A systematic study of thermodynamic energetic and environmental aspects of harnessing geothermal power plants

Over the last years, the growing energy demand worldwide and the development of stringent international, national and regional regulations on polluting emissions have favoured the development of innovative energy systems in the field of renewable energy. In this context, geothermal energy, which boasts for a hundred years of exploitation systems of heat and hot water of the Earth, has returned to interest most of the nations for the optimization and efficiency of geothermal systems for the production of electricity and heat for a large part of the world population. The Tuscany region boasts its primacy in using geothermal energy thanks to the first high enthalpy exploitation experiment in Larderello in 1904, and in 1913 the first plant for the production of electricity from 250 kW up to the current value of 810 MW was built of installed power. Geothermal energy, having a simple operation, uses steam or biphasic fluids to represent the raw material to power the turbine. According to the geothermal fluid, there are three main types of geothermal power plants: a. dry steam, the simplest technology that extracts steam from fractures in the ground and uses it directly to drive a turbine; b. flash, a transformation of boiling and high-pressure water into steam which is expanded in a turbine c. binary, water or steam are run alongside a second fluid with a lower boiling point than water; production of vapour and introduction into the turbine. The whole process defines alternative and clean geothermal energy. "Clean" because it produces low emissions compared to the combustion processes of fossil fuel plants that emit CO2 and fine dust while alternative because through other renewable sources (wind and solar in particular) they contribute to the production of electricity at "zero km", exploiting natural and renewable resources even in the most inaccessible places in the region. But at the same time, some disadvantages can be solved thanks to scientific research. They are the presence of unwanted species in geothermal fluids with particular attention to carbon dioxide (CO2), hydrogen sulphide (H2S) and methane (CH4) and rarely the presence of heavy metals such as mercury (Hg), Cadmium (Cd) and lead (Pb). They are present at the moment of extraction from the geothermal reservoir and, in the absence of efficient abatement methods, throughout the process up to the cooling towers and the consequent reinjection wells. The present study analyses and compares thermodynamic models (TM) on geothermal fluids containing unwanted species and salts. The work starts with the campaign to collect experimental data in the various sectors of applied thermodynamics. Thanks to the French research centre's contribution, IFP energies nouvelles (IFPEN), the most influential binary, ternary and quaternary mixtures that influence geothermal plants' processes, have been selected. Furthermore, more than a thousand experimental data were collected and subsequently selected thanks to the databases present in IFPEN and the scientific publications from 1918 to 2020. The experimental data, filtered, verified in their congruity, and grouped by temperature, pressure and molality of the NaCl salt were the source of comparison with the results of the TM defined for a geothermal process. Considering the variable composition of geothermal mixtures and the IFPEN team's experience, it was discussed which TM can obtain the best results of solubility and enthalpy, applicable in a subsequent work also for the transport properties (density, viscosity, thermal conductivity, diffusion coefficient ). Furthermore, the work aims to indicate which TM is the most appropriate in process simulation. The best choice of a TM depends on the percentage of the non-condensable gas components inside the geothermal fluid and dissolved salts. The performance of the TM depends not only on the kinds of reservoirs present in the world (Chapter 2) but also on the pressure and temperature conditions. Starting from the developed TM, their performances (Chapter 4) and the corresponding analysis (Chapter 5), the suggested TM for process simulation, for fluids without salts, are Sour Peng- Robinson (SPR) and OLI AQ for geothermal mixtures containing CO2 and H2S as the main components, while OLI MSE for geothermal mixtures containing CH4, CO2 and H2S as main components. The presence of salt affects the choice of the TM. For this reason, the best TM is represented by OLI MSE SRK. From all the tested TM studied in this work, the modified version of the Duan-Sun model provides good agreement with literature data and, therefore, can be integrated into commercial process software like Unisim Design. In a second step, three different geothermal plants were identified and analyzed: a. Castelnuovo (Tuscany Region, Italy): an ORC-based geothermal power generation (5 MWe) with CO2 reinjection prototype; b. Hellisheidi (Iceland): double flash combined heat and power plant (303.3 MWe and 133 MWt); c. Chiusdino (Tuscany Region, Italy): a standard power plant with a nominal capacity of 20 MWe connected to a district heating network, with a planned capacity of 7 MWth. A thermodynamic package appropriate to the species present in the geothermal fluid was chosen for each geothermal plant. For some case studies, the following were applied: ▪ An economic evaluation of the main constituent components of the geothermal plant; ▪ An environmental feasibility analysis - Life cycle Assessment (LCA), particularly for two case studies on the Icelandic Hellisheidi geothermal plant. The models and the data obtained by simulations made it possible to identify geothermal plants' methods. As a result, the choice of a thermodynamic model and the validation of the numerical results, which was among the main objectives of this work, can be reliably used for the accurate and optimized Geothermal power plants' design (GTPPs). Therefore, this study showed that selecting a thermodynamic model for the GTTP process simulation defines the best way to optimize the process for energetic and environmental performances.