Table of Contents

    Topic review

    Gas Turbine Power Generation Systems

    Subjects: Energy & Fuels
    View times: 168
    Submitted by: Omar Mohamed

    Abstract

    This paper reviews the modeling techniques and control strategies applied to gas turbine power generation plants. Recent modeling philosophies are discussed and the state-of-the-art feasible strategies for control are shown. Research conducted in the field of modeling, simulation, and control of gas turbine power plants has led to notable advancements in gas turbines’ operation and energy efficiency. Tracking recent achievements and trends that have been made is essential for further development and future research. A comprehensive survey is presented here that covers the outdated attempts toward the up-to-date techniques with emphasis on different issues and turbines’ characteristics. Critical review of the various published methodologies is very useful in showing the importance of this research area in practical and technical terms. The different modeling approaches are classified and each category is individually investigated by reviewing a considerable number of research articles. Then, the main features of each category or approach is reported. The modern multi-variable control strategies that have been published for gas turbines are also reviewed. Moreover, future trends are proposed as recommendations for planned research.

    1. Introduction

    Modeling and control of gas turbine (GT) power generation systems are very important and are interrelated disciplines to study and improve the GT performance and efficiency. Understanding GT dynamics before actual installation or existing GT units cannot be achieved without sufficiently accurate models. GTs have occupied a privileged position among other power generation technologies for many reasons, including: high reliability; higher efficiency, especially when integrated with combined cycle; flexible operation; and regular availability [1][2]. The advances in GT operation and efficiency have occurred either from progress in GT control system philosophies [3] or introducing new designs [4]. GTs can be found in applications including engines used in aircraft and gas turbines used in power generation plants [5][6]. Due to the differences in the practical objectives between aircraft gas turbines and power generation gas turbines, the review presented here is dedicated to gas turbine power generation plants (GTPGP) used in power systems, whether they are studied on their own open cycle or as a part integrated to steam cycle in combined cycle gas turbine (CCGT) power plants. Therefore, for organizational and directive research reasons, the models for aircraft gas turbines are not included in this survey. Throughout our reading of the published research in this research area, the survey papers were found to be too general, and more specific review is needed [7][8][9][10]. The reviews in [7][8] summarized the GT modeling up to 2008 and 2011, respectively, with rather short explanations, whereas the survey in [9] is a general survey of thermal power plant simulations. Recent reviews on gas turbines diagnostics have been published in [10][11], however, those surveys have reported the methods of GT diagnosis and do not focus on modeling-based control theory and dynamic performance studies. The survey in this paper rather focuses on the models-based control and dynamic performance studies for gas turbine generation units. There is an urgent demand to reorganize the most recent and state-of-the-art methods of developments in GTPGP modeling and control, classify them properly, and discuss how they are cognitively connected with what had been previously published. The contribution of this paper is then to provide a more updated and a comprehensive survey about dynamical modeling of GTPGP from control point of view and the feasible methods of control that can be integrated to the GT unit with compliance of operational restrictions. The survey is beneficial for reporting the state-of-the-art techniques and attempting to extract future trends in the field. The survey is organized as follows: The modeling part has been divided according to the modeling philosophy and compared against each other. Moreover, the study outlines the feasible control strategies of gas turbine generation systems and discusses the future opportunities in the field. The survey offered in this paper shall be confined to GTs used in power generation or GTPGP for two main reasons: firstly, to understand and justify the dramatic growth of GTs in electricity sector as a power system resource and its positive influences on the power grid performance, such as grid stability and continuity of service; and secondly, the survey will simplify the way to investigate more feasible and safe operation strategies for compliance of grid codes specified by the system authority in different countries, which is a very specialized requirement in power plant engineering.

    2. An Overview on Gas Turbines Power Plants and the Purposes of Their Dynamical Modeling

    Gas turbines are widely used for propulsion and power production applications [12][13][14]. Consequently, for all industrial applications of GTs, modeling procedures and control methodologies are widely reported in the literature. Proper operation strategies are the key objectives to be fulfilled by process simulation and control. The essential parts of a typical gas turbine are shown in Figure 1, which are a compressor, a combustor or combustion chamber, and the turbine. Figure 2 shows the entropy–temperature (T–S) diagram of a typical GT unit. The air that is necessary for firing is fed by the compressor (control volume 1–2). In the firing chamber, the fuel/air mixture is combusted (control volume 2–3). Ideally, the control volume 1–2 contains isentropic process whereas control volume 2–3 is an isobaric process. The burnt gases are expanded in the turbine as an isentropic process (control volume 3–4) which produces the required mechanical work which is sufficient to drive the rotor of the synchronous generator (SG). Finally, in (1–4), the heat is rejected with fixed pressure. Gas turbine usually exists as a part of combined cycle unit in which the gas exhausted from the gas turbine is harnessed by the heat recovery steam generator (HRSG) to supply a high energy steam to the steam turbine (ST). The electrical power is delivered by the synchronous generator.

    Figure 1. Main components of gas turbine unit.

     

     

    Figure 2. Temperature–Entropy (or T–S) diagram.

