Simultaneous Synthesis Of Heat Exchanger Network Based On Improved Quantum Particle Swarm Optimization Algorithm And Stream Optimization

Since the global energy crisis happened from last century, countries in the world pay more attention to energy development utilization and impact on the environment. In the process of use of energy, heat exchanger network structure and the process optimized degree affect the energy utilization and investment, thus optimizing heat exchanger network and operation is important to the energy saving of industrial processes. In this paper, heat exchanger network is optimized based on the improved quantum particle swarm algorithm, and streams involved in the heat exchanger network of atmospheric tower is also optimized.Firstly, mathematical model of heat exchanger network was established based on superstructure model, one allowed stream split and another not allowed. Based on the study of wolves algorithm, improved research is made on quantum particle swarm optimization. Based on the superstructure model with non-isothermal mixing of split stream, a two-level approach combined with improved quantum-behaved particle swarm optimization (IQPSO) algorithm is proposed to find the optimum structure with a minimum annual cost. In the upper level, IQPSO is utilized to generate the structure of the network, while in the lower level, split-stream fractions and heat load of exchangers are optimized by IQPSO. Benchmark problems are solved and results show that the two level improved quantum particle swarm algorithm is feasible and effective for heat exchanger network problems. Further, improved quantum particle swarm optimization is applied to simultaneous synthesis problem of heat exchanger network with no stream splitted, which aims at getting a suitable structure with optimal annual cost. Variables of heat exchanger network structure and heat load variables are generated at the same time. The heat exchanger network with no stream splitted is less complex compared with the model with stream splitted and the former needs less solving time. Three typical examples verified the effectiveness of the method.Finally, streams in the heat exchanger network is optimized. In this paper, efficient global optimization algorithm based on surrogate model is applied to optimization of atmospheric tower’s heat recovery. Kriging surrogate model is used as a replacement to the original model which is time-consuming in iterative optimization process and realizes energy savings and meets product separation accuracy requirements.