Skip to main content Accessibility help
×
Hostname: page-component-586b7cd67f-t8hqh Total loading time: 0 Render date: 2024-11-24T05:41:07.992Z Has data issue: false hasContentIssue false

7 - Optimization and Exergoeconomics

Published online by Cambridge University Press:  19 March 2021

Efstathios Michaelides
Affiliation:
Texas Christian University
Get access

Summary

Mathematical optimization has been used since the early 20th century to improve the profitability of systems and processes. The time-value of money that leads to the concepts of net present value, annual worth, and annual cost of capital investment, is paramount in the optimization of energy systems that typically operate for very long periods. The method of thermoeconomics (which was formulated in the 1960s) and the similar method of exergoeconomics (which emerged in the 1990s) are two cost-analysis methods extensively used for the optimization of energy systems, components, and processes. Calculus optimization and the Lagrange undetermined multipliers are similarly used tools. This chapter begins with an exposition of the basic concepts of economics and optimization theory, and continues with the critical examination of the mathematical tools for the optimization of energy conversion systems using the exergy concept. The uncertainty of the optimum solution, which is an important consideration in all economic analyses, is clarified and an uncertainty analysis for exergy-consuming systems is presented.

Type
Chapter
Information
Publisher: Cambridge University Press
Print publication year: 2021

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Reclaitis, G. V., Ravindran, A., and Ragsdell, K.M., Engineering Optimization – Methods and Applications (New York: Wiley, 1983).Google Scholar
Hurlbert, G. H., Linear Optimization (New York: Springer, 2010).CrossRefGoogle Scholar
Michaelides, E. E., Alternative Energy Sources (Berlin: Springer, 2012).Google Scholar
Park, C. S., Contemporary Engineering Economics, 4th ed. (New Jersey: Pearson, 2007).Google Scholar
Sullivan, W. G., Wicks, E. M., and Luxhoj, J. T., Engineering Economy, 12th ed. (New Jersey: Pearson, 2003).Google Scholar
Michaelides, E. E., Energy, the Environment, and Sustainability (Boca Raton, FL: CRC Press, 2018).Google Scholar
Sayed, M. M. El, The Thermoeconomics of Energy Conversions (Oxford: Elsevier, 2003).Google Scholar
Tsatsaronis, G. and Cziesla, F., Thermoeconomics. In Meyers, R. A., ed., Encyclopedia of Physical Science and Technology, 3rd ed., 16 (Academic Press, 2002), 659–80.Google Scholar
Tsatsaronis, G., Thermoeconomic Analysis and Optimization of Energy Systems. Progress in Energy and Combustion Science, 19 (1993), 227–57.CrossRefGoogle Scholar
Bejan, A., Tsatsaronis, G., and Moran, M. J., Thermal Design and Optimization (New York: Wiley, 1996).Google Scholar
Sciubba, E., Exergo-Economics: Thermodynamic Foundations of a More Rational Resource Use. International Journal of Energy Research, 29 (2005), 613–36.CrossRefGoogle Scholar
Rocco, M. V., Colombo, E., and Sciubba, E., Advances in Exergy Analysis: A Novel Assessment of the Extended Exergy Accounting Method. Applied Energy, 113 (2014), 1405–20.Google Scholar
Frangopoulos, C. A., Recent Developments and Trends in Optimization of Energy Systems. Energy, 164 (2018), 1011–20.CrossRefGoogle Scholar
Cambero, C. and Sowlati, T., Incorporating Social Benefits in Multi-Objective Optimization of Forest-Based Bioenergy and Biofuel Supply Chains. Applied Energy, 178 (2016), 721–35.CrossRefGoogle Scholar
Lior, N., Quantifying Sustainability for Energy Development. Energy Bulletin 19, International Sustainable Energy Development Center under the Auspices of UNESCO (2015), 824.Google Scholar
Michaelides, E. E., A New Model for the Lifetime of Fossil Fuel Resources. Natural Resources Research, 26 (2017), 161–75.CrossRefGoogle Scholar
The U.S. Energy Information Administration www.eia.gov/totalenergy/data/annual/index.php, last visited November 2019.Google Scholar
Valero, A., Lozano, M. A., Serra, L., Tsatsaronis, G., Pisa, J., Frangopoulos, C., and von Spakovsky, M. R., CGAM Problem: Definition and Conventional Solution. Energy, 19 (1994), 279–86CrossRefGoogle Scholar

Save book to Kindle

To save this book to your Kindle, first ensure [email protected] is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Available formats
×

Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

Available formats
×