Dynamic simulation of solar-powered ORC using Open-Source tools: a case study combining SAM and Coolprop via Python

Abstract The lack of an open-source dynamic simulation framework integrated with well-established thermodynamic package represents a major constraint facing open-source software users in process industry. To overcome this limitation, many approaches can be adopted to create a unified dynamic co-simulation framework. The purpose of this work is to demonstrate one of them which aims at simulating a cyclopentane based ORC cycle powered by solar thermal energy using SAM, coolprop, and Python. All unit operations (UO) involved in the ORC cycle are coded in Python language, while thermodynamic properties are estimated using Coolprop Python wrapper. The required thermal power produced by the solar field (SF) has been simulated through PySAM wrapper and then transmitted to the power cycle. Once the co-simulation architecture is established, the overall system is dynamically simulated using 10 minutes time step weather data file measured in Benguerir city. Subsequently, the tool is validated against literature data for the aforementioned site. The estimated mean absolute error between the simulated and the literature results was found in the range 0.7 % to 10.0 % in terms of the SF produced thermal power, Q sf , and less than 2.25 % in terms of the ORC produced electrical power, W ˙ net . Thus, the proposed simulation approach allows properly simulating the entire system dynamics response to the solar irradiation evolution overtime with good accuracy. The simulation tool is also used to compare the dynamic performance of the ORC cycle using the weather data of seven sites in Morocco. The obtained dynamic profiles of Q sf , the working fluid (WF) temperature T wf , and W ˙ net , for the studied sites are in good agreement with their respective DNI profiles. The most significant ORC time averaged efficiency have been achieved in Tata and Benguerir, its value found to be arround 18 %.