6 th World Congress on Structural and Multidisciplinary Optimization Rio de Janeiro, 30 May - 03 June 2005, Brazil Exergoeconomic Improvement: an Alternative to Conventional Mathematical Optimization of Complex Thermal Systems Leonardo S. Vieira, a João L. Donatelli, b Manuel E. Cruz c a Special Technologies Department, CEPEL-Electrical Energy Research Center Rio de Janeiro, RJ, Brazil E-mail: lsrv@cepel.br b Department of Mechanical Engineering, UFES-Federal University of Espírito Santo Vitória, ES, Brazil E-mail: joaoluiz@npd.ufes.br c Department of Mechanical Engineering, COPPE/UFRJ-Federal University of Rio de Janeiro Rio de Janeiro, RJ, Brazil E-mail: manuel@serv.com.ufrj.br 1. Abstract In this paper we present the development and automated implementation of an iterative exergoeconomic methodology for improvement of thermal systems, which integrates exergoeconomics with a process simulator, so as to be applicable to real, complex plants. The process simulator provides the solution of the mass, energy and exergy balance equations for the system and exergoeconomics provides insights for system improvement. The proposed methodology represents an alternative to conventional mathematical optimization techniques with respect to application to large systems, because it reduces substantially the number of variables that should be considered in the improvement process. By exploiting the computational power of a professional process simulator, the proposed integrated approach permits the optimization routine to ignore the variables associated with the thermodynamic balance equations and thus to deal only with the decision variables. In addition, the methodology combines recent available exergoeconomic techniques with new qualitative and quantitative criteria for the following tasks: (i) identification of decision variables which affect system total cost and exergetic efficiency; (ii) hierarchical classification of components; (iii) identification of predominant terms in the system total cost; and (iv) choice of main decision variables in the iterative process. These criteria further decrease the number of decision variables that must be simultaneously handled in the improvement routine. To show the strengths and potential advantages of the proposed methodology, it is here applied to a complex 24-component cogeneration system, which includes all the major equipment of a typical thermal plant and requires more than 800 variables for its simulation. The results obtained are presented and discussed in detail and are compared to those reached using a conventional mathematical optimization procedure coupled to a process simulator. For engineering purposes, due to the large uncertainties associated with cost information and normal operational fluctuations of thermodynamic parameters of complex thermal systems, improvement of the system is often more cost effective and less time consuming than optimization of the system. 2. Keywords: exergoeconomic improvement, complex thermal systems, exergy 3. Introduction The growing concern about conservation of energy and environmental preservation has led to the development and intense application of techniques based on the second law of thermodynamics, such as exergoeconomic analysis - an exergy analysis combined with an economic evaluation. Exergoeconomic analysis can address environmental issues, reveal the cost formation process of system products and aid system optimization [1], [2], [3], [4], [5], [10]. According to El-Sayed and Gaggioli [6], [7], exergoeconomic methods can be grouped in two classes: the algebraic methods and the calculus methods. The algebraic methods use algebraic balance equations, always require auxiliary cost equations for each component, focus essentially on the cost formation process and determine average costs. On the other hand, calculus methods use differential equations, such that system cost flows are obtained in conjunction with optimization procedures based on the method of Lagrange multipliers and determine marginal costs. All methods, whether algebraic or calculus, are considered subjective. While algebraic methods are considered subjective with respect to the auxiliary costing criteria, calculus methods are considered subjective in the way functional diagrams are conceived [1]. Most exergoeconomic optimization theories have been applied to relatively simple systems only. Conventional mathematical optimization, exergoeconomic or not, of real thermal systems are large scale problems, due to their complicated nonlinear characteristics and because the mass, energy and exergy (or entropy) balance equations must be introduced in the problem as restrictions [8]. To efficiently optimize complex thermal systems, it is thus desired, if not required, to integrate optimization algorithms with a professional thermodynamic process simulator, such that the optimization task does not have to deal with the mass, energy and exergy balance equations. Furthermore, according to Jaluria [8], it is important to focus on the dominant decision variables, rather than manipulating all variables that might affect the solution. In this paper we present the development and automated implementation of a new approach for design improvement of complex thermal systems, based on the integration of an iterative methodology for exergoeconomic improvement with a professional process simulator. As such, the proposed methodology is algebraic and should be easily mastered and applied by practising engineers of the industrial community. The iterative algorithm efficiently combines well-known exergoeconomic techniques [2], [3] with new qualitative and quantitative criteria for the following tasks: (i) identification of variables that affect system total cost and exergetic efficiency; (ii) hierarchical classification of components; (iii) identification of predominant terms in the system total cost; and (iv)