Towards net-zero emissions through the hybrid SMR-solar cogeneration plant equipped with modular PCM storage system for seawater desalination

Sadeghi, Khashayar; Ghazaie, Seyed Hadi; Chebac, Riccardo; Sokolova, Ekaterina; Fedorovich, E. D.; Cammi, Antonio; Ricotti, Marco Enrico; Shirani, Amir Saeed

doi:10.1016/j.desal.2021.115476

Cited by 9 publications

(3 citation statements)

References 41 publications

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“…Phase change materials (PCMs) are extensively exploited in LHTES in view of not only high latent heat but trivial temperature changes during the phase change processes. Moreover, PCMs are widely employed in solar energy systems 4 , buildings 5,6 , desalination 7 , and thermal management of electronic devices 8 . However, the inherent defect of PCMs, low thermal conductivity, prolongs their melting (charge) and solidification (discharge) processes, restricting their applications.…”

Section: List Of Symbolsmentioning

confidence: 99%

Multi-objective optimization of multiple droplet impacts on a molten PCM using NSGA-II optimizer and artificial neural network

Faghiri

Poureslami

Aria

et al. 2023

Sci Rep

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Embracing an interaction between the phase change material (PCM) and the droplets of a heat transfer fluid, the direct contact (DC) method suggests a cutting-edge solution for expediting the phase change rates of PCMs in thermal energy storage (TES) units. In the direct contact TES configuration, when impacting the molten PCM pool, droplets evaporate, provoking the formation of a solidified PCM area (A). Then, they reduce the created solid temperature, leading to a minimum temperature value (Tmin). As a novelty, this research intends to maximize A and minimize Tmin since augmenting A expedites the discharge rate, and by lowering Tmin, the generated solid is preserved longer, resulting in a higher storage efficacy. To take the influences of interaction between droplets into account, the simultaneous impingement of two ethanol droplets on a molten paraffin wax is surveyed. Impact parameters (Weber number, impact spacing, and the pool temperature) govern the objective functions (A and Tmin). Initially, through high-speed and IR thermal imaging, the experimental values of objective functions are achieved for a wide range of impact parameters. Afterward, exploiting an artificial neural network (ANN), two models are fitted to A and Tmin, respectively. Subsequently, the models are provided for the NSGA-II algorithm to implement multi-objective optimization (MOO). Eventually, utilizing two different final decision-making (FDM) approaches (LINMAP and TOPSIS), optimized impact parameters are attained from the Pareto front. Regarding the results, the optimum amount of Weber number, impact spacing, and pool temperature accomplished by LINMAP and TOPSIS procedures are 309.44, 2.84 mm, 66.89 °C, and 294.98, 2.78 mm, 66.89 °C, respectively. This is the first investigation delving into the optimization of multiple droplet impacts for TES applications.

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Section: List Of Symbolsmentioning

confidence: 99%

Multi-objective optimization of multiple droplet impacts on a molten PCM using NSGA-II optimizer and artificial neural network

Faghiri

Poureslami

Aria

et al. 2023

Sci Rep

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“…According to the given technical information for the proposed small gas turbine, the available heat for thermal desalination plants was 10,180 kW th . The relation between total capacity of thermal desalination plant and required heat can be expressed using Equation (3) [30].…”

Section: Levelized Power Cost [$/Kwh] = Total Annual Cost [M$]/annual...mentioning

confidence: 99%

Feasibility of Hybrid Desalination Plants Coupled with Small Gas Turbine CHP Systems

et al. 2022

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Nowadays, several technologies for desalination processes are available and widely employed. However, they consume a considerable amount of energy and involve high capital and operating costs. Therefore, the techno-economic analysis of a system coupling different energy sources with the desalination processes is of value. The possibility of coupling a small gas turbine combined heat and power system (GT CHP) with hybrid desalination plants (HDPs) has been assessed in this study. The proposed gas turbine power generation system, based on a single-stage centrifugal compressor and an uncooled centripetal turbine, provides design simplicity and reasonable installation costs for the power generating plant. The hybrid desalination technique, based on the use of two different desalination technologies, i.e., Reverse Osmosis (RO) and a thermal desalination process, has been chosen to better exploit the electrical and thermal energy produced by the mini CHP plant. The proposed solution is numerically investigated from both thermodynamic and economic points of view, and the results of the thermodynamic analysis of the cycle are used as input for the evaluation of the amount of freshwater produced and of costs. The economic assessment of standalone desalination systems is also shown for the comparison with the hybrid solutions here proposed. Results show that the total cost of the water produced by MED + RO was less than the total cost of the water obtained by MSF + RO, and that the energy cost of MED + RO hybrid desalination system was about 15% less than that for stand-alone RO desalination technology. Thus, the MED + RO hybrid desalination system can be considered a promising solution for the coupling with the proposed mini GT CHP plant, which, due to the small size and cost, as well as the easy installation, can be easily applied in off-grid or remote areas.

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“…However, there has been a shift towards hybrid power plants (HyPP) given their higher efficiency, increased functionalities, and dispatchability [9]. In this direction, Sadeghi et al [10] performed an economic assessment of desalinated water for scenarios in which energy is obtained from solar, small modular reactor (SMR) or both; concluding on the superiority of the HyPP structure. While Liu et al [11] integrate freshwater storage, wind and solar power in a coastal desalination installation to reduce the water production costs.…”

Section: Introductionmentioning

confidence: 99%

Machine learning-driven energy management of a hybrid nuclear-wind-solar-desalination plant

et al. 2022

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Towards net-zero emissions through the hybrid SMR-solar cogeneration plant equipped with modular PCM storage system for seawater desalination

Cited by 9 publications

References 41 publications

Multi-objective optimization of multiple droplet impacts on a molten PCM using NSGA-II optimizer and artificial neural network

Multi-objective optimization of multiple droplet impacts on a molten PCM using NSGA-II optimizer and artificial neural network

Feasibility of Hybrid Desalination Plants Coupled with Small Gas Turbine CHP Systems

Machine learning-driven energy management of a hybrid nuclear-wind-solar-desalination plant

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