Integrated design of ORC process and working fluid using process flowsheeting software and PC-SAFT

Schilling, Johannes; Groß, Joachim

doi:10.1016/j.egypro.2017.09.184

Cited by 24 publications

(16 citation statements)

References 22 publications

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“…Schilling et al have developed an approach to select working fluids and design ORCs simultaneously using continuous-molecular targeting (CoMT) and CAMD. The CoMT approach provides an upper bound of the objective function for an ORC design problem by relaxing an MINLP into NLP, and a CAMD formulation seeks the working fluid and the ORC, which can give the optimum objective function value close to the upper bound. , Although the methods described so far have succeeded in significantly improving the efficiency of ORCs, the working fluid obtained as a result of the optimization methods would not be suitable for an actual ORC, because of its vulnerability to uncertainties in operating conditions.…”

Section: Introductionmentioning

confidence: 99%

Robust Design of Multicomponent Working Fluid for Organic Rankine Cycle

Kim

et al. 2019

Ind. Eng. Chem. Res.

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A method for designing the optimal working fluid mixture of organic Rankine cycles (ORC), which is robust against uncertainty in its composition, is developed. The objective function for designing the working fluid is formulated using statistical moments to achieve high performance even when the composition deviates from the nominal value. To obtain the statistical moments with a small number of simulations, nonintrusive polynomial chaos expansion (PCE) is employed. A Bayesian algorithm is adopted to solve the optimization of which objective function value is computed by PCE. The proposed method allows one to design robust working fluids, which cannot be performed in a reasonable time with Monte Carlo simulations, because of heavy computational efforts. It has been shown that changes in composition can have serious consequences to stable operation of ORC, and the working fluid designed by the proposed method allows flexible ORC operation, despite the existence of uncertainty in the composition.

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Section: Introductionmentioning

confidence: 99%

Robust Design of Multicomponent Working Fluid for Organic Rankine Cycle

Kim

et al. 2019

Ind. Eng. Chem. Res.

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“…The implementation of 1‐stage CoMT‐CAMD into gPROMS ProcessBuilder provides a user‐friendly design tool that engineers can use on a daily basis overcoming the challenge of previous integrated design approaches, which are based on specific tools . In our previous work, we have integrated 1‐stage CoMT‐CAMD into gPROMS ProcessBuilder for an integrated thermodynamic design of processes and molecules . The thermodynamic properties are calculated using the PC‐SAFT EoS available in the gSAFT property package of gPROMS ProcessBuilder.…”

Section: Framework For Integrated Design Of Molecules Processes Equmentioning

confidence: 99%

“…stage CoMT-CAMD into gPROMS ProcessBuilder for an integrated thermodynamic design of processes and molecules 77. The thermodynamic properties are calculated using the PC-SAFT EoS available in the gSAFT property package of gPROMS ProcessBuilder.…”

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confidence: 99%

Integrating superstructure‐based design of molecules, processes, and flowsheets

2020

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The key to many chemical and energy conversion processes is the choice of the right molecule, for example, used as working fluid. However, the choice of the molecule is inherently coupled to the choice of the right process flowsheet. In this work, we integrate superstructure‐based flowsheet design into the design of processes and molecules. The thermodynamic properties of the molecule are modeled by the PC‐SAFT equation of state. Computer‐aided molecular design enables considering the molecular structure as degree of freedom in the process optimization. To consider the process flowsheet as additional degree of freedom, a superstructure of the process is used. The method results in the optimal molecule, process, and flowsheet. We demonstrate the method for the design of an organic Rankine cycle considering flowsheet options for regeneration, reheating, and turbine bleeding. The presented method provides a user‐friendly tool to solve the integrated design problem of processes, molecules, and process flowsheets.

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“…In a similar way, Molina-Thierry and Flores-Tlacuahuac performed a constrained simultaneous optimization of fluid mixtures (generated from a prespecified set of pure fluids) and the process operating conditions. Lampe et al , and Schilling and co-workers − performed fluid-searching using a reverse engineering approach for ORC processes. Roskosch and Atakan applied a reverse engineering approach for a heat pump application.…”

Section: Introductionmentioning

confidence: 99%

“…Various molecular design or reverse engineering frameworks that have been developed used cubic EoSs. ,,,,− Another alternative for a low-parametric EoS is Perturbed-Chain Statistical Associating Fluid Theory (PC-SAFT) . Working fluid analysis studies , as well as fluid design frameworks − have been developed with a PC-SAFT as the property model for thermodynamic cycles.…”

Section: Introductionmentioning

confidence: 99%

Reverse Engineering of Working Fluid Selection for Industrial Heat Pump Based on Monte Carlo Sampling and Uncertainty Analysis

Frutiger¹,

Zühlsdorf²,

Elmegaard³

et al. 2018

Ind. Eng. Chem. Res.

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This study presents a novel methodology for the identification of suitable pure component working fluids for heat pumps. Two challenges are addressed: the difficulties in solving a complex product-process design problem and making it accessible for practical applications, as well as the impact of the working fluid property uncertainties on the solution. A Monte Carlo sampling is applied to generate sets of different property parameter combinations (virtual fluids), which are subsequently evaluated in the heat pump process model. The distance between the property values of the virtual fluid and the uncertainty bound of the properties of real fluids (collected from a database) are calculated. The fluids that are closest to the top-performing virtual fluids are further analyzed through evaluation in the cycle and subsequent uncertainty propagation of the respective input property uncertainties to the model output uncertainties. The methodology has been applied to an industrial heat pump system used for waste heat recovery from a spray drying facility in the dairy industry. To remain focused on the validation of underlying concepts of the methodology, the study considered screening only among cyclic hydrocarbon working fluids. The compounds identified by the methodology had a low global warming potential (<0.1) but a high flammability (lower flammability limit <1.8 vol %). Cyclopentane showed the best performance with a coefficient of performance of 3.06 ± 0.05. The sampling-based reverse engineering method identified top performing working fluids, but avoided solving complex and computationally demanding molecular design problems, and took into account the real fluid property uncertainties.

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Integrated design of ORC process and working fluid using process flowsheeting software and PC-SAFT

Cited by 24 publications

References 22 publications

Robust Design of Multicomponent Working Fluid for Organic Rankine Cycle

Robust Design of Multicomponent Working Fluid for Organic Rankine Cycle

Integrating superstructure‐based design of molecules, processes, and flowsheets

Reverse Engineering of Working Fluid Selection for Industrial Heat Pump Based on Monte Carlo Sampling and Uncertainty Analysis

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