Heat Recovery Steam Generator (HRSG) systems in conjunction with a primary gas turbine and a secondary steam turbine can provide advanced modern power generation with high thermal efficiency at low cost. To achieve such low cost efficiencies, near optimal settings of parameters of the HRSG must be employed. Unfortunately, current approaches to obtaining such parameter settings are very limited. The published literature associated with the Tabu Search (TS) metaheuristic has shown conclusively that it is a powerful methodology for the solution of very challenging large practical combinatorial optimization problems. This report documents a hybrid TS-direct pattern search (TS-DPS) approach and applied to the thermoeconomic optimization of a three pressure level HRSG system. To the best of our knowledge, this algorithm is the first to be developed that is capable of successfully solving a practical HRSG system.
A requirement of the TS-DPS technique was the creation of a robust simulation module to evaluate the associated extremely complex 19 variable objective function. The simulation module was specially constructed to allow the evaluation of infeasible solutions, a highly preferable capability for methods like TS-DPS. The direct pattern search context is explicitly embodied within the TS neighborhoods permitting different neighborhood structures to be tested and compared. Advanced TS is used to control the associated continuum discretization with minimal memory requirements. Our computational studies show that TS is a very effective method for solving this HRSG optimization problem. / text
| Identifer | oai:union.ndltd.org:UTEXAS/oai:repositories.lib.utexas.edu:2152/ETD-UT-2010-05-811 |
| Date | 11 November 2010 |
| Creators | Liu, Zelong |
| Source Sets | University of Texas |
| Language | English |
| Detected Language | English |
| Type | thesis |
| Format | application/pdf |
Page generated in 0.0019 seconds