Optimization of triple-pressure combined-cycle power plants by generalized disjunctive programming and extrinsic functions
| Autor: | Nicolás J. Scenna, Miguel C. Mussati, Sergio Fabian Mussati, Juan Ignacio Manassaldi |
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| Rok vydání: | 2021 |
| Předmět: |
Mathematical optimization
Work (thermodynamics) Series (mathematics) Combined cycle 020209 energy General Chemical Engineering Process (computing) 02 engineering and technology Computer Science Applications Power (physics) law.invention 020401 chemical engineering law Heat transfer Heat exchanger 0202 electrical engineering electronic engineering information engineering 0204 chemical engineering Representation (mathematics) Mathematics |
| Zdroj: | Computers & Chemical Engineering. 146:107190 |
| ISSN: | 0098-1354 |
| DOI: | 10.1016/j.compchemeng.2020.107190 |
| Popis: | A new mathematical framework for optimal synthesis, design, and operation of triple-pressure steam-reheat 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. |
| Databáze: | OpenAIRE |
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