Abstract

The paper presents two different optimization methods for the cost-effective design of energy conversion systems. Starting point of the optimization is a complex superstructure that allows several alternative design specifications for a combined-cycle-based cogeneration plant to be studied. Depending on the user specified demands for electricity and process steam, the optimization algorithm performs a simultaneous structural and process variable optimization of the design, to minimize the levelized total costs of the plant products. Mathematical programming and specialized genetic algorithms are used as optimization algorithms. These do not only differ largely in their optimization approach but also have different requirements for the modeling of the superstructure. Several optimization cases are presented to examine the applicability of both algorithms on the present optimization problem. A concluding comparison reveals the advantages and disadvantages of each optimization method.

Full Text

Published Version

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.