Working fluid selection for organic rankine cycles via deterministic global optimization of design and operation

DOI10.1007/s11081-019-09454-1zbMath1447.90058OpenAlexW2963448122WikidataQ127448191 ScholiaQ127448191MaRDI QIDQ779765

Artur M. Schweidtmann, Wolfgang R. Huster, Alexander Mitsos

Publication date: 14 July 2020

Published in: Optimization and Engineering (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11081-019-09454-1

zbMATH Keywords

multiobjective optimizationhybrid modelingartificial neural networkswaste heat recoveryMAiNGOthermoeconomic optimization

Mathematics Subject Classification ID

Applications of mathematical programming (90C90) Multi-objective and goal programming (90C29) Learning and adaptive systems in artificial intelligence (68T05)

Related Items (1)

Optimizing design and dispatch of a renewable energy system with combined heat and power

Uses Software

• libMC
• ANTIGONE
• MC++
• Refprop
• CoolProp
• MAiNGO

Cites Work

• Unnamed Item
• Convergence analysis of multivariate McCormick relaxations
• Deterministic global optimization of process flowsheets in a reduced space using McCormick relaxations
• Deterministic global optimization with artificial neural networks embedded
• A polyhedral branch-and-cut approach to global optimization
• ANTIGONE: algorithms for coNTinuous/Integer global optimization of nonlinear equations
• McCormick-Based Relaxations of Algorithms

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