论文部分内容阅读
Liquefied natural gas(LNG) is the most economical way of transporting natural gas(NG) over long distances. Liquefaction of NG using vapor compression refrigeration system requires high operating and capital cost. Due to lack of systematic design methods for multistage refrigeration cycles, conventional approaches to determine optimal cycle are largely trial-and-error. In this paper a novel mixed integer non-linear programming(MINLP)model is introduced to select optimal synthesis of refrigeration systems to reduce both operating and capital costs of an LNG plant. Better conceptual understanding of design improvement is illustrated on composite curve(CC) and exergetic grand composite curve(EGCC) of pinch analysis diagrams. In this method a superstructure representation of complex refrigeration system is developed to select and optimize key decision variables in refrigeration cycles(i.e. partition temperature, compression configuration, refrigeration features, refrigerant flow rate and economic trade-off). Based on this method a program(LNG-Pro) is developed which integrates VBA,Refprop and Excel MINLP Solver to automate the methodology. Design procedure is applied on a sample LNG plant to illustrate advantages of using this method which shows a 3.3% reduction in total shaft work consumption.
Liquefied natural gas (LNG) is the most economical way of transporting natural gas (NG) over long distances. Liquefaction of NG using vapor compression refrigeration system requiring high operating and capital cost. Due to lack of systematic design methods for multistage refrigeration cycles, conventional approaches to determine optimal cycle are substantial trial-and-error. In this paper a novel mixed integer non-linear programming (MINLP) model is introduced to select optimal synthesis of refrigeration systems to reduce both operating and capital costs of an LNG plant. conceptual understanding of design improvement is illustrated on composite curve (CC) and exergetic grand composite curve (EGCC) of pinch analysis diagrams. In this method a superstructure representation of complex refrigeration system is developed to select and optimize key decision variables in refrigeration cycles (ie partition temperature, compression configuration, refrigeration features, refrigerant flow rate and ec onomic trade-off). Based on this method a program (LNG-Pro) is developed which integrates VBA, Refprop and Excel MINLP Solver to automate the methodology. Design procedure is applied on a sample LNG plant to illustrate advantages of using this method which shows a 3.3% reduction in total shaft work consumption.