Browsing by Author "Newby, Michael A."

Now showing 1 - 6 of 6
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    Creep-life usage analysis and tracking for industrial gas turbines
    (AIAA, 2017-07-14) Saturday, Egbigenibo Genuine; Li, Yiguang; Newby, Michael A.
    Creep-life usage analysis and tracking of first-stage turbine rotor blades of an aeroderivative industrial gas-turbine engine are investigated in this study. An engine performance model is created, and blade thermal and stress models are developed for the calculation of the blade material temperatures and stresses at different sections of the blade. A creep-life model is developed based on the Larson–Miller parameter method by taking inputs from the thermal and stress models. An integrated creep-life estimation system is developed by bringing together the engine performance model, the blade thermal and stress models, the creep-life model, and a data acquisition and preprocessing model. Relative creep-life consumption analysis using new concepts developed in this research is introduced for the analysis of creep-life consumption of the gas-turbine engine operating for a period of time; these concepts include equivalent creep life and equivalent creep factor. The developed algorithms have been applied to the creep-life tracking of an aeroderivative gas-turbine engine using its field test data. The results show that it is able to provide a quick evaluation and tracking of engine creep-life consumption and provide very useful information for gas-turbine operators to support their operation optimization and creep-life consumption monitoring.
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    Non-linear model calibration for off-design performance prediction of gas turbines with experimental data
    (Cambridge University Press, 2017-09-18) Tsoutsanis, Elias; Li, Yi-Guang; Pilidis, Pericles; Newby, Michael A.
    One of the key challenges of the gas turbine community is to empower the condition based maintenance with simulation, diagnostic and prognostic tools which improve the reliability and availability of the engines. Within this context, the inverse adaptive modelling methods have generated much attention for their capability to tune engine models for matching experimental test data and/or simulation data. In this study, an integrated performance adaptation system for estimating the steady-state off-design performance of gas turbines is presented. In the system, a novel method for compressor map generation and a genetic algorithm-based method for engine off-design performance adaptation are introduced. The methods are integrated into PYTHIA gas turbine simulation software, developed at Cranfield University and tested with experimental data of an aero derivative gas turbine. The results demonstrate the promising capabilities of the proposed system for accurate prediction of the gas turbine performance. This is achieved by matching simultaneously a set of multiple off-design operating points. It is proven that the proposed methods and the system have the capability to progressively update and refine gas turbine performance models with improved accuracy, which is crucial for model-based gas path diagnostics and prognostics.
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    Operation optimisation study for CCGT power plant.
    (2018-11) Chen, Yuzhi; Li, Ivan Yiguang; Nalianda, Devaiah; Newby, Michael A.
    A major concern for the power generation industry is to obtain a maximum economic benefit without over-consuming the remaining life of the gas turbine hot section. This study explored a methodology to support decision making for operational optimisation of a combined cycle gas turbine (CCGT) power plant. There is no published algorithm for modelling a parallel dual pressure, once-through steam generator (OTSG), nor any proposed method for OTSG degradation diagnosis and how the degradation affects OTSG performance. What is more, few publications were found for optimisation existing power plant operation considering gas turbine creep life. This study presents a new thermodynamic algorithm to simulate the thermodynamic performance of parallel dual pressure OTSG. In this study, a novel gas path diagnostic method for an OTSG based on the Newton-Raphson method was developed to predict the OTSG degradation caused by fouling. A daily operation decision support platform for this existing power plant is proposed that models CCGT performance, creep life, emissions, economics, and provides a basis for decision-making based optimised results. The OTSG performance model is applied to an OTSG operating in a CCGT power plant at Manx Utilities on the Isle of Man, United Kingdom to demonstrate the effectiveness of the simulation method. A comparison between predicted OTSG performance and OTSG field data showed that the proposed model offers good prediction accuracy when simulating OTSG performance for both design and off-design points. The OTSG diagnostic system was applied to a model OTSG to test its effectiveness. The impact of measurement noise on the diagnostic accuracy was also analysed and discussed. A comparison between predicted and implanted degradation of a model OTSG demonstrated that the results were satisfactory, and the method is promising. Moreover, the diagnostic analysis of an OTSG based on real measurement has further proved that the proposed diagnostic method works well. This simulation will recommend to the plant operator optimal operation schedules taking into consideration thermo-economics and lifing, under conditions of variation of power demand, electricity price, ambient conditions and gas turbine engine health states. It will suggest the more severely degraded engine should run at a relatively lower power setting to decrease creep life consumption. The established power plant optimisation framework will assist power plant operators to decide the total power output and power split between generators based on an optimisation system that considers both immediate economic benefit and life considerations. It will help existing power plant to adjust daily operation to achieve better thermoeconomic and lifing benefits. The outcome of this research will be useful for industrial CCGT power generation.
