Integrated design of ORC process and working fluid using process flowsheeting software and PC-SAFT
Johannes Schilling, Joachim Gross, André Bardow
Session: Poster session & Welcome drinks
Session starts: Wednesday 13 September, 17:30
Johannes Schilling ()
Joachim Gross ()
André Bardow ()
Organic Rankine Cycles (ORCs) generate electrical power from low-temperature heat. To make best use of a heat source, ORC process and working fluid have to be optimized simultaneously. However, working fluid design and process optimization are commonly separated into a two-step approach: In a first step, promising working fluids are preselected using heuristic guidelines. In a second step, the set of preselected working fluids is employed for process optimization. However, if the preselection fails, this two-step approach leads to suboptimal solutions. To obtain an overall optimal solution, integrated design approaches have been developed. However, integrated design approaches are usually complex and based on specific software and tools which prevents fast and easy development of the ORC models.
In this work, we have integrated the so-called 1-stage CoMT-CAMD approach  into the process flowsheeting software gPROMS allowing the integrated design of process and working fluid while employing model libraries of gPROMS ProcessBuilder . In 1-stage CoMT-CAMD, thermodynamic properties are modeled by the Perturbed-Chain Statistical Associating Fluid Theory (PC-SAFT) equation of state , which we use directly from the gPROMS physical property package. We have implemented the homosegmented group contribution method of PC-SAFT  and the Computer-aided Molecular Design (CAMD) formulation of the 1-stage CoMT-CAMD approach in gPROMS. Thereby, we can define the molecular structure of the working fluid as an additional degree of freedom within the process optimization. For this purpose, the existing model libraries of gPROMS were adapted to allow for varying molecular structures during process optimization. The resulting tool allows for easy definition and configuration of the considered process based on the “drag-and-drop” feature of the process flowsheeting software. The resulting mixed integer nonlinear program (MINLP) optimization problem is solved by the standard MINLP solver integrated in gPROMS. Thereby, the optimal working fluid and the corresponding optimal process are identified in one single optimization. We demonstrate the resulting approach for the design of a subcritical geothermal ORC application.
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 Schilling, J., Lampe, M., Gross, J., and Bardow, A., 1-stage CoMT-CAMD: An approach for integrated design of ORC process and working fluid using PC-SAFT, Chem. Eng. Sci., 2016, http://dx.doi.org/10.1016/j.ces.2016.04.048.
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