Multi-objective optimization of a cryogenic cold energy recovery system for LNG regasification

Abstract

Regasification of LNG for combustion in power plants typically employ seawater as a heat carrier in Open-Rack Vaporizers (ORV), causing much of the cold energy to be lost to the ambient. A comprehensive literature review shows that, thus far, no studies have been conducted to simultaneously consider the impacts of the exergy, economy and environment in the optimal design of a hybrid LNG recovery system. This paper aims to address this knowledge gap by establishing a multi-objective optimization model for a novel cascading quad-generation cold energy LNG recovery system. Single- and multi-objective optimizations based on Fuzzy method and Pareto optimal method are carried out on the proposed system to obtain the optimal operating parameters and component sizing, as well as the corresponding performances for each condition. The optimal sizing for each stage is computed for the maximizing of exergy efficiency and CO2 savings rate, and the minimizing of capital cost. The exergy efficiency obtained from the triple-objective optimization yields 12.3% improvement compared to the best result from the single-objective optimization with a 5 kg/s LNG mass flow rate. In addition, when the LNG mass flow is larger than 1 kg/s, the maximized exergy efficiency remains constant (around 0.13) with increasing LNG mass flow rate while the maximized CO2 emission reduction rate and minimized total cost per year increase linearly with the LNG mass flow rate. It has been demonstrated in this work that the system is able to maintain consistency in performance for the optimal design conditions over a wide range of LNG demands and hence good scalability for possible industrial and commercial settings.