Modelling of Dry-Low Emission Gas Turbine Fuel System using First Principle Data-Driven Method

  • Madiah Binti Omar Universiti Teknologi PETRONAS, 32610 Bandar Seri Iskandar, Perak, Malaysia http://orcid.org/0000-0002-3975-1253
  • Rosdiazli Ibrahim Universiti Teknologi PETRONAS, 32610 Bandar Seri Iskandar, Perak, Malaysia
  • Mohd Faris Abdullah Universiti Teknologi PETRONAS, 32610 Bandar Seri Iskandar, Perak, Malaysia
  • Mohammad Haizad Mohd Tarik Universiti Teknologi PETRONAS, 32610 Bandar Seri Iskandar, Perak, Malaysia

Abstract

Achieving reliable power generation from Dry Low Emission gas turbines together with low CO2 and NOx discharge is a great challenge, as the rigorous control strategy is susceptible to frequent trips. Therefore, it is crucial to establish a dynamic model of the turbine (such as the one commonly attributed to Rowen) to ascertain the stability of the system. However, the major distinctive fuel system design in the DLE gas turbine is not constructed in the well-established model. With this issue in mind, this paper proposes a modelling approach to the DLE gas turbine fuel system which consists of integrating the main and pilot gas fuel valve into Rowen’s model, using the First Principle Data-Driven (FPDD) method. First, the structure of the fuel system is determined and generated in system identification. Subsequently, the validated valve models are integrated into Rowen’s model as the actual setup of the DLE gas turbine system. Ultimately, the core of this modelling approach is fuel system integration based on the FPDD method to accurately represent the actual signals of the pilot and main gas fuel valves, gas fuel flow and average turbine temperature. Then, the actual signals are used to validate the whole structure of the model using MAE and RMSE analysis. The results demonstrate the high accuracy of the DLE gas turbine model representation for future utilization in fault identification and prediction study.

Author Biographies

Madiah Binti Omar, Universiti Teknologi PETRONAS, 32610 Bandar Seri Iskandar, Perak, Malaysia
Madiah B. Omar received the B.S. degree in chemical engineering from Universiti Teknologi PETRONAS, Perak, Malaysia in 2012 and the M.Eng. degree in Analytical Instruments, Measurement and Sensor Technology from Coburg University of Applied Sciences and Arts, Coburg, Germany, in 2014. She is currently pursuing the Ph.D. degree in electrical \& electronic engineering at Universiti Teknologi PETRONAS, Perak, Malaysia. Her research interest includes the gas turbine models, process control and fault prediction technique.
Rosdiazli Ibrahim, Universiti Teknologi PETRONAS, 32610 Bandar Seri Iskandar, Perak, Malaysia
Rosdiazli B. Ibrahim received the B.Eng. degree in electrical engineering from Universiti Putra Malaysia, Kembangan, Malaysia, in 1996, the M.Sc. degree in automation and control from Newcastle University, Newcastle upon Tyne, U.K., in 2000, and the Ph.D. degree in electrical and electronic engineering from the University of Glasgow, Glasgow, U.K., in 2008. He is an Associate Professor with the Department of Electrical and Electronics Engineering at Universiti Teknologi PETRONAS (UTP), Seri Iskandar, Perak, Malaysia. He is currently, The Dean, Centre for Graduate Studies, UTP. His current research interests include intelligent control and non-linear multi-variable process modeling for control application.
Mohd Faris Abdullah, Universiti Teknologi PETRONAS, 32610 Bandar Seri Iskandar, Perak, Malaysia
Mohd Faris B. Abdullah completed his PhD at Universiti Teknologi PETRONAS (UTP) in 2015. He is currently a senior lecturer at UTP since 2009. Prior to that, he was working with Tenaga Nasional Berhad (TNB) since 1989 and serving distribution division for 12 years and transmission division for 8 years. His experience in the distribution division includes planning, construction, maintenance, metering, and protection. In the transmission division, he was working in the maintenance department that responsible for substation, lines, cables, protection, telecontrol and technical support. He is Professional Engineer (Board of Engineers Malaysia), Competent Engineer (Energy Commission), member of The Institute of Electrical \& Electronics Engineers (IEEE) and member of The Institute Of Engineers, Malaysia (IEM). His research field is in power systems.
Mohammad Haizad Mohd Tarik, Universiti Teknologi PETRONAS, 32610 Bandar Seri Iskandar, Perak, Malaysia
Mohammad Haizad B. Mohd Tarik received the B.Eng. degree in electrical and electronic engineering from Universiti Teknologi PETRONAS, Malaysia in 2004. He is currently pursuing the MSc degree in electrical and electronic engineering at Universiti Teknologi PETRONAS, Malaysia. His research interest includes the development of gas turbine model using a black box approach, optimization of machine learning algorithm and predictive analytics.