    There are many goals and objectives for the modeling of GT or CCGT, including:

    • Simulators for training purposes [15][16][17][18].
    • Conditions monitoring and fault diagnosis [11][19][20][21].
    • Upgrading the performance by control system analysis [3][22][23][24][25][26][27][28][29][30][31][32][33][34][35][36][37][38][39][40].
    • Stability Studies (large signal and small signal stabilities) [22][23][24][25][26].

    Apart from these modeling objectives, and to grasp the trends of the modeling literature of GTs, the modeling survey can be classified in a better and clearer manner as follows:

    • Physical models based on the physical laws and parameters identification by data sets.
    • Empirical models with predefined structure, which are based on operational data sets.
    • Simplified mathematical models which are mostly transfer functions derived from system physics and identified to fit the plant manufacturer responses.

    The next section reveals the significant differences between the models within each sorting.

    The entry is from 10.3390/en13092358

    References

    1. Rayaprolu, K. Boilers for Power and Process; CRC Press: Boca Raton, FL, USA, 2009.
    2. Mohamed, O.; Wang, J.; Khalil, A.; Limhabrash, M. The Application of System Identification Via Canonical Variate Algorithm to North Benghazi Gas Turbine Power Generation System. In Proceedings of the IEEE Jordan Conference on Applied Electrical Engineering and Computing, Amman, Jordan, 3–5 November 2015; pp. 1–6.
    3. Mohamed, O.; Wang, J.; Khalil, A.; Limhabrash, M. Predictive control strategy of a gas turbine for improvement of combined cycle power plant dynamic performance and efficiency. SpringerPlus 2016, 5, 980.
    4. Jansohn, P.; Griffin, T.; Mantzaras, I.; Marechal, F.; Clemens, F. Technologies for gas turbine power generation with CO2 mitigation. Energy Procedia 2011, 4, 1901–1908.
    5. Rashid, K.; Sheha, M.N.; Powell, K.M. Real-time optimization of a solar-natural gas hybrid power plant to enhance solar power utilization. In Proceedings of the 2018 Annual American Control Conference (ACC), Milwaukee, WI, USA, 27–29 June 2018; pp. 3002–3007.
    6. Roumeliotis, I.; Aretakis, N.; Alexiou, A. Industrial Gas Turbine Health and Performance Assessment with Field Data. ASME J. Eng. Gas Turbines Power 2017, 139, 051202.
    7. Yee, S.K.; Milanovic, J.V.; Hughes, F.M. Overview and Comparative Analysis of Gas Turbine Models for System Stability Studies. IEEE Trans. Power Syst. 2008, 23, 108–118.
    8. Asgari, H.; Chen, X.; Sainudiin, R. Considerations in modelling and control of gas turbines—A review. In Proceedings of the 2nd International Conference on Control, Instrumentation and Automation (ICCIA), Shiraz, Iran, 27–29 December 2011; pp. 84–89.
    9. Alobaid, F.; Mertens, N.; Starkloff, R.; Lanz, T.; Heinze, C.; Epple, B. Progress in dynamic simulation of thermal power plants. Prog. Energy Combust. Sci. 2017, 59, 79–162.
    10. Fentaye, A.D.; Baheta, A.T.; Gilani, S.I.; Kyprianidis, K.G. A Review on Gas Turbine Gas-Path Diagnostics: State-of-the-Art Methods, Challenges and Opportunities. Aerospace 2019, 6, 83.
    11. Hanachi, H.; Mechefske, C.; Liu, J.; Banerjee, A.; Chen, Y. Performance-based gas turbine health monitoring diagnostics and prognostics: A survey. IEEE Trans. Reliab. 2018, 67, 1340–1363.
    12. Kehlhofer, R. Combined Cycle Steam & Gas Turbine Power Plants; PenWell: Tulsa, OK, USA, 1997.
    13. Kulikov, G.G.; Thompson, H.A. Dynamic Modelling of Gas Turbines: Identification, Simulation, Condition Monitoring and Optimal Control; Springer: London, UK, 2004.
    14. Sonntag, R.E.; Borgnakke, C. Fundamentals of Thermodynamics; John Wiley & Sons: Hoboken, NJ, USA, 1998.
    15. Power System Dynamic Performance Committee. Dynamic Models of Turbine-Governors in Power System Studies; Tech. Rep. PES-TR1; IEEE Power & Energy Society: Piscataway, NJ, USA, 2013.
    16. Lu, S. Dynamic modelling and simulation of power plant systems. Proc. Inst. Mech. Eng. Part A J. Power Energy 1999, 213, 7–22.
    17. Kola, V.; Bose, A.; Anderson, P.M. Power plant models for operator training simulators. IEEE Trans. Power Syst. 1989, 4, 559–565.
    18. Villasana, E.J.R.; Alegría, Y.M.; Arena, J.J.Z.; Cardoso, M.J.; Cruz, R.C. Development of a Gas Turbine Full Scope Simulator for Operator’s Training. In Proceedings of the Second UKSIM European Symposium on Computer Modeling and Simulation, Liverpool, UK, 8–10 September 2008; pp. 376–381.
