Multiparameter optimization of the acid gas removal process using self-heat recuperation technology in IGCC system based on genetic algorithm

Abstract

The acid gas removal (AGR) process in the integrated gasification combined cycle (IGCC) system consumes a large amount of heat and reduces the generation efficiency. Process modification of self-heat recuperation (SHR) technology based on vapor compression heat pumps is expected to reduce the energy consumption of the AGR process. On this basis, this paper conducted a comprehensive and parametric analysis of the AGR process integrated with a vapor compression heat pump. Wherein, two key parameters, the stripper pressure (P1) and the heat pump heat exchanger inlet pressure (P2), were analyzed in detail to understand the energy consumption characteristics of each module of the system. By establishing the optimization objective functions of minimizing system operating cost and exergy loss respectively, the system multi-parameter optimization was conducted based on the genetic algorithm by coding and solving in HYSYS and MATLAB. The corresponding parameter variables for the optimal cases of the two optimization objectives are also comparatively derived. The results showed that P1 mainly changes the SHR capacity of the system by changing the allowable flow rate of the SHR mass under different working conditions, while P2 mainly affects the SHR capacity of the system by changing the heat of the fraction at the top of the stripper. The minimum operating cost of the system decreased to 0.0655 $/kgH2S, which is 1.50% lower compared to the original case. The minimum exergy loss of the system is reduced from 7788.89kW to 7398.59MW, which is about 5.01% lower than that of the original case.