References

1.Kwon, H.M., Moon, S.W., Kim, T.S., Kang, D.W.,
Sohn, J.L., and Lee, J. (2019) A study on 65 % potential
eciency of the gas turbine combined cycle.
Journal of Mechanical Science and Technology, 33
(9), 4535{4543.
2.Huitenga, H., and Norster, E.R. (2014) Development
Approach to the Dry Low Emission Combustion
System of MAN Diesel and Turbo Gas Turbines. Vol-
ume 4A: Combustion Fuels and Emissions.
3.Suman, A., Casari, N., Fabbri, E., Pinelli, M., Mare,
L. di, and Montomoli, F. (2018) Gas Turbine Fouling
Tests: Review Critical Analysis, and Particle Impact
Behavior Map. Journal of Engineering for Gas Tur-
bines and Power, 141 (3).
4.Rigo-Mariani, R., Zhang, C., Romagnoli, A., Kraft,
M., Ling, K.V., and Maciejowski, J.M. (2019) A Combined
Cycle Gas Turbine Model for Heat and Power
Dispatch Subject to Grid Constraints. IEEE Transac-
tions on Sustainable Energy, 1{1.
5.Hazel, T., Peck, G., and Mattsson, H. (2014) Industrial
Power Systems Using Dry Low Emission Turbines.
IEEE Transactions on Industry Applications,
50 (6), 4369{4378.
6.Nemitallah, M.A., Rashwan, S.S., Mansir, I.B., Abdelhafez,
A.A., and Habib, M.A. (2018) Review of
Novel Combustion Techniques for Clean Power Production
in Gas Turbines. Energy & Fuels, 32 (2),
979{1004.
7.Abdelhafez, A., Rashwan, S.S., Nemitallah, M.A.,
and Habib, M.A. (2018) Stability map and shape of
premixed CH4/O2/CO2
ames in a model gas-turbine
combustor. Applied Energy, 215, 63{74.
8.Serbin, S.I., Matveev, I.B., and Mostipanenko, G.B.
(2011) Investigations of the Working Process in a
\Lean-Burn" Gas Turbine Combustor With Plasma
Assistance. IEEE Transactions on Plasma Science,
39 (12), 3331{3335.
9.Massey, J.C., Chen, Z.X., and Swaminathan, N.
(2019) Lean Flame Root Dynamics in a Gas Turbine
Model Combustor. Combustion Science and Technol-
ogy, 191 (5-6), 1019{1042.
10.Zettervall, N., Worth, N.A., Mazur, M., Dawson,
J.R., and Fureby, C. (2019) Large eddy simulation of
CH4-air and C2H4-air combustion in a model annular
gas turbine combustor. Proceedings of the Combus-
tion Institute, 37 (4), 5223{5231.
11.Aldi, N., Casari, N., Morini, M., Pinelli, M., Spina,
P.R., and Suman, A. (2018) Gas Turbine Fouling: A
Comparison Among 100 Heavy-Duty Frames. Journal
of Engineering for Gas Turbines and Power, 141 (3).
12.Fentaye, A.D., Gilani, S.I.U.-H., Baheta, A.T., and
Li, Y.-G. (2018) Performance-based fault diagnosis
of a gas turbine engine using an integrated support
vector machine and articial neural network method.
Proceedings of the Institution of Mechanical Engi-
neers Part A: Journal of Power and Energy, 233 (6),
786{802.
13.Tsoutsanis, E., and Meskin, N. (2019) Dynamic
performance simulation and control of gas turbines
used for hybrid gas/wind energy applications. Applied
Thermal Engineering, 147, 122{142.
14.Iqbal, M.M.M., Sarumathi, S., Jothi, K.R., and
Brindadevi, A. (2018) Model order reduction of heavy
duty gas turbine power plants with eld test parameters.
International Transactions on Electrical Energy
Systems, 29 (2), e2703.
15.Mohammadian, P.K., and Saidi, M.H. (2019) Simulation
of startup operation of an industrial twin-shaft
gas turbine based on geometry and control logic. En-
ergy, 183, 1295{1313.
16.Rowen, W.I. (1983) Simplied Mathematical Representations
of Heavy-Duty Gas Turbines. Journal of
Engineering for Power, 105 (4), 865{869.
