Research Papers: Energy Conversion/Systems

Systematic Optimization of the Design of Steam Cycles Using MINLP and Differential Evolution

[+] Author and Article Information
Ligang Wang

School of Energy, Power and
Mechanical Engineering,
North China Electric Power University,
Beinong Rd 2,
Beijing 102206, China
Institut für Energietechnik,
Technische Universität Berlin,
Marchstraße 18,
Berlin 10587, Germany

Yongping Yang

School of Energy, Power and
Mechanical Engineering,
North China Electric Power University,
Beinong Rd 2,
Beijing 102206, China
e-mail: yyp@ncepu.edu.cn

Changqing Dong

School of Energy, Power and
Mechanical Engineering,
North China Electric Power University,
Beinong Rd 2,
Beijing 102206, China

Tatiana Morosuk

Institut für Energietechnik,
Technische Universität Berlin,
Marchstraße 18,
Berlin 10587, Germany

George Tsatsaronis

Institut für Energietechnik,
Technische Universität Berlin,
Marchstraße 18,
Berlin 10587, Germany
e-mail: georgios.tsatsaronis@tu-berlin.de

1Corresponding author.

Contributed by the Advanced Energy Systems Division of ASME for publication in the JOURNAL OF ENERGY RESOURCES TECHNOLOGY. Manuscript received June 18, 2013; final manuscript received December 12, 2013; published online March 4, 2014. Assoc. Editor: S. O. Bade Shrestha.

J. Energy Resour. Technol 136(3), 031601 (Mar 04, 2014) (12 pages) Paper No: JERT-13-1186; doi: 10.1115/1.4026268 History: Received June 18, 2013; Revised December 12, 2013

The process synthesis and design optimization of energy conversion systems can be modeled as a mixed integer nonlinear programming (MINLP) problem. The nonconvexity potential and the combinatorial nature of the objective functions and constraints largely suggest the application of heuristic search methods for global optimization. In this paper, a modified differential evolutionary algorithm is applied to a MINLP problem for optimizing the design of steam cycles based on a complex superstructure, containing a variable number and varying positions of reheatings, varying layouts of the feedwater preheating train, and a boiler feedpump turbine with steam extractions. The energy-savings potential from the existing system design was studied. The optimization of a 262 bar/600 °C/ 605 °C unit with a single reheat shows that an efficiency improvement between 0.55 percentage points (PP) and 1.28 PP can be achieved. The optimal design of steam cycles over 650 °C was found to be different from those of the designs under current steam conditions: a transition throttle pressure, above which the benefits of steam temperature elevation can be completely realized, is critical and, accordingly, three design zones associated with the match of throttle pressure and the steam temperature level are clearly identified with recommended ranges of reheat pressures.

Copyright © 2014 by ASME
Your Session has timed out. Please sign back in to continue.


