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Relative Free Energy Function and Structural Theory of Thermoeconomics

Author

Listed:
  • Antonio Valero

    (CIRCE Institute, Universidad de Zaragoza, 50018 Zaragoza, Spain)

  • César Torres

    (CIRCE Institute, Universidad de Zaragoza, 50018 Zaragoza, Spain)

Abstract

This paper explores the advantages of using relative free energy instead of exergy to build a mathematical theory of thermodynamic costs to diagnose malfunctions in thermal systems. This theory is based on the definition of a linearized characteristic equation that represents the physical behavior of each component. The physical structure of the system described by its energy interrelationships is called “primal”, and its derivatives are the costs and consumptions. The obtained costing structure is the mathematical “dual” of its primal. The theory explains why the F and P cost assessment rules and any other suggestion may (or may not be) rational under a given disaggregation scheme. A result of the theory is a new thermodynamic function, called the relative free energy , and a new parameter called deterioration temperature due to a component’s deterioration cause, characterized by a h-s thermodynamic trajectory describing the effects on the exiting stream. The relative free energy function allows for an exact relationship between the amount of used resources and the increase in entropy generation caused by the deterioration path of the component. This function allows the obtaining of, for the first time, an appropriate characteristic equation for a turbine and a new definition of efficiency that does not depend on the environment temperature but on its deterioration temperature. Also, costing with relative free energy instead of exergy may open a new path for more precise and straightforward assessments of component deteriorations.

Suggested Citation

  • Antonio Valero & César Torres, 2020. "Relative Free Energy Function and Structural Theory of Thermoeconomics," Energies, MDPI, vol. 13(8), pages 1-21, April.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:8:p:2024-:d:347428
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    References listed on IDEAS

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    Cited by:

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    2. Yilmaz, Ceyhun & Sen, Ozan, 2024. "Feasibility of optimum energy use and cost analyses by applying artificial intelligence and genetic optimization methods in geothermal and solar energy-assisted multigeneration systems," Renewable Energy, Elsevier, vol. 237(PA).

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