New analytical solution and optimization of a thermocline solar energy storage using differential quadrature method and genetic programming

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@Article{GHEZELBASH:2022:est,

• author = "Ghazal Ghezelbash and Mojtaba Babaelahi and Mahdi Saadatfar",
• title = "New analytical solution and optimization of a thermocline solar energy storage using differential quadrature method and genetic programming",
• journal = "Journal of Energy Storage",
• volume = "52",
• pages = "104806",
• year = "2022",
• ISSN = "2352-152X",
• DOI = "doi:10.1016/j.est.2022.104806",
• URL = "https://www.sciencedirect.com/science/article/pii/S2352152X22008155",
• keywords = "genetic algorithms, genetic programming, Thermocline energy storage, Differential quadrature method, Solar energy, Optimization",
• abstract = "This paper aims to present an analytical correlation to investigate heat transfer characteristics in thermocline storage tanks based on numerical solution results. Thermocline tanks are used to store solar thermal energy to ensure the stable operation of the solar system. For the evaluation of thermocline energy storage, the mass and energy balance equations for the heat transfer fluid and the material used in the tank are extracted and simplified. The governing equations for two different configurations, including concrete blocks with vertical holes and concrete plates, are considered. Depending on the type of governing equations, an efficient numerical method called the Differential Quadrature Method (DQM) has been used to achieve an accurate solution in a short time, and the results have been validated in special cases based on previous research. Based on the numerical solution results, temperature distribution, thermodynamic efficiency, energy stored in charge and discharge mode, and thermocline tank capacity are calculated; and the effect of different variables on these parameters are evaluated. Based on the results, the effective variables are selected as the decision variable, and for different values of these variables, the evaluation parameters were calculated using DQM. Based on the results obtained from the DQM, a comprehensive database has been created and used as an input of genetic programming tools. Then the analytical correlations are presented to evaluate the evaluating parameters. Based on the prepared analytical correlations, different multi-objective optimization has been performed to maximize the stored energy (charge/discharge mode), thermodynamic efficiency, and power; and minimization of costs",

}

Genetic Programming entries for Ghazal Ghezelbash Mojtaba Babaelahi Mahdi Saadatfar

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