Performance and optimization study of graded thermal energy storage system for direct steam generation dish type solar thermal power

Case Studies in Thermal Engineering(2023)

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摘要
The traditional dish type Stirling power generation system cannot have the thermal energy storage system, so the power generation is discontinuous. The direct steam generation dish type solar thermal power, which includes the thermal energy storage system, is expected to solve this problem. Currently, research on graded thermal energy storage system is limited to single-factor analysis, and there have been no reports on single-objective optimization and cost analysis for such systems. A graded thermal energy storage system combining the latent and sensible thermal energy storage in which solar salt (60% NaNO3-40% KNO3) is used as sensible thermal energy storage material, and sodium nitrate is selected as the phase change material (PCM), is studied in present work. To improve the performance of the graded thermal energy storage system, this paper studies the influence of mass flow rate ratio Rm (the sensible thermal energy storage materials mass flow rate from the cold tank to the intermediate tank relative to the mass flow rate from the intermediate tank to the hot tank), the superheated steam temperature at the inlet of the system, and the mass flow rate of sensible thermal energy storage material. In addition, the significance of three factors is analyzed by response surface methodology. Finally, taking efficiency as the goal, the single-objective optimal operating parameters of the graded thermal energy storage system are obtained by using a genetic algorithm. The study found that increasing the Rm or reducing the inlet superheated steam temperature can effectively improve the exergy efficiency of the system. The optimization results show that the exergy efficiency of this graded thermal energy storage system has been improved by 20%.
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关键词
Graded thermal energy storage,Thermodynamic analysis,Temperature-enthalpy characteristic,Response surface method,Genetic algorithm
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