Optimization‐based process synthesis under seasonal and daily variability: Application to concentrating solar power

We propose an optimization‐based framework for process synthesis under variability in two frequencies. Low‐frequency variability is represented through scenarios and high‐frequency variability is modeled using modes. The proposed framework allows for the selection of different process configurations...

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Veröffentlicht in:AIChE journal Jg. 65; H. 7
Hauptverfasser: Peng, Xinyue, Root, Thatcher W., Maravelias, Christos T.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York American Institute of Chemical Engineers 01.07.2019
Schlagworte:
Energy storage
mixed‐integer nonlinear programming
Optimization
Organic chemistry
Power plants
Solar energy
Solar power plants
stochastic programming
superstructure‐based process synthesis
Synthesis
ISSN:0001-1541, 1547-5905
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Zusammenfassung:We propose an optimization‐based framework for process synthesis under variability in two frequencies. Low‐frequency variability is represented through scenarios and high‐frequency variability is modeled using modes. The proposed framework allows for the selection of different process configurations during different modes, a feature necessary to model systems under wide high frequency variability (e.g., solar‐based technologies). The optimization problem is formulated as a two‐stage stochastic programming model with mode subproblems nested inside each scenario. The proposed framework is applied to the design of concentrating solar power plants with thermochemical energy storage, leading to the formulation of a computationally efficient model, as well as the identification of a superior design. © 2018 American Institute of Chemical Engineers AIChE J, 65: e16458 2019
Bibliographie:ObjectType-Article-1
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ISSN:0001-1541
1547-5905
DOI:10.1002/aic.16458