that obtained by the sequential quadratic programming method (SQP) and BOX method in reported literatures.%丙烷预冷混合制冷液化流程(C3-MR)在液化天然气生产中应用最广.该流程的优化属于非线性问题,优化结果受到过程变量和算法的影响.基于HYSYS软件模拟,对C3-MR流程用MATLAB嵌入粒子群算法(PSO)优化制冷剂组分、流量以及流程压力以降低过程能耗.研究结果表明,对C3-MR流程使用PSO算法优化迭代20次便收敛,优化后理论能耗低于公开文献报导的序列二次规划(SQP)和BOX方法的结果.
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