A new iterative approach to the optimization of thermal energy systems: Application to the regenerative Brayton cycle

• Published in: Proceedings of the Institution of Mechanical Engineers. Part A, Journal of power and energy Vol. 224; no. 3; pp. 313 - 327
• Main Authors: Seyyedi, S M, Ajam, H, Farahat, S
• Format: Journal Article
• Language: English
• Published: London, England SAGE Publications 01.01.2010; SAGE PUBLICATIONS, INC
• Subjects: Brayton cycle; Coding; Cost analysis; Design analysis; Design engineering; Destruction; Electric power plants; Evolutionary algorithms; Exergy; Financing; Investment; Iterative methods; Mathematical models; Matlab; Mechanical engineering; Methods; Optimization; Power plants; Regenerative; Sensitivity analysis; Thermal energy; Thermodynamics; Thermoelectricity; structural method; optimization; exergoeconomic analysis
• ISSN: 0957-6509; 2041-2967
• DOI: 10.1243/09576509JPE862

Abstract Optimization is one of the most interesting and essential subjects in the design of energy systems. In the present work, a new iterative approach for the optimization of complex thermal power plants based on the exergoeconomic analysis and the structural optimization method is proposed. Exergoeconomic analysis is used to determine the sum of the investment and exergy destruction cost flowrates for each component. A numerical sensitivity analysis is performed in order to determine the importance of each decision variable, and by using the structural optimization method, the total cost flowrate is minimized. The advantages of this new iterative methodology are: (a) it can be applied to the large real complex thermal systems, (b) the procedure of optimization is performed without user interface, and (c) since a numerical sensitivity analysis is used, convergency is improved. A simple regenerative Brayton cycle was used as an example to demonstrate how this proposed methodology minimizes the system's total cost flowrate. For comparison of results, a real coding evolutionary algorithm was developed in MATLAB and the optimum solution was obtained.