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.

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Fig. 4

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

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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)

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Fig. 2

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

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Fig. 1

Simple cycles for preliminary investigation

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Fig. 5

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

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Fig. 8

Evolution of each candidate solution after 50 generations for case 1

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Fig. 9

The best solutions in each generation for cases 1 to 3

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Fig. 10

Relationships between overall efficiency, final feedwater temperature and feedwater number

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Fig. 6

Schematic representation of the DE algorithm

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Fig. 11

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

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Fig. 12

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

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Fig. 13

Statistical optimal reheat pressure ratios of zone A and C

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Fig. 14

Optimal reheat pressures of type1 varying with the throttle pressure



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