Optimization of triple-pressure combined-cycle power plants by generalized disjunctive programming and extrinsic functions.
Date
2021-02-01
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Abstract
A new mathematical framework for optimal synthesis, design, and operation of triple-pressure steamreheat combined-cycle power plants (CCPP) is presented. A superstructure-based representation of the
process, which embeds a large number of candidate configurations, is first proposed. Then, a generalized
disjunctive programming (GDP) mathematical model is derived from it. Series, parallel, and combined
series-parallel arrangements of heat exchangers are simultaneously embedded. Extrinsic functions
executed outside GAMS from dynamic-link libraries (DLL) are used to estimate the thermodynamic
properties of the working fluids. As a main result, improved process configurations with respect to two
reported reference cases were found. The total heat transfer areas calculated in this work are by around
15% and 26% lower than those corresponding to the reference cases.
This paper contributes to the literature in two ways: (i) with a disjunctive optimization model of natural gas CCPP and the corresponding solution strategy, and (ii) with improved HRSG configurations.
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Keywords
GAMS, Generalized disjunctive programming, Extrinsic functions, Three-pressure reheat combined-cycle power plant, Heat recovery steam generator HRSG
Citation
Computers & Chemical Engineering, 146, 107190.
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