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A Genetic Algorithm for Optimizing Heat Recovery Steam Generators of Combined Cycle Power Plants

[+] Author Affiliations
Roberto Carapellucci, Lorena Giordano

University of L’Aquila, L’Aquila, Italy

Paper No. IMECE2011-63703, pp. 121-130; 10 pages
doi:10.1115/IMECE2011-63703
From:
  • ASME 2011 International Mechanical Engineering Congress and Exposition
  • Volume 4: Energy Systems Analysis, Thermodynamics and Sustainability; Combustion Science and Engineering; Nanoengineering for Energy, Parts A and B
  • Denver, Colorado, USA, November 11–17, 2011
  • Conference Sponsors: ASME
  • ISBN: 978-0-7918-5490-7
  • Copyright © 2011 by ASME

abstract

Improving performance of combined cycle power plants has been the target of numerous investigations. Most of the researchers have focused their attention on the heat recovery steam generator (HRSG), the connecting equipment between the gas turbine group and the steam section. On the other hand, almost all equipment in a combined cycle is a fairly standard design available from a manufacturer, while the HRSG is one of the few components that may be somewhat customized. In fact, the HRSG provides many different design options with respect to the layout of heat transfer sections and their operating parameters. The aim of this work is the development of a model for optimizing the main operating parameters of the heat recovery steam generator of a CCGT. The thermodynamic behaviour of the power plant has been simulated through the commercial software GateCycle, whereas the optimization has been carried out using a genetic algorithm. The objective function to be minimized is the cost of electricity, evaluated through a cash flow analysis in constant or in current dollars. Two CCGT power plant configurations, with one or three-pressure reheat HRSG, are simulated and optimized, evaluating the influence of fuel price variation on the optimal operating parameters of HRSG.

Copyright © 2011 by ASME

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