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    Performance adaptation of gas turbines for power generation applications
    (Cranfield University, 2010-06-29) Tsoutsanis, Elias; Li, Yiguang; Pilidis, Pericles; Newby, Michael A.
    One of the greatest challenges that the world is facing is that of providing everyone access to safe and clean energy supplies. Since the liberalization of the electricity market in the UK during the 1990s many combined cycle gas turbine (CCGT) power plants have been developed as these plants are more energy efficient and friendlier to the environment. The core component in a combined cycle plant is the gas turbine. In this project the MEA’s Pulrose Power Station CCGT plant is under investigation. This plant cronsists of two aeroderivative LM2500+ gas turbines of General Electric for producing a total of 84MW power in a combined cycle configuration. Cont/d.
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    Performance simulation of a parallel dual-pressure once-through steam generator
    (Elsevier, 2019-02-08) Chen, Yu-Zhi; Li, Yi-Guang; Newby, Michael A.
    The increasing demand for electricity and concern about global warming mean that electric power generation is required to be more efficient, cleaner, and more cost-effective. Combined-cycle power plants have gradually replaced their simple-cycle counterparts to generate more useful power by adding a bottom cycle to recover more energy from prime mover exhaust gas. There are two types of devices used to produce steam—one is the conventional drum-type heat recovery steam generator, and the other is the once-through steam generator (OTSG). The performance simulation of the former is relatively mature but is more difficult for the later. In this research, a novel simulation method for the thermodynamic performance of a parallel dual-pressure OTSG under both design and off-design operating conditions has been developed. The method has been applied to an OTSG operating in a combined-cycle gas turbine power plant at Manx Utilities, Isle of Man in the UK to demonstrate the effectiveness of the method. Meanwhile, the OTSG performance variation caused by inlet gas energy variation and downstream steam turbine erosion are demonstrated. The simulation results of the OTSG show good agreement with field data. The proposed method may be useful for both researchers and engineers in relevant area.
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    Techno-economic evaluation and optimization of CCGT power plant: a multi-criteria decision support system
    (Elsevier, 2021-04-19) Chen, Yu-Zhi; Li, Yi-Guang; Tsoutsanis, Elias; Newby, Michael A.; Zhao, Xu-Dong
    A key objective of the power generation industry is to achieve maximum economic benefit without over-consuming the life of power plants and over-maintaining its assets. From a CCGT power plant operator’s perspective, the stand-alone performance analysis of the plant is not enough to support the decision-making process due to the plethora of possible scenarios characterized by variable ambient conditions, engine health (fouling, erosion), electricity prices, and power demand. This study proposes a novel methodology to support decision-making for a CCGT power plant’s operational optimization. The comprehensive techno-economic performance evaluation is conducted by multidisciplinary optimization and decision-making to enhance information integration for the combined cycle power plant operated by Manx Utilities in the Isle of Man, UK. The decision support system has the capability to recommend the optimal operation schedules to plant operators. It recommends that the more severely degraded engine should run at a relatively lower power setting to decrease creep life consumption. The established power plant optimization framework has the potential to assist power plant operators in deciding the total power output and power split between gas turbines based on optimