The growing global energy demand, combined with the urgent need to reduce greenhouse gas emissions, has accelerated the adoption of renewable energy sources in recent years. Within this context, Organic Rankine Cycle (ORC) systems have gained prominence for their ability to effectively harness low and medium-temperature heat sources using a diverse range of working fluids. This thesis explores the potential of geothermal brines, particularly through the application of ORC systems, to objectively compare various thermodynamic cycle architectures and identify the optimal solution from both thermodynamic and techno-economic perspectives. The study analyzed five configurations, including subcritical and supercritical cycles, two pressure levels with turbines in series, turbines in parallel, and the use of mixtures as working fluids. To model these thermodynamic configurations, Python code was developed using object-oriented programming, structuring the cycles from a component class that integrates all the necessary subclasses for accurate modeling. The methodology used to identify the most efficient thermodynamic solutions is thoroughly discussed. The objective was to pinpoint the configurations that yield the highest net electric power under different constraints on the brine reinjection temperature (free, 75°C, and 100°C). From a techno-economic standpoint, the study determined the most profitable solution in terms of the Levelized Cost of Energy (LCOE) for scenarios with brine reinjection temperatures exceeding 75°C. It was found that supercritical cycles and mixtures outperformed subcritical configurations in terms of net power production and achieved lower LCOE values. However, the study revealed that mixtures did not consistently offer an economic advantage due to phase transition issues. The model's robustness was also evaluated through sensitivity analyses on drilling costs and the heat transfer coefficient.
La crescente domanda di energia a livello globale, unita all'urgente necessità di ridurre le emissioni di gas serra, ha notevolmente accelerato l'adozione delle fonti di energia rinnovabile negli ultimi decenni. In questo contesto, i sistemi ORC (Organic Rankine Cycle) si distinguono per la loro capacità di utilizzare una vasta gamma di fluidi di lavoro, permettendo lo sfruttamento efficiente di sorgenti di calore a bassa e media temperatura, spesso non adeguatamente valorizzate. Questa tesi esplora il potenziale dei fluidi geotermici, in particolare attraverso l'applicazione dei sistemi ORC, con l'obiettivo di confrontare in modo oggettivo diverse architetture di cicli termodinamici per identificare la soluzione ottimale sia dal punto di vista termodinamico che tecnico-economico. Sono state analizzate cinque configurazioni: subcritica, supercritica, a due livelli di pressione con turbine in serie o in parallelo, e l'utilizzo di miscele come fluidi di lavoro. Per descrivere queste configurazioni termodinamiche, è stato sviluppato un codice in Python utilizzando la programmazione orientata agli oggetti, strutturando i cicli a partire da una classe di componenti che integra tutte le sottoclassi necessarie per un modellamento accurato. La metodologia seguita per identificare le soluzioni termodinamiche più efficienti è ampiamente discussa. Dal punto di vista termodinamico, lo studio identifica le configurazioni che producono la maggiore potenza elettrica netta sotto diversi vincoli di temperatura di reiniezione del fluido geotermico (libera, 75°C e 100°C). Dal punto di vista tecnico-economico, è stata determinata la soluzione più redditizia in termini di LCOE (Levelized Cost of Energy) per scenari con temperature di reiniezione del fluido geotermico superiori a 75°C. I cicli supercritici e le miscele si sono dimostrati superiori alle configurazioni subcritiche in termini di produzione di potenza netta e hanno raggiunto valori di LCOE inferiori. Tuttavia, per le miscele, la presenza del glide in fase di transizione non ha sempre offerto un vantaggio tecnico-economico. Per valutare la robustezza del modello, sono state effettuate analisi di sensibilità sui costi di perforazione e sul coefficiente di trasferimento del calore.
Comparative study of ORC systems for medium enthalpy geothermal resources
Del Pizzo, Domenico
2023/2024
Abstract
The growing global energy demand, combined with the urgent need to reduce greenhouse gas emissions, has accelerated the adoption of renewable energy sources in recent years. Within this context, Organic Rankine Cycle (ORC) systems have gained prominence for their ability to effectively harness low and medium-temperature heat sources using a diverse range of working fluids. This thesis explores the potential of geothermal brines, particularly through the application of ORC systems, to objectively compare various thermodynamic cycle architectures and identify the optimal solution from both thermodynamic and techno-economic perspectives. The study analyzed five configurations, including subcritical and supercritical cycles, two pressure levels with turbines in series, turbines in parallel, and the use of mixtures as working fluids. To model these thermodynamic configurations, Python code was developed using object-oriented programming, structuring the cycles from a component class that integrates all the necessary subclasses for accurate modeling. The methodology used to identify the most efficient thermodynamic solutions is thoroughly discussed. The objective was to pinpoint the configurations that yield the highest net electric power under different constraints on the brine reinjection temperature (free, 75°C, and 100°C). From a techno-economic standpoint, the study determined the most profitable solution in terms of the Levelized Cost of Energy (LCOE) for scenarios with brine reinjection temperatures exceeding 75°C. It was found that supercritical cycles and mixtures outperformed subcritical configurations in terms of net power production and achieved lower LCOE values. However, the study revealed that mixtures did not consistently offer an economic advantage due to phase transition issues. The model's robustness was also evaluated through sensitivity analyses on drilling costs and the heat transfer coefficient.File | Dimensione | Formato | |
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https://hdl.handle.net/10589/227142