A thermoeconomic optimization of a binary geothermal power plant

This research was carried out for the thermodynamic analysis of a binary geothermal power plant and its thermoeconomic optimization based on the results obtained. In this context, initially, data related to the design point and off-design operating points of the plant were collected from a geothermal power plant which is currently operating in the Aydın/Germencik region in southwestern Anatolia. Based on the data obtained, a thermodynamic model of the power plant was constructed as a result of various simulations and this model was verified by using the outputs of the plant (such as net power, first and second law efficiency) and the outputs of similar plants in the literature. By means of this model, an exergy analysis of the power plant was carried out in the first place. Following the exergy analysis, a new method has been proposed, consisting of 4 steps and based on thermodynamic-thermoeconomic criteria, in order to make the selection of working fluid more effective in the existing power plant. As a result of the elimination of 29 candidate fluids from different chemical groups according to the new method, it was evaluated that R113 could be a more suitable alternative to the existing n-pentane fluid. In addition, a waste-heat recovery system was proposed for the re-utilization of geothermal water, which is re-injected to the soil at the exit of the power plant, and R115 was chosen as the working fluid for this hypothetical system. After this case study, by using 3 different exergoeconomic analysis methods on the power plant, levelized electrical cost (LEC) of the power plant was tried to be estimated through the initial thermodynamic model. Moreover advantages/disadvantages of the methods compared to each other. After this stage, studies were carried out to create a non-design model that can represent the non-design operating points of the plant with sufficient accuracy. At the first stage, the turbine curves in the two cycles were determined and their integration into the thermodynamic model was provided by using off-design plant data. Statistical models for various parameters were also established in the MATLAB environment in order to increase the power and mass flow rate estimation precision of the turbine curves. The results obtained from the turbine curves were compared with various power plant data and empirical correlations. In the last stage, optimum plant configurations have been determined and presented as novel suggestions, both from a retrospective point of view and depending on the changing environment and initial conditions, by using convex and gradient-based optimization algorithms for off-design data points.