International Energy Agency, Organisation for Economic Co-operation and Development, World Energy Outlook 2010, retrieved on May 30, 2012 from www.iea.org/Textbase/npsum/weo2010sum.pdf.
BP Company, BP Statistical Review of World Energy2011, retrieved on May 30, 2012 from www.bp.com.
Yang, Y., Guo, X., and Wang, N., 2010, “Power Generation From Pulverized Coal in China,” Energy35(11), pp. 4336–4348. [CrossRef]
Ruth, L. A., 2000, “Advanced Coal-Fired Power Plants,” ASME J. Energy Resour. Technol., 123(1), pp. 4–9. [CrossRef]
Bugge, J., Kjaer, S., and Blum, R., 2006, “High-Efficiency Coal-Fired Power Plants Development and Perspectives,” Energy31(10–11), pp. 1437–1445. [CrossRef]
Espatolero, S., Cortos, C., and Romeo, L. M., 2010, “Optimization of Boiler Cold-End and Integration With The Steam Cycle in Supercritical Units,” Appl. Energy87(5), pp. 1651–1660. [CrossRef]
European AD700 project, https://projectweb.elsam-eng.com/AD700/default.aspx (accessed on Oct 25, 2012).
Fukuda, Y., 2010, “Development of Advanced Ultra Supercritical Fossil Power Plants in Japan: Materials and High Temperature Corrosion Properties,” Mater. Sci. Forum, 696, pp. 236–241. [CrossRef]
Weitzel, P., 2011, “Steam Generator for Advanced Ultra-Supercritical Power Plants 700 to 760c,” ASME 2011 Power Conference, Denver, CO.
Silvestri, G. J., Bannister, R. L., Fujikawa, T., and Hizume, A., 1992, “Optimization of Advanced Steam Condition Power Plants,” ASME J. Eng. Gas Turbines Power114(4), pp. 612–620. [CrossRef]
Silvestri, G. J., 1995, “Boiler Feedpump Turbine Drive/Feedwater Train Arrangement,” U.S. Patent No 5404724.
Kjaer, S., 2009, Steam Turbine System, U.S. Patent No 7607304B2.
Kjaer, S., and Drinhaus, F., 2010, “A Modified Double Reheat Cycle,” ASME Conf. Proc., 2010(49354), pp. 285–293.
Weir, C. D., 1960, “Optimization of Heater Enthalpy Rises in Feed-Heating Trains,” Proc. Inst. Mech. Eng., 174(1), pp. 769–796. [CrossRef]
Grkovic, V., 1990, “Selection of the Optimal Extraction Pressure for Steam From a Condensation-Extraction Turbine,” Energy, 15(5), pp. 459–465. [CrossRef]
Papoulias, S. A., and Grossmann, I. E., 1983, “A Structural Optimization Approach in Process Synthesis—I: Utility Systems,” Comput. Chem. Eng., 7(6), pp. 695–706. [CrossRef]
Papoulias, S. A. and Grossmann, I. E., 1983, “A Structural Optimization Approach in Process Synthesis—II: Heat Recovery Networks,” Comput. Chem. Eng., 7(6), pp. 707–721. [CrossRef]
Floudas, C. A., 1995, Nonlinear and Mixed-Integer Optimization: Fundamentals and Applications, Oxford University Press, New York.
General Algebraic Modeling System (GAMS), www.gams.com/default.htm (accessed on Oct 25, 2012).
Bussieck, M. R., and Vigerske, S., 2010, “MINLP Solver Software,” Wiley Encyclopedia of Operations Research and Management Science, Cochran, J. J., Cox, L. A., Keskinocak, P., Kharoufeh, J. P., and Smith, J. C., eds. Wiley, Chichester, UK.
Ahadi-Oskui, T., Alperin, H., Nowak, I., Cziesla, F., and Tsatsaronis, G., 2006, “A Relaxation-Based Heuristic for the Design of Cost-Effective Energy Conversion Systems,” Energy31(10–11), pp. 1346–1357. [CrossRef]
Ahadi-Oskui, T., Vigerske, S., Nowak, I., and Tsatsaronis, G., 2010, “Optimizing the Design of Complex Energy Conversion Systems by Branch and Cut,” Comput. Chem. Eng34(8), pp. 1226–1236. [CrossRef]
Tabkhi, F., Pibouleau, L., Azzaro-Pantel, C., and Domenech, S., 2009, “Total Cost Minimization of a High-Pressure Natural Gas Network,” ASME J. Energy Resour. Technol., 131(4), p. 043002. [CrossRef]
Luo, X., Zhang, B., Chen, Y., and Mo, S., 2011, “Modeling and Optimization of a Utility System Containing Multiple Extractions Steam Turbines,” Energy, 36(5), pp. 3501–3512. [CrossRef]
Luo, X., Zhang, B., Chen, Y., and Mo, S., 2012, “Operational Planning Optimization of Multiple Interconnected Steam Power Plants Considering Environmental Costs,” Energy, 37(1), pp. 549–561. [CrossRef]
Manassaldi, J. I., Mussati, S. F., and Scenna, N. J., 2011, “Optimal Synthesis and Design of Heat Recovery Steam Generation (HRSG) Via Mathematical Programming,” Energy, 36(1), pp. 475–485. [CrossRef]
Frangopoulos, C. A., 2003, Methods of Energy Systems Optimization, Summer School: Optimization of Energy Systems and Processes , Gliwice, Poland.
Cammarata, G., Fichera, A., and Marletta, L., 1998, “Using Genetic Algorithms and the Exergonomic Approach to Optimize District Heating Networks,” ASME J. Energy Resour. Technol., 120(3), pp. 241–246. [CrossRef]
Ilamathi, P., Selladurai, V., and Balamurugan, K., 2013, “Modeling and Optimization of Unburned Carbon in Coal-Fired Boiler Using Artificial Neural Network and Genetic Algorithm,” ASME J. Energy Resour. Technol., 135(3), p. 032201. [CrossRef]
Vasquez Padilla, R., Ramos Archibold, A., Goswami, D. Y., Rahman, M. M., Demirkaya, G., Besarati, S., and Stefanakos, E. L., 2012, “Multi-Objective Optimization of a Combined Power and Cooling Cycle for Low-Grade and Midgrade Heat Sources,” ASME J. Energy Resour. Technol., 134(3), p. 032002. [CrossRef]
Soares, J., Silva, M., Sousa, T., Vale, Z., and Morais, H., 2012, “Distributed Energy Resource Short-Term Scheduling Using Signaled Particle Swarm Optimization,” Energy, 42(1), pp. 466–476. [CrossRef]
Zhang, Z., Zeng, Y., and Kusiak, A., 2012, “Minimizing Pump Energy in a Wastewater Processing Plant,” Energy, 47(1), pp. 505–514. [CrossRef]
Angira, R. and Babu, B., 2006, “Optimization of Process Synthesis and Design Problems: A Modified Differential Evolution Approach,” Chem. Eng. Sci., 61(14), pp. 4707–4721. [CrossRef]
Differential Evolution Homepage, www.icsi.berkeley.edu/storn/code.html (accessed on April 20, 2012).
Babu, B. and Angira, R., 2006, “Modified Differential Evolution (mde) for Optimization of Non-Linear Chemical Processes,” Comput. Chem. Eng., 30(6), pp. 989–1002. [CrossRef]
Amjady, N. and Sharifzadeh, H., 2011, “Security Constrained Optimal Power Flow Considering Detailed Generator Model by a New Robust Differential Evolution Algorithm,” Electr. Power Syst. Res., 81(2), pp. 740–749. [CrossRef]
Zhang, H. and Rangaiah, G., 2012, “An Efficient Constraint Handling Method With Integrated Differential Evolution For Numerical and Engineering Optimization,” Comput. Chem. Eng., 37(0), pp. 74–88. [CrossRef]
Habib, M., Said, S., and Al-Zaharna, I., 1995, “Optimization of Reheat Pressures in Thermal Power Plants,” Energy, 20(6), pp. 555–565. [CrossRef]
EBSILON Professional 10 by STEAG Energy Services GmbH, Germany, www.ebsilon.com (accessed on Oct 25, 2012).


