Systematic Methods for Working Fluid Selection and the Design, Integration and Control of Organic Rankine Cycles—A Review

There is a rather recent tendency to define the physical structure and the control structure of a system concurrently when designing the architecture of a product, i.e., to perform codesign. We argue that co-design can only be enabled when the mutual influence between physical system and control is made evident to the designer at an early stage. Though the idea of design integration is not new, to the best of our knowledge, there is no computer tooling that explicitly supports this activity by enabling co-design as stated before. In this paper the authors propose a method for co-design of physical and control architectures as a better approach to design mechatronic systems, allowing to exploit the synergy between software and hardware and detecting certain design problems at an early stage of design. The proposed approach is supported by a set of tools and demonstrated through an example case.

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Heat pump working fluid selection—economic and thermodynamic comparison of criteria and boundary conditions

International Journal of Refrigeration ◽

10.1016/j.ijrefrig.2018.11.034 ◽

2019 ◽

Vol 98 ◽

pp. 500-513 ◽

Cited By ~ 8

Author(s):

Benjamin Zühlsdorf ◽

Jonas Kjær Jensen ◽

Brian Elmegaard

Keyword(s):

Boundary Conditions ◽

Heat Pump ◽

Working Fluid ◽

Working Fluid Selection

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Surrogate Models Applied to Optimized Organic Rankine Cycles

Energies ◽

10.3390/en14248456 ◽

2021 ◽

Vol 14 (24) ◽

pp. 8456

Author(s):

Icaro Figueiredo Vilasboas ◽

Victor Gabriel Sousa Fagundes dos Santos ◽

Armando Sá Ribeiro Júnior ◽

Julio Augusto Mendes da Silva

Keyword(s):

Polynomial Regression ◽

Surrogate Models ◽

Industrial Plant ◽

Computational Time ◽

Working Fluid ◽

Or Efficiency ◽

Specific Cost ◽

Complex Models ◽

Organic Rankine Cycles ◽

Main Components

Global optimization of industrial plant configurations using organic Rankine cycles (ORC) to recover heat is becoming attractive nowadays. This kind of optimization requires structural and parametric decisions to be made; the number of variables is usually high, and some of them generate disruptive responses. Surrogate models can be developed to replace the main components of the complex models reducing the computational requirements. This paper aims to create, evaluate, and compare surrogates built to replace a complex thermodynamic-economic code used to indicate the specific cost (US$/kWe) and efficiency of optimized ORCs. The ORCs are optimized under different heat sources conditions in respect to their operational state, configuration, working fluid and thermal fluid, aiming at a minimal specific cost. The costs of 1449.05, 1045.24, and 638.80 US$/kWe and energy efficiencies of 11.1%, 10.9%, and 10.4% were found for 100, 1000, and 50,000 kWt of heat transfer rate at average temperature of 345 °C. The R-square varied from 0.96 to 0.99 while the number of results with error lower than 5% varied from 88% to 75% depending on the surrogate model (random forest or polynomial regression) and output (specific cost or efficiency). The computational time was reduced in more than 99.9% for all surrogates indicated.

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