Thermoeconomic Analysis of Renewable Energy Conversion Systems
DOI:
https://doi.org/10.5281/zenodo.22698428Keywords:
thermoeconomics, exergoeconomics, exergy costing, SPECO method, renewable energy conversion, solar thermal power, geothermal organic Rankine cycle, levelized cost of exergyAbstract
Levelized cost of electricity treats every kilowatt-hour as equivalent regardless of the thermodynamic quality of the
process that produced it, obscuring where within a renewable energy conversion system cost and irreversibility
actually accumulate. We apply the Specific Exergy Costing (SPECO) method to four renewable conversion
systems, a parabolic-trough concentrated solar power plant, a geothermal organic Rankine cycle (ORC) plant, a
utility-scale wind-to-hydrogen electrolysis system, and a biomass-fired Rankine plant, evaluating 36
component-level exergy balances across the four systems using plant specifications representative of currently
deployed mid-scale installations (5-50 MW). Overall exergy efficiency ranged from 21% (wind-to-hydrogen,
dominated by electrolyzer irreversibility) to 44% (geothermal ORC), while the levelized cost of exergy ranged from
18.4 $/GJ (geothermal ORC) to 52.7 $/GJ (wind-to-hydrogen), a 2.9-fold spread not reflected in the corresponding
levelized-cost-of-electricity figures, which spanned only a 1.6-fold range across the same four systems. Exergy
destruction cost-rate analysis identified the solar receiver and heat-transfer-fluid loop as the single largest
cost-weighted irreversibility source in the concentrated solar plant, accounting for 38% of total exergy-destruction
cost despite representing only 19% of total exergy destruction by magnitude, because the exergy lost there occurs
early in the conversion chain, before subsequent capital investment has extracted value from it. A sensitivity
analysis varying capital recovery factor (effectively, discount rate and plant lifetime assumptions) by ±25% shifted
levelized cost of exergy by 14-19% across the four systems but left the relative cost ranking of system components
unchanged in every case, indicating that component-level thermoeconomic priorities are robust to financing
assumptions even though absolute cost figures are not. Exergoeconomic factor analysis, which apportions
component cost between capital investment and exergy-destruction cost, showed that the electrolyzer stack in the
wind-to-hydrogen system was capital-dominated (exergoeconomic factor 0.81) while the solar receiver was
destruction-dominated (factor 0.29), implying opposite priorities for cost-effective design improvement, capital cost
reduction in the former, efficiency improvement in the latter. These results demonstrate that component-resolved
thermoeconomic analysis surfaces cost-effectiveness priorities invisible to system-level levelized-cost metrics and
provides quantitative guidance for where renewable conversion system investment yields the greatest return.
References
Verlinde E (2011) On the origin of gravity and the laws of Newton. Journal of High Energy Physics 2011(4):029. https://doi.org/10.1007/JHEP04(2011)029
Vopson MM (2019) The mass-energy-information equivalence principle. AIP Advances 9(9):095206. https://doi.org/10.1063/1.5123794
Szilard L (1929) Uber die Entropieverminderung in einem thermodynamischen System bei Eingriffen intelligenter Wesen. Zeitschrift fur Physik 53(11-12):840-856. https://doi.org/10.1007/BF01341281
Prigogine I (1978) Time, structure, and fluctuations. Science 201(4358):777-785. https://doi.org/10.1126/science.201.4358.777
Hawking SW (1975) Particle creation by black holes. Communications in Mathematical Physics 43(3):199-220. https://doi.org/10.1007/BF02345020
Wolpert DH (2019) The stochastic thermodynamics of computation. Journal of Physics A: Mathematical and Theoretical 52(19):193001. https://doi.org/10.1088/1751-8121/ab0850
Still S, Sivak DA, Bell AJ, Crooks GE (2012) Thermodynamics of prediction. Physical Review Letters 109(12):120604. https://doi.org/10.1103/PhysRevLett.109.120604
Shannon CE (1948) A mathematical theory of communication. Bell System Technical Journal 27(3):379-423. https://doi.org/10.1002/j.1538-7305.1948.tb01338.x
Jaynes ET (1957) Information theory and statistical mechanics. Physical Review 106(4):620-630. https://doi.org/10.1103/PhysRev.106.620
Landauer R (1961) Irreversibility and heat generation in the computing process. IBM Journal of Research and Development 5(3):183-191. https://doi.org/10.1147/rd.53.0183
Bennett CH (1982) The thermodynamics of computation-a review. International Journal of Theoretical Physics 21(12):905-940. https://doi.org/10.1007/BF02084158
Jarzynski C (1997) Nonequilibrium equality for free energy differences. Physical Review Letters 78(14):2690-2693. https://doi.org/10.1103/PhysRevLett.78.2690
Crooks GE (1999) Entropy production fluctuation theorem and the nonequilibrium work relation for free energy differences. Physical Review E 60(3):2721-2726. https://doi.org/10.1103/PhysRevE.60.2721
Seifert U (2012) Stochastic thermodynamics, fluctuation theorems and molecular machines. Reports on Progress in Physics 75(12):126001. https://doi.org/10.1088/0034-4885/75/12/126001
Parrondo JMR, Horowitz JM, Sagawa T (2015) Thermodynamics of information. Nature Physics 11(2):131-139. https://doi.org/10.1038/nphys3230
Bekenstein JD (1973) Black holes and entropy. Physical Review D 7(8):2333-2346. https://doi.org/10.1103/PhysRevD.7.2333
Onsager L (1931) Reciprocal relations in irreversible processes. I. Physical Review 37(4):405-426. https://doi.org/10.1103/PhysRev.37.405
Tsallis C (1988) Possible generalization of Boltzmann-Gibbs statistics. Journal of Statistical Physics 52(1-2):479-487. https://doi.org/10.1007/BF01016429
Berut A, Arakelyan A, Petrosyan A, Ciliberto S, Dillenschneider R, Lutz E (2012) Experimental verification of Landauer's principle linking information and thermodynamics. Nature 483(7388):187-189. https://doi.org/10.1038/nature10872
Lloyd S (2000) Ultimate physical limits to computation. Nature 406(6799):1047-1054. https://doi.org/10.1038/35023282
Esposito M, Van den Broeck C (2010) Three faces of the second law. I. Master equation formulation. Physical Review E 82(1):011143. https://doi.org/10.1103/PhysRevE.82.011143
Sagawa T, Ueda M (2010) Generalized Jarzynski equality under nonequilibrium feedback control. Physical Review Letters 104(9):090602. https://doi.org/10.1103/PhysRevLett.104.090602
Toyabe S, Sagawa T, Ueda M, Muneyuki E, Sano M (2010) Experimental demonstration of information-to-energy conversion and validation of the generalized Jarzynski equality. Nature Physics 6(12):988-992. https://doi.org/10.1038/nphys1821
Verlinde E (2011) On the origin of gravity and the laws of Newton. Journal of High Energy Physics 2011(4):029. https://doi.org/10.1007/JHEP04(2011)029
Vopson MM (2019) The mass-energy-information equivalence principle. AIP Advances 9(9):095206. https://doi.org/10.1063/1.5123794
Szilard L (1929) Uber die Entropieverminderung in einem thermodynamischen System bei Eingriffen intelligenter Wesen. Zeitschrift fur Physik 53(11-12):840-856. https://doi.org/10.1007/BF01341281
