Optimization on process parameters of TEG dehydration based on PSO algorithm

At present, many researchers have developed a lot of optimization improvement on TEG dehydration process. However, it is difficult for common software simulation or experimental method conducted in the field to achieve the expected improvement efficiently and accurately. Moreover, unnecessary energy waste was resulted from human factors. Based on above problems, an optimization method combining Particle Swarm Optimization (PSO) algorithm and HYSYS simulation software was put forward. Through the connection between Matlab and HYSYS, PSO could be applied to automatically updating optimal variables which were getting close to the optimal value, in order to obtain the final optimization objective. The proposed method not only enhanced optimization efficiency but also strengthened the system reliability by avoiding the influence of human factors. In the end, the method was used in a case study which aimed to minimize energy consumption of dehydration, and the TEG circulation volume and regeneration tower temperature were decided as decision variables. Taking the HYSYS as the calculation core, PSO was utilized to work out the process parameters with minimum energy consumption. The results showed that TEG circulation volume and reboiler temperature decreased by 0.2 m³/h and 6 ℃ respectively. And the total energy consumption of the system was reduced by 93.8 kW. The optimization method could offer instructions for process operating and parameters setting, which played a significance role in the economic benefits improvement for the oil and gas fields.