17.Chaibakhsh, A., and Amirkhani, S. (2018) A simulation
model for transient behaviour of heavy-duty gas turbines. Applied Thermal Engineering, 132,
115{127.
18.Rahman, M., Zaccaria, V., Zhao, X., and Kyprianidis,
K. (2018) Diagnostics-Oriented Modelling of
Micro Gas Turbines for Fleet Monitoring and Maintenance
Optimization. Processes, 6 (11), 216.
19.Kang, D.W., and Kim, T.S. (2018) Model-based
performance diagnostics of heavy-duty gas turbines
using compressor map adaptation. Applied Energy,
212, 1345{1359.
20.Montazeri-Gh, M., Fashandi, S.A.M., and
Abyaneh, S. (2018) Real-time simulation test-bed for
an industrial gas turbine engine's controller. Mechan-
ics & Industry, 19 (3), 311.
21.Liu, Z., and Karimi, I.A. (2018) Simulating
combined cycle gas turbine power plants in Aspen
HYSYS. Energy Conversion and Management, 171,
1213{1225.
22.Pires, T.S., Cruz, M.E., Colaco, M.J., and Alves,
M.A.C. (2018) Application of nonlinear multivariable
model predictive control to transient operation of a
gas turbine and NOX emissions reduction. Energy,
149, 341{353.
23.Caceres, I.E., Monta~nes, R.M., and Nord, L.O.
(2018) Flexible operation of combined cycle gas turbine
power plants with supplementary ring. Journal
of Power Technologies, 98 (2), 188{197.
24.Yee, S.K., Milanovic, J.V., and Hughes, F.M.
(2008) Overview and Comparative Analysis of Gas
Turbine Models for System Stability Studies. IEEE
Transactions on Power Systems, 23 (1), 108{118.
25.Gomez, F.J., Chaves, M.A., Vanfretti, L., and
Olsen, S.H. (2018) Multi-Domain Semantic Information
and Physical Behavior Modeling of Power Systems
and Gas Turbines Expanding the Common Information
Model. IEEE Access, 6, 72663{72674.
26.Huang, D., Chen, J.-wei, Zhou, D.-ji, Zhang, H.-
sheng, and Su, M. (2018) Simulation and analysis of
humid air turbine cycle based on aeroderivative threeshaft
gas turbine. Journal of Central South University,
25 (3), 662{670.
27.Tarik, M.H.M., Omar, M., Abdullah, M.F., and
Ibrahim, R. (2017) Modelling of dry low emission gas
turbine using black-box approach. TENCON 2017 -
2017 IEEE Region 10 Conference.
28.Pondini, M., Signorini, A., Colla, V., and Barsali,
S. (2019) Analysis of a simplied Steam Turbine governor
model for power system stability studies. Energy
Procedia, 158, 2928{2933.
29.Kim, D.-J., Moon, Y.-H., Choi, B.-S., Ryu, H.-
S., and Nam, H.-K. (2018) Impact of a Heavy-Duty
Gas Turbine Operating Under Temperature Control
on System Stability. IEEE Transactions on Power Sys-
tems, 33 (4), 4543{4552.
30.Balamurugan, S., Janarthanan, N., and Chandrakala,
K.R.M.V. (2016) Small and large signal modeling
of heavy duty gas turbine plant for load frequency
control. International Journal of Electrical
Power & Energy Systems, 79, 84{88.
31.Kumar, S.S., Xavier, R.J., and Balamurugan, S.
(2016) Small signal modelling of gas turbine plant for
load frequency control. 2016 Biennial International
Conference on Power and Energy Systems: Towards
Sustainable Energy (PESTSE).
32.Eslami, M., Shayesteh, M.R., and Pourahmadi, M.
(2018) Optimal Design of PID-Based Low-Pass Filter
for Gas Turbine Using Intelligent Method. IEEE
Access, 6, 15335{15345.
33.Khamseh, S.A., and Fatehi, A. (2017) Performance
monitoring of heavy duty gas turbines based
on Bayesian and Dempster-Shafer theory. 2017 In-
