Synthesis and optimization of utility system using parameter adaptive differential evolution algorithm

doi:10.1016/j.cjche.2015.01.013

Chin.J.Chem.Eng. ›› 2015, Vol. 23 ›› Issue (8): 1350-1356.DOI: 10.1016/j.cjche.2015.01.013

• PROCESS SYSTEMS ENGINEERING • Previous Articles Next Articles

Synthesis and optimization of utility system using parameter adaptive differential evolution algorithm

Zeqiu Li, Wenli Du, Liang Zhao, Feng Qian

Key Laboratory of Advanced Control and Optimization for Chemical Process, Ministry of Education, East China University of Science and Technology, Shanghai 200237, China

Received:2014-09-03 Revised:2015-01-30 Online:2015-09-26 Published:2015-08-28
Contact: Liang Zhao, Feng Qian
Supported by:
Supported by the Major State Basic Research Development Program of China (2012CB720500), the National Natural Science Foundation of China (U1162202, 61222303), the National Science Foundation of Shanghai (14ZR1410000),Shanghai R&D Platform Construction Program (13DZ2295300), Shanghai Rising-Star Program (13QH1401200) and Shanghai Leading Academic Discipline Project (B504).

Synthesis and optimization of utility system using parameter adaptive differential evolution algorithm

Zeqiu Li, Wenli Du, Liang Zhao, Feng Qian

Key Laboratory of Advanced Control and Optimization for Chemical Process, Ministry of Education, East China University of Science and Technology, Shanghai 200237, China

通讯作者: Liang Zhao, Feng Qian
基金资助:
Supported by the Major State Basic Research Development Program of China (2012CB720500), the National Natural Science Foundation of China (U1162202, 61222303), the National Science Foundation of Shanghai (14ZR1410000),Shanghai R&D Platform Construction Program (13DZ2295300), Shanghai Rising-Star Program (13QH1401200) and Shanghai Leading Academic Discipline Project (B504).

Abstract

Abstract: Synthesis and optimization of utility system usually involve grassroots design, retrofitting and operation optimization, which should be considered in modeling process. This paper presents a general method for synthesis and optimization of a utility system. In this method, superstructure based mathematical model is established, in which different modeling methods are chosen based on the application. A binary code based parameter adaptive differential evolution algorithm is used to obtain the optimal configuration and operation conditions of the system. The evolution algorithm and models are interactively used in the calculation,which ensures the feasibility of configuration and improves computational efficiency. The capability and effectiveness of the proposed approach are demonstrated by three typical case studies.

Key words: Utility system synthesis, MINLP, Operation optimization

摘要： Synthesis and optimization of utility system usually involve grassroots design, retrofitting and operation optimization, which should be considered in modeling process. This paper presents a general method for synthesis and optimization of a utility system. In this method, superstructure based mathematical model is established, in which different modeling methods are chosen based on the application. A binary code based parameter adaptive differential evolution algorithm is used to obtain the optimal configuration and operation conditions of the system. The evolution algorithm and models are interactively used in the calculation,which ensures the feasibility of configuration and improves computational efficiency. The capability and effectiveness of the proposed approach are demonstrated by three typical case studies.

关键词: Utility system synthesis, MINLP, Operation optimization

Zeqiu Li, Wenli Du, Liang Zhao, Feng Qian. Synthesis and optimization of utility system using parameter adaptive differential evolution algorithm[J]. Chin.J.Chem.Eng., 2015, 23(8): 1350-1356.

Zeqiu Li, Wenli Du, Liang Zhao, Feng Qian. Synthesis and optimization of utility system using parameter adaptive differential evolution algorithm[J]. Chinese Journal of Chemical Engineering, 2015, 23(8): 1350-1356.

References

[1] T. Petroulas, G. Reklaitis, Computer-aided synthesis and design of plant utility systems, AICHE J. 30(1) (1984) 69-78.

[2] S.A. Papoulias, I.E. Grossmann, A structural optimization approach in process synthesis-I:Utility systems, Comput. Chem. Eng. 7(6) (1983) 695-706.

[3] J.C. Bruno, F. Ferrnandez, F. Castells, I.E. Grossmann, A rigorous MINLP model for the optimal synthesis and operation of utility plants, Chem. Eng. Res. Des. 76(3) (1998) 246-258.

[4] I.S. Han, Y.H. Lee, C.H. Han, Modeling and optimization of the condensing steam turbine network of a chemical plant, Ind. Eng. Chem. Res. 45(2) (2006) 670-680.

[5] Z. Li, L. Zhao, W. Du, F. Qian, Modeling and optimization of the steam turbine network of an ethylene plant, Chin. J. Chem. Eng. 21(5) (2013) 520-528.

[6] Y.-C. Lin, K.-S. Hwang, F.-S. Wang, Co-evolutionary hybrid differential evolution for mixed-integer optimization problems, Eng. Optim. 33(6) (2001) 663-682.

[7] H. Schmidt, G. Thierauf, A combined heuristic optimization technique, Adv. Eng. Softw. 36(1) (2005) 11-19.

[8] E. Mezura-Montes, M.E. Miranda-Varela, R. del Carmen Gómez-Ramón, Differential evolution in constrained numerical optimization:An empirical study, Inform. Sci. 180(22) (2010) 4223-4262.

[9] M. Varadarajan, K.S. Swarup, Differential evolution approach for optimal reactive power dispatch, Appl. Soft Comput. 8(4) (2008) 1549-1561.

[10] A. Ponsich, C.A.C. Coello, Differential Evolution performances for the solution of mixed-integer constrained process engineering problems, Appl. Soft Comput. 11(1) (2011) 399-409.

[11] M. Srinivas, G.P. Rangaiah, Differential evolution with tabu list for global optimization and its application to phase equilibrium and parameter estimation problems, Ind. Eng. Chem. Res. 46(10) (2007) 3410-3421.

[12] D. Datta, J.R. Figueira, A real-integer-discrete-coded differential evolution, Appl. Soft Comput. 13(9) (2013) 3884-3893.

[13] Z. Shang, Analysis and Optimisation of Total Site Utility Systems, UMIST, UK, 2000.

[14] P.S. Varbanov, S. Doyle, R. Smith, Modelling and optimization of utility systems, Chem. Eng. Res. Des. 82(5) (2004) 561-578.

[15] Z. Shang, A. Kokossis, A transhipment model for the optimisation of steam levels of total site utility system for multiperiod operation, Comput. Chem. Eng. 28(9) (2004) 1673-1688.

[16] R. Storn, K. Price, Differential Evolution-A Simple and Efficient Adaptive Scheme for Global Optimization Over Continuous Spaces, ICSI, Berkeley, 1995.

[17] F. Neri, V. Tirronen, Recent advances in differential evolution:a survey and experimental analysis, Artif. Intell. Rev. 33(1-2) (2010) 61-106.

[18] J. Zhang, A.C. Sanderson, Adaptive Differential Evolution:A Robust Approach to Multimodal Problem Optimization, Springer, 2009. 46-75.

[19] L. Yiqing, Y. Xigang, L. Yongjian, An improved PSO algorithm for solving non-convex NLP/MINLP problems with equality constraints, Comput. Chem. Eng. 31(3) (2007) 153-162.

[20] J. Lampinen, A constraint handling approach for the differential evolution algorithm, Proceedings of the World Congress on Computational Intelligence 2002, pp. 1468-1473.

Synthesis and optimization of utility system using parameter adaptive differential evolution algorithm

Synthesis and optimization of utility system using parameter adaptive differential evolution algorithm

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