TSOUTSANIS, Elias, LI, Y.G., PILIDIS, P. and NEWBY, M. (2012). Part-load performance of gas turbines - Part II: Multi-point adaptation with compressor map generation and ga optimization. In: ASME 2012 Gas Turbine India Conference. Mumbai, Maharashtra, ASME, 743-751.
Full text not available from this repository.Abstract
Accurate gas turbine performance simulation is a vital aid to the operational and maintenance strategy of thermal plants having gas turbines as their prime mover. Prediction of the part load performance of a gas turbine depends on the quality of the engine's component maps. Taking into consideration that compressor maps are proprietary information of the manufacturers, several methods have been developed to encounter the above limitation by scaling and adapting component maps. This part of the paper presents a new off-design performance adaptation approach with the use of a novel compressor map generation method and Genetic Algorithms (GA) optimization. A set of coefficients controlling a generic compressor performance map analytically is used in the optimization process for the adaptation of the gas turbine performance model to match available engine test data. The developed method has been tested with off-design performance simulations and applied to a GE LM2500+ aeroderivative gas turbine operating in Manx Electricity Authority's combined cycle power plant in the Isle of Man. It has been also compared with an earlier off-design performance adaptation approach, and shown some advantages in the performance adaptation. Copyright © 2012 by ASME.
Item Type: | Book Section |
---|---|
Additional Information: | Conference of ASME 2012 Gas Turbine India Conference, GTINDIA 2012 ; Conference Date: 1 December 2012 Through 1 December 2012; Conference Code:100944 |
Uncontrolled Keywords: | Compressor maps; Compressor performance; Gas turbine performance; Maintenance strategies; Multipoint adaptation; Off-design performance; Performance adaptation; Proprietary information, Combined cycle power plants; Compressors; Design; Genetic algorithms; Optimization, Gas turbines |
Departments - Does NOT include content added after October 2018: | Faculty of Science, Technology and Arts > Department of Engineering and Mathematics |
Identification Number: | https://doi.org/10.1115/GTINDIA2012-9581 |
Page Range: | 743-751 |
Depositing User: | Elias Tsoutsanis |
Date Deposited: | 25 Aug 2017 09:13 |
Last Modified: | 18 Mar 2021 17:15 |
URI: | https://shura.shu.ac.uk/id/eprint/16185 |
Actions (login required)
View Item |
Downloads
Downloads per month over past year