Energy Systems Engineering / Enerji Sistemleri Mühendisliği

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  • Article
    Stochastic 1-D Reactive Transport Simulations To Assess Silica and Carbonate Phases During the $co_2$ Reinjection Process in Metasediments
    (TÜBİTAK - Türkiye Bilimsel ve Teknolojik Araştırma Kurumu, 2024) Erol, Selçuk
    One proposed method to mitigate carbon emission is to mineralize the $CO_2$ in deep geothermal reservoirs while mixing the coproduced CO2 with the effluent fluid for reinjection. The injection fluid temperature fluctuates due to the mixing process between CO2-charged water and the effluent fluid, and compressor interruptions change the thermodynamic conditions that influence the fluid- rock interaction in the reservoir. Mineral dissolution or precipitations are associated with changes in permeability and porosity that affect the flow and, eventually, the lifespan of the reservoir. A combined stochastic–reactive transport simulation approach is useful for inspection purposes. Moreover, the stochastic algorithm validates the deterministic reactive transport simulation and demonstrates the time evolution of a chemically reacting system in the reservoir. This study examines a range of injection temperatures between 80 °C and 120 °C to evaluate silica and calcite precipitation along a flow path. One-dimensional (1-D) reactive transport and compartment- based stochastic reaction-diffusion-advection Gillespie algorithms are carried out. The 1-D model represents a reservoir feed zone of around 2300 m. Two common metasediment rock types are evaluated for inspection. The first one is the muscovite schist, which has approximately 60% quartz, and the second is the quartz schist, consisting of roughly 90% quartz. The stochastic method can be applied more effectively if the chemical system is completely defined with proper reaction rates as a function of temperature. The mixing ratio of the coproduced $CO_2$ over the effluent fluid is around 0.0028. Simulation results show that $CO_2$ is partially sequestrated as calcite within the first 10 m of the entrance to the reservoir and plugs the pores completely in the muscovite schist scenario. Chalcedony and α-cristobalite precipitate as secondary minerals evenly along the flow path. $CO_2$ injection into a quartz schist layer is more appropriate for geochemical interactions below 120 °C.
  • Article
    Citation - WoS: 22
    Citation - Scopus: 24
    Design, Evaluation, and Optimization of an Integrated Proton Exchange Membrane and Double Flash Geothermal Based Organic Rankine Cycle Multi-Generation System Fed by a Biomass-Fueled Gasifier
    (Elsevier, 2024) Taheri, Muhammad Hadi; Seker, Utku; Akkurt, Gulden Gokcen; Mohammadpourfard, Mousa
    This study introduces an innovative approach by formulating and evaluating a synergistic biomass-geothermal structure, emphasizing optimized inter-component connections. The research stands out for its thorough analysis of parameter impacts on the system and variables, addressing an unexplored aspect in integrated energy systems. The multi-generation systems are the integration of a combined gasification gas turbine cycle, double flash geothermal cycle, and proton exchange membrane cycle for the generating power and hydrogen. The overall system and its subsystems are studied to explore how the performance of thermodynamics and the total cost rate are influenced by operating parameters. The best operational conditions for both subsystems and the overall system have been determined by analyzing the impact of operating parameters on the thermodynamic behavior and environmental impact through parametric studies. The findings indicate while Sabalan's current efficiency is 16.26 %, the system energy efficiency reached 24.89 % when coupled with other renewable source. To enhance the system's efficiency, a genetics algorithm was utilized to simultaneously optimize the total cost of exergy destruction and investment cost. The outcome of the multi-objective optimization revealed that the exergy efficiency of optimal point for the system is 29.8 % and a total investment cost is 6 (M$/year).