Design of a MoNiKa-turbine and condenser model in Modelica/Dymola and comparison with previous Simulink models and experimental results

To research optimization possibilities in supercritical ORC processes for geothermal power production the Modular low-Temperature Circuit Karlsruhe (MoNiKa) was built at Campus North of the Karlsruhe Institute of Technology. Several research tasks have been conducted over this installation focusing on individual components. The present master thesis describes the development of a coupled MoNiKa turbine-condenser model using the Modelica modeling language with the Dymola development environment. For thermodynamic components the commercial library TIL was used. To calculate the properties of the working fluid a Dymola-REFPROP interface was utilized. For the turbine model an empirical efficiency correlation of the MoNiKa turbine was developed from experimental data and implemented. The determination of the turbine inlet pressure is based on Stodola’s cone law which has been adjusted to the MoNiKa turbine in previous studies. To reduce computational time the input data has been pre-processed by applying filters. For the condenser model grid convergence studies were carried out to ensure precision and convergence. The simulation results of the developed models were compared to the results of previous Simulink models for turbine and condenser. The model was then validated using experimental data from several MoNiKa test runs from 08-10 November 2021 representing a range of different operating conditions. The quantitative and qualitative agreement of the simulated turbine shaft power with the experimental data could be improved compared to the previous models. The developed coupled turbine-condenser model is capable of providing close approximations of turbine shaft power and condenser outlet variables over a wide operating range of the MoNiKa plant. In addition, the computation time could be kept within reasonable limits to enable further extensions of the model to complete the MoNiKa cycle. The influence of individual input parameters on the output variables could be determined by means of a sensitivity study to guide further improvements in the measuring equipment.