Multi-objective optimization of utility systems and heat exchanger networks: method and application to the solar assisted hydrothermal gasification case

This work presents a novel framework for the multi-objective synthesis of utility systems and Heat Exchanger Networks (HEN) under single or multi-period operations. In order to solve the resulting Mixed Integer Non Linear (MINLP) programming problem, a bi-level approach is proposed to optimize process and utility systems design, utility scheduling, as well as Heat Exchanger Network Synthesis (HENS), including thermal storage. At the upper level the derivative free Queuing Multi Objective Optimization (QMOO) algorithm proposed by Molyneaux et al. (2001) is used to optimize process and utility design variables as well as Heat Exchanger Network design variables with respect to multiple competing objectives. At the lower level, first the process and utility systems are simulated with Belsim Vali, then the sequential algorithm proposed by Mian et al. (2016a), Mian et al. (2016b) is used to optimize the utility scheduling and the HEN configuration for multi-period operations. The proposed framework is applied to the Multi-objective synthesis of solar-assisted catalytic hydrothermal gasification problem. The plant consists of a catalytic hydrothermal gasification (CHTG) process including a thermal solar concentrator, a photovoltaic field and a high temperature thermal storage utility.