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A Physics-Based Dynamic Model for Boilers: Part 2 — Model Reduction in a Cogeneration Application

[+] Author Affiliations
Matthew J. Blom, Michael J. Brear, Chris G. Manzie, Ashley P. Wiese

University of Melbourne, Parkville, Australia

Paper No. GT2017-63546, pp. V006T05A008; 10 pages
doi:10.1115/GT2017-63546
From:
  • ASME Turbo Expo 2017: Turbomachinery Technical Conference and Exposition
  • Volume 6: Ceramics; Controls, Diagnostics and Instrumentation; Education; Manufacturing Materials and Metallurgy
  • Charlotte, North Carolina, USA, June 26–30, 2017
  • Conference Sponsors: International Gas Turbine Institute
  • ISBN: 978-0-7918-5091-6
  • Copyright © 2017 by ASME

abstract

This paper is the second part of a two part study that develops, validates and integrates a one-dimensional, physics-based, dynamic boiler model. Part 1 of this study [1] extended and validated a particular modelling framework to boilers. This paper uses this framework to first present a higher order model of a gas turbine based cogeneration plant. The significant dynamics of the cogeneration system are then identified, corresponding to states in the gas path, the steam path, the gas turbine shaft, gas turbine wall temperatures and boiler wall temperatures. A model reduction process based on time scale separation and singular perturbation theory is then demonstrated.

Three candidate reduced order models are identified using this model reduction process, and the simplest, acceptable dynamic model of this integrated plant is found to require retention of both the gas turbine and boiler wall temperature dynamics. Subsequent analysis of computation times for the original physics-based one-dimensional model and the candidate, reduced order models demonstrates that significantly faster than real time simulation is possible in all cases. Furthermore, with systematic replacement of the algebraic states with feedforward maps in the reduced order models, further computational savings of up to one order of magnitude can be achieved. This combination of model fidelity and computational tractability suggest suggests that the resulting reduced order models may be suitable for use in model based control of cogeneration plants.

Copyright © 2017 by ASME

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