Research Papers: Gas Turbines: Electric Power

Maximization of the Profit of a Complex Combined-Cycle Cogeneration Plant Using a Professional Process Simulator

[+] Author and Article Information
Leonardo S. Vieira

DTE, Electric Power Research Center (CEPEL), Avenida Hum s/n, CP 68007, Cidade Universitária, Rio de Janeiro 21944-970, Brazillsrv@cepel.br

Carlos F. Matt

DIE, Electric Power Research Center (CEPEL), Avenida Hum s/n, CP 68007, Cidade Universitária, Rio de Janeiro 21944-970, Brazilcfmatt@cepel.br

Vanessa G. Guedes

DTE, Electric Power Research Center (CEPEL), Avenida Hum s/n, CP 68007, Cidade Universitária, Rio de Janeiro 21944-970, Brazilvanessag@cepel.br

Manuel E. Cruz

DEM/Politécnica/COPPE, Federal University of Rio de Janeiro (UFRJ), CT, CP 68503, Cidade Universitária, Rio de Janeiro 21945-970, Brazilmanuel@mecanica.coppe.ufrj.br

Fernando V. Castellões

Petrobras R&D Center, CENPES, Gas & Energy, Avenida Horácio Macedo 950, Cidade Universitária, Rio de Janeiro 21941-915, Brazilfcastelloes@petrobras.com.br

J. Eng. Gas Turbines Power 132(4), 041801 (Jan 15, 2010) (10 pages) doi:10.1115/1.3204506 History: Received January 24, 2009; Revised June 16, 2009; Published January 15, 2010; Online January 15, 2010

The high cost of energy resources has driven a strong and continued quest for their optimal utilization. In this context, modern thermoeconomic optimization techniques have been developed to analyze and design improved energy systems, leading to a better compromise between energetic efficiency and cost. Thermoeconomic optimization can be parametric (plant configuration is fixed), applicable both at the design phase or operation phase of a system, or structural (plant configuration may vary). In practice, mathematical thermoeconomic optimization may be accomplished in two ways: (i) the conventional way, which manipulates all pertinent equations simultaneously or (ii) integrated with a professional process simulator, such that the equations are manipulated separately. In the latter case, the simulator deals with the thermodynamic property and balance equations, while an external optimization routine, linked to the simulator, deals with the economic equations and objective function. In this work, a previous implementation of an integrated approach for parametric mathematical thermoeconomic optimization of complex thermal systems is applied to an actual combined-cycle cogeneration plant located in the outskirts of the city of Rio de Janeiro in Brazil. The plant contains more than 60 thermal components, including two gas turbines, one steam turbine, and two heat recovery steam generators. Several hundred variables are required to simulate the plant at one operational steady-state. The plant produces 380 MW of power nominally, and exports a mass flow rate between 200 tons/h and 400 tons/h of superheated process steam, at 45 bars and 404°C, to a neighboring refinery. The simulator is the THERMOFLEX software, which interfaces with the Microsoft Excel program. The optimization routine is written in the Visual Basic for Applications language and is based on Powell’s method. The cogeneration plant operates subjected to time-changing economic scenarios, because of varying fuel, electricity, and steam prices. Thus, to manage the plant, it is necessary to vary the operational state appropriately as the economic parameters change. For a prescribed economic scenario, previous work determined the minimum operational cost, when a fixed contracted hourly-rate of process steam was to be exported, while a variable amount of electrical power was produced. In this paper, a broader optimization problem is formulated and solved, for which the objective is to maximize the plant profit under different economic scenarios. It is shown that the optimal operating conditions depend on the economic parameters, and do not necessarily imply maximum efficiency. The integrated optimization approach proves effective, robust, and helpful for optimal plant management.

Copyright © 2010 by American Society of Mechanical Engineers
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Figure 1

Schematic flow diagram of the combined-cycle cogeneration plant

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Figure 2

Schematic flow diagram of the off-design model for the plant (component numbers are italicized, flow numbers appear in normal font)

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Figure 3

Optimization results, OF versus NC, for the first set of exercises

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Figure 4

Optimization results, OF versus NC, for the second set of exercises



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