Energy, Exergy, Entropy Generation Minimization, and Exergoenvironmental Analyses of Energy Systems-A Mini-Review

Abstract

Meeting the growing energy demands has become a crucial challenge, which should employ energy integration and benefit from the extraction of the maximum thermodynamic potential of the resources consumed. This brief review presents an overview of the essential elements of the methods of energy, exergy, entropy generation minimization, and exergoenvironmental analyses. In combination, these methodologies constitute a powerful toolbox for the design, analysis, and optimization of energy systems. The quantification of energy and environmental impacts provided by them is essential in guiding toward system designs that are consistent with current energy and environmental needs.

Entropy Generation Analysis in Turbulent Reacting Flows and Near Wall: A Review

“…Exploiting the ability to quantify the degree of irreversibility by means of the entropy generation, which can be considered as a function that depends on the path followed by the thermodynamic process and on geometrical parameters of the system design, made it possible to use the Entropy Generation Analysis along with the Entropy Generation Minimization (EGM) [ 8 , 143 ]; see also [ 31 ] for optimization purposes.…”

“…Bejan [ 8 ] was the first to provide a review of the development and adoption of the Entropy generation minimization (finite time thermodynamics, or thermodynamic optimization) in several sectors of relevant practical importance, such as cryogenics, heat transfer, education, storage systems, solar power plants, nuclear and fossil power plants, as well as refrigerators. Ordonez et al [ 143 ] reported, in their recent review on the thermodynamic methods of analysis, the concepts of the exergy and entropy generation in order to assess system performance by means of metrics that quantify the degrees of irreversibility.…”

“…As usual in optimization tasks, both methods enable the formulation of constrained optimization problems in which the objective function is the entropy generation, the degrees of freedom include typically operational and geometrical parameters, and the constraints are associated with the finite resources (heat transfer areas, system volume, etc.) [ 143 ].…”

“…This can, on occasion, be accomplished analytically but often requires numerical approaches. In principle, any suitable function minimization approach can be used [ 143 ].…”

“…Nevertheless, an overview of contributions dealing with optimization of systems systems involving mass transfer, chemical reactions and other transport phenomena can be found in [ 5 ], while further examples of entropy generation minimization and thermodynamic optimizations are provided in a recent mini-review [ 143 ].…”