Solar-driven sodium thermal electrochemical converter coupled to a Brayton heat engine: Parametric optimization
Sodium thermal electrochemical converter
Brayton heat engine
Fecha de publicación
Peng, W., Gonzalez-Ayala, J., Guozhen, S., Jincan, C., Calvo Hernández, A. (2021). Solar-driven sodium thermal electrochemical converter coupled to a Brayton heat engine: Parametric optimization. Renewable Energy, 164, pp.260-271
[EN]A novel high-efficiency device comprised of three subsystems, a solar collector, a sodium thermal electrochemical converter, and a non-recuperative Brayton heat engine, is modeled by taking into account the main internal and external irreversibility sources. The model extends previous works in which the heat waste of the electrochemical converter is used as heat input in a Brayton gas turbine to study its performance and feasibility when a solar energy input is added. The operative working temperatures of three subsystems are determined by energy balance equations. The dependence of the efficiency and power output of the overall system on the solar concentration ratio, the current density, the thickness of the electrolyte, and the adiabatic pressure ratio (or temperature ratio) of the Brayton cycle is discussed in detail. The maximum efficiencies and power output densities are calculated and the states of the maximum efficiency-power density are determined under different given solar concentration ratios. The parametric optimum selection criteria of a number of critical parameters of the overall system are provided and the matching problems of the three subsystems are properly addressed. It is found that under a solar concentration around 1350, the maximum efficiency and power output density of the proposed hybrid system can reach, respectively, 29.6% and 1:23 105 W/m2. These values amount approximately 32.7% and 156% compared to those of the solar-driven sodium thermal electrochemical converter system without the bottoming Brayton cycle. The Pareto front obtained from numerical multiobjective and multi-parametric methods endorses previous findings.
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