A novel procedure for finding the optimum values of design parameters of industrial twin-shaft gas turbines at various ambient temperatures is presented here. This paper focuses on being off design due to various ambient temperatures. The gas turbine modeling is performed by applying compressor and turbine characteristic maps and using thermodynamic matching method. The gas turbine power output is selected as an objective function in optimization procedure with genetic algorithm. Design parameters are compressor inlet guide vane angle, turbine exit temperature, and power turbine inlet nozzle guide vane angle. The novel constrains in optimization are compressor surge margin and turbine blade life cycle. A trained neural network is used for life cycle estimation of high pressure (gas generator) turbine blades. Results for optimum values for nozzle guide vane/inlet guide vane (23°/27°–27°/6°) in ambient temperature range of 25–45 ℃ provided higher net power output (3–4.3%) and more secured compressor surge margin in comparison with that for gas turbines control by turbine exit temperature. Gas turbines thermal efficiency also increased from 0.09 to 0.34% (while the gas generator turbine first rotor blade creep life cycle was kept almost constant about 40,000 h). Meanwhile, the averaged values for turbine exit temperature/turbine inlet temperature changed from 831.2/1475 to 823/1471°K, respectively, which shows about 1% decrease in turbine exit temperature and 0.3% decrease in turbine inlet temperature.
MartisDArthurRBrianP, et al.Engine performance improvement by controlling the low pressure compressor working line. J Eng Gas Turbines Power2006; 129: 755–760.
2.
BotrosKKGolshanHRogersD, et al.Evaluation of gas turbine outboard bleed air on overall engine efficiency and CO2e emission in natural gas compressor stations. J Eng Gas Turbines Power2013; 135: 101201–101201.
3.
BringhentiCBarbosaJ. Methodology for gas turbine performance improvement using variable-geometry compressors and turbines. Proc IMechE, Part A: J Power Energy2004; 218: 541–549.
4.
KimTSHwangSH. Part load performance analysis of recuperated gas turbines considering engine configuration and operation strategy. Energy2006; 31: 260–277.
5.
SilvaVKhatibVRFlemingW, et al.Performance optimization of gas turbine engine. Eng Appl Artif Intell2005; 18: 575–583.
6.
HaglindF. Variable geometry gas turbines for improving the part-load performance of marine combined cycles–gas turbine performance. Energy2010; 35: 562–570.
7.
HaglindF. Variable geometry gas turbines for improving the part-load performance of marine combined cycles–combined cycle performance. Appl Therm Eng2011; 31: 467–476.
8.
BakalisDStamatisPAnastassiosG. Improving hybrid SOFC-GT systems performance through turbomachinery design. Int J Energy Res2014; 38: 1975–1986.
9.
BakalisDStamatisPAnastassiosG. Optimization methodology of turbomachines for hybrid SOFC–GT applications. Energy2014; 70: 86–94.
10.
Mendoza E, Lin T and Jiang X. Reduction of gas turbine exhaust temperature limit due to HRSG limitations by change on control curve to optimize plant operation and performance. In: ASME Turbo Expo 2015: turbine technical conference and exposition. New York, NY: American Society of Mechanical Engineers, 2015.
11.
GhafirMALiYGWangL. Creep life prediction for aero gas turbine hot section component using artificial neural networks. J Eng Gas Turbines Power2014; 136: 031504.
12.
Ghafir MFA, Li YG, Singh R, et al. Impact of operating and health conditions on aero gas turbine: hot section creep life using a creep factor approach. In: Proceedings of turbo expo: power for land, sea, and air, 14–18 June 2010, Glasgow, UK, pp.533–545.
13.
ZaretskyEVLittJSHendricksRC, et al.Determination of turbine blade life from engine field data. J Propul Power2012; 28: 1156–1167.
14.
ParthasarathyGMenonSRichardsonK, et al.Neural network models for usage based remaining life computation. J Eng Gas Turbines Power2008; 130: 012508-012508–7.
15.
Sellers JF and Daniele CJ. DYNGEN: a program for calculating steady-state and transient performance of turbojet and turbofan engines, Patent NASA-TN-D-7901, E-8111, USA, 1975.
16.
Louis J, Hiraoka K and El-Masri MA. A comparative study of different means of turbine cooling on gas turbine performance. ASME Paper (83-GT), p.I80.
17.
El-MasriMA. On thermodynamic of gas turbine cycles, part 2: a model for expansion in cooled turbines. ASME J Eng Gas Turbine Power1986; 108: 151–159.
18.
ZhuPSaravanamuttooHIH. Simulation of an advanced twin spool industrial gas turbine and power. J Eng Gas Turbine Power1992; 114: 180–186.
19.
RashidzadehHHosseinalipourSMMohammadzadehA. The SGT-600 industrial twin-shaft gas turbine modeling for mechanical drive applications at the steady state conditions. J Mech Sci Technol2015; 29: 4473–4481.