ternational Conference on Electrical and Information
Technologies (ICEIT).
34.Meegahapola, L., and Flynn, D. (2015) Characterization
of Gas Turbine Lean Blowout During Frequency
Excursions in Power Networks. IEEE Transactions on
Power Systems, 30 (4), 1877{1887.
35.Omar, M., Tarik, M.H.M., Ibrahim, R., and Abdullah,
M.F. (2017) Suitability study on using rowen's
model for dry-low emission gas turbine operational
performance. TENCON 2017 - 2017 IEEE Region 10
Conference.
36.Czop, P., Kost, G., S lawik, D., and Wszo lek,
G. (2011) Formulation and identication of rstprinciple
data-driven models. Journal of Achieve-
ments in materials and manufacturing Engineering,
44 (2), 179{186.
37.Czop, P., S lawik, D., and Wszo lek, G. (2011)
Demonstration of First-Principle Data-Driven models
using numerical case studies. Journal of Achieve-
ments in Materials and Manufacturing Engineering,
45 (2), 170{177.
38.Winter, R., Montanari, F., Noe, F., and Clevert,
D.-A. (2019) Learning continuous and datadriven
molecular descriptors by translating equivalent
chemical representations. Chemical science, 10 (6),
1692{1701.
39.Rowen, W.I. (1992) Simplied mathematical representations
of single shaft gas turbines in mechanical drive service. ASME 1992 international gas turbine
and aeroengine congress and exposition.
40.Ayed, A.H., Kusterer, K., Funke, H.H.-W., Keinz,
J., and Bohn, D. (2017) CFD based exploration of the
dry-low-NOx hydrogen micromix combustion technology
at increased energy densities. Propulsion and
Power Research, 6 (1), 15{24.
41.Funke, H.H.W., Beckmann, N., Keinz, J., and
Abanteriba, S. (2018) Comparison of Numerical Combustion
Models for Hydrogen and Hydrogen-Rich Syngas
Applied for Dry-Low-Nox-Micromix-Combustion.
Journal of Engineering for Gas Turbines and Power,
140 (8).
42.Hermann, J., Greifenstein, M., Boehm, B., and
Dreizler, A. (2019) Experimental investigation of
global combustion characteristics in an eusion cooled
single sector model gas turbine combustor. Flow, Tur-
bulence and Combustion, 102 (4), 1025{1052.
43.Hackney, R., Sadasivuni, S.K., Rogerson, J.W.,
and Bulat, G. (2016) Predictive Emissions Monitoring
System for Small Siemens Dry Low Emissions Combustors:
Validation and Application. ASME Turbo
Expo 2016: Turbomachinery Technical Conference
and Exposition.
44.Tavakoli, M.R.B., Vahidi, B., and Gawlik, W.
(2009) An educational guide to extract the parameters
of heavy duty gas turbines model in dynamic
studies based on operational data. IEEE Transactions
on power systems, 24 (3), 1366{1374.
Published
2020-03-17
How to Cite
BINTI OMAR, Madiah et al. Modelling of Dry-Low Emission Gas Turbine Fuel System using First Principle Data-Driven Method. Journal of Power Technologies, [S.l.], v. 100, n. 1, p. 1-13, mar. 2020. ISSN 2083-4195. Available at: <https://papers.itc.pw.edu.pl/index.php/JPT/article/view/1571>. Date accessed: 23 july 2021.
Section
Electrical Engineering

Keywords

dry-low emission, gas turbine, Rowen's model, first principle data-driven, fuel valve, first-order transfer function

Most read articles by the same author(s)

Obs.: This plugin requires at least one statistics/report plugin to be enabled. If your statistics plugins provide more than one metric then please also select a main metric on the admin's site settings page and/or on the journal manager's settings pages.