Grahic Jump Location
Fig. 1

Simple cycles for preliminary investigation

Grahic Jump Location
Fig. 2

Effect of pressures on plant efficiency (this figure was obtained for tms = 600 °C and pms = 262 bar based on Fig. 1)

Grahic Jump Location
Fig. 3

Effect of reheat temperature on efficiency and steam quality at the steam turbine outlet (this figure was obtained for tms = 600 °C and pms = 262 bar based on Fig. 1)

Grahic Jump Location
Fig. 4

Logic of stream path formation via the four switches (Ii: ith incoming stream; Oi: ith outgoing stream)

Grahic Jump Location
Fig. 5

The superstructure considering double reheats, up to 10 preheaters and an ET

Grahic Jump Location
Fig. 6

Schematic representation of the DE algorithm

Grahic Jump Location
Fig. 8

Evolution of each candidate solution after 50 generations for case 1

Grahic Jump Location
Fig. 9

The best solutions in each generation for cases 1 to 3

Grahic Jump Location
Fig. 10

Relationships between overall efficiency, final feedwater temperature and feedwater number

Grahic Jump Location
Fig. 11

Optimal efficiency for different steam conditions under the constraint type1 and type2 for xex,MT

Grahic Jump Location
Fig. 12

Optimal efficiency differences from the two constraints and optimal reheat pressures of type2 varying with the throttle pressure

Grahic Jump Location
Fig. 13

Statistical optimal reheat pressure ratios of zone A and C

Grahic Jump Location
Fig. 14

Optimal reheat pressures of type1 varying with the throttle pressure




Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging and repositioning the boxes below.

Related Journal Articles
Related eBook Content
Topic Collections

Sorry! You do not have access to this content. For assistance or to subscribe, please contact us:

  • TELEPHONE: 1-800-843-2763 (Toll-free in the USA)
  • EMAIL: asmedigitalcollection@asme.org
Sign In