20.
WangH, et al.A thermodynamic-cycle performance analysis method and application on a three-shaft gas turbine. Applied Thermal Engineering2017; 127: 465–472.
21.
GuC-w, et al.Development and application of a thermodynamic-cycle performance analysis method of a three-shaft gas turbine. Energy2016; 112: 307–321.
22.
DeuflhardP. A modified Newton method for the solution of ill-conditioned systems of nonlinear equations with application to multiple shooting. Numer Math1974; 22: 289–315.
23.
Ben-IsraelA. A Newton–Raphson method for the solution of systems of equations. J Math Anal Appl1966; 15: 243–252.
24.
WhiteNTourlidakisAElderR. Numerical investigations of performance optimization using variable guide vanes in a multistage compressor of a 6 MW gas turbine engine. Proc IMechE, Part A: J Power Energy2003; 217: 593–603.
25.
Saravanamuttoo HIH, Rogers GFC and Cohen H. Gas turbine theory. London, UK: Pearson Education, 2001.
26.
VanWylen G, Borgnakke C and Sonntag RE. Fundamentals of classical thermodynamics. Hoboken, NJ: Wiley, 1998.
27.
H cohen GR and Saravanamuttoo HIH. Gas turbine theory. Harlow, UK: Longman Group Limited, 2001.
28.
CoxJCHutchinsonDOswaldJI. The Westinghouse/Rolls-Royce WR-21 gas turbine variable area power turbine design. Power (MW)1995; 9258: 3.
29.
MartinBBrownAFinnisM. The influences of turbine blade mean temperature and component efficiencies on coolant optimization in the gas turbine. Proc IMechE, Part A: J Power Energy1997; 211: 181–190.
30.
El-MasriM. GASCAN – an interactive code for thermal analysis of gas turbine systems. J Eng Gas Turbines Power1988; 110: 201–209.
31.
Kim J, Kim TS, Lee JS, et al. Performance analysis of a turbine stage having cooled nozzle blades with trailing edge ejection. In: ASME Turbo Asia Conference, Jakarta, Indonesia, 5–7 November 1996, pp.1–8. New York, NY: American Society of Mechanical Engineers.
32.
Eshati S. An evaluation of operation and creep life of stationary gas turbine engine. PhD Thesis. Cranfield University, Bedford, UK, 2012.
33.
EshatiSAbuALaskaridisP, et al.Influence of water–air ratio on the heat transfer and creep life of a high pressure gas turbine blade. Appl Therm Eng2013; 60: 335–347.
34.
WoodM. Gas turbine hot section components: the challenge of ‘residual life’ assessment. Proc IMechE, Part A: J Power Energy2000; 214: 193–201.
35.
Rumelhart DE, Hinton GE and Williams RJ. Learning internal representations by error propagation. In: Parallel distributed processing: explorations in the microstructure of cognition. vol. 1. Cambridge, MA: MIT Press, 1986, pp.318–362.
36.
Ghafir M. Performance based creep life estimation for gas turbines application. PhD Thesis. Cranfield University, Bedford, UK, 2011.
37.
Bert J. Application of a design optimization strategy to multi-stage compressor matching. MS Thesis, Department of Aeronautics and Astronautics, Massachusetts Institute of Technology, 2006.
38.
AtashkariK, et al.Thermodynamic Pareto optimization of turbojet engines using multi-objective genetic algorithms. Int J Therm Sci2005; 44: 1061–1071.
39.
SayyaadiHAminianH. Multi-objective optimization of a recuperative gas turbine cycle using non-dominated sorting genetic algorithm. Proc IMechE, Part A: J Power Energy2011; 225: 1041–1051.
40.
Walsh PP and Fletcher P. Gas turbine performance. 2nd ed. Blackwell, Oxford, 2004.
Nyberg I. Continued product development/possibilities SGT-600/700 Part 1. Lincoln, UK: Siemens Industrial Turbomachinery.
43.
Siemens. Maintenance plan SGT-600/GT10A/B1/B2, 2006, p.8.
44.
ISO 3977-9: 1999. Internal Standard. Gas turbine, procurement, Part 9: reliability, availability, maintainability and safety.
45.
Olov A, Navrotsky V and Santammaria S. Siemens's medium size gas turbine continued product and operation improvement program. Lincoln, UK: Siemens Industrial Turbomachinery, 2010.
46.
Bringhenti C and Barbosa J. Analysis of gas turbine off-design safe operation using variable geometry compressor. In: Proceedings of the COBEM, COBEM2003-0230, São Paulo, SP, November 2003, pp.10–14.
47.
MohammadiEMontazeri-GhM. Simulation of full and part-load performance deterioration of industrial two-shaft gas turbine. J Eng Gas Turbines Power2014; 136: 092602–092602.
48.
Rinman J. Maintenance plan SGT-600 mechanical drive. Lincoln, UK: Siemens Industrial Turbomachinery.