    19. Wang, W.; Xu, Z.; Tang, R.; Li, S.; Wu, W. Fault Detection and Diagnosis for Gas Turbines Based on a Kernelized Information Entropy Model. Sci. World J. 2014, 14, 1–13.
    20. Booth, C.; McDonald, J.R.; Donald, P.; Lines, N.; Cooke, N.; Smith, C. Model-Based Condition Monitoring of Gas Turbines for Power Generation Duty. IEEE Power Eng. Rev. 2001, 21, 62–63.
    21. Zeng, D.; Zhou, D.; Tan, C.; Jiang, B. Research on Model-Based Fault Diagnosis for a Gas Turbine Based on Transient Performance. Appl. Sci. 2018, 8, 148.
    22. Mohamed, O.; Za’ter, M.E. Comparative Study between Three Modeling Approaches for a Gas Turbine Power Generation System. Arab. J. Sci. Eng. 2020, 45, 1803–1820.
    23. Hung, W. Digital Simulation of a Gas Turbine Generating Unit. Ph.D. Thesis, Loughborough University, Loughborough, UK, 1983.
    24. Jordan, F.D.; Hum, M.R.; Carras, A.N. An Analog Computer Simulation of a Closed Brayton Cycle System; ASME Paper; 69-GT-50; ASME: New York, NY, USA, 1969; pp. 1–15.
    25. Schobeiri, M.T.; Attia, M.; Lippke, C. GETRAN: A generic modularly structured computer code for simulation of dynamic behavior of aero- and power generation gas turbine engines. ASME J. Eng. Gas Turbines Power 1994, 116, 483–494.
    26. Hussain, A.; Seifi, H. Dynamic modeling of a single shaft gas turbine. In Proceedings of the IFAC Symposium on Control of Power Plants and Power Systems, Munich, Germany, 9–11 March 1992; pp. 43–48.
    27. Chaibakhsh, A.; Amirkhani, S. A simulation model for transient behaviour of heavy-duty gas turbines. Appl. Therm. Eng. 2018, 132, 115–127.
    28. El Hefni, B.; Bouskela, D.; Lebreton, G. Dynamic modeling of a combined cycle power plant with ThermoSysPro. In Proceedings of the 8th Modelica Conference, Dresden, Germany, 20–22 March 2011; pp. 265–375.
    29. El Hefni, B.; Bouskela, D. Gas Turbine Modeling. In Modeling and Simulation of Thermal Power Plants with ThermoSysPro; Springer: Cham, Switzerland, 2019; pp. 297–309.
    30. Casella, F.; Pretolani, F. Fast Start-up of A Combined Cycle Power Plant: A Simulation Study with Modelica. In Proceedings of the 5th International Modelica Conference, Vienna, Austria, 4–6 September 2006; pp. 3–10.
    31. Reddy, V.V.; Selvam, K.; De Prosperis, R. Gas turbine shutdown thermal analysis and results compared with experimental data. In Proceedings of the ASME Turbo Expo 2016: Turbomachinery Technical Conference and Exposition, Seoul, Korea, 13–17 June 2016. GT2016-56601.
    32. Kim, J.H.; Song, T.W.; Kim, T.S.; Ro, S.T. Model development and simulation of transient behavior of heavy duty gas turbines. ASME J. Eng. Gas Turbines Power 2001, 123, 589–594.
    33. Shin, J.Y.; Jeon, Y.J.; Maeng, D.J.; Kim, J.S.; Ro, S.T. Analysis of the dynamic characteristics of a combined-cycle power plant. Energy 2002, 27, 1085–1098.
    34. Oyedepo, S.O.; Kilanko, O. Thermodynamic Analysis of a Gas Turbine Power Plant Modelled with an Evaporative Cooler. Int. J. Thermodyn. 2014, 17, 14–20.
    35. Kim, T.S.; Lee, D.K.; Ro, S.T. Dynamic behavior analysis of a heat recovery steam generator during start-up. Int. J. Energy Res. John Wiley Sons 2000, 24, 137–149.
    36. Mohammadian, P.K.; Saidi, M.H. Simulation of startup operation of an industrial twin-shaft gas turbine based on geometry and control logic. Energy 2019, 183, 1295–1313.
    37. Yee, S.K.; Milanović, J.V.; Hughes, F.M. Validated models for gas turbines based on thermodynamic relationships. IEEE Trans. Power Syst. 2011, 26, 270–281.
    38. Rashid, K.; Mohammadi, K.; Powell, K. Dynamic simulation and techno-economic analysis of a concentrated solar power (CSP) plant hybridized with both thermal energy storage and natural gas. J. Clean. Prod. 2020, 248, 119193.
    39. Kaviri, A.K.; Jaafar, M.N.M. Thermodynamic modeling and exergy optimization of a gas turbine power plant. In Proceedings of the IEEE 3rd International Conference on Communication Software and Networks (ICCSN), Xi’an, China, 27–29 May 2011; pp. 366–370.
    40. Gülen, S.C.; Kihyung, K. Gas Turbine Combined Cycle Dynamic Simulation: A Physics Based Simple Approach. ASME J. Eng. Gas Turbines Power 2013, 136, 011601.
    More
    1. Please check and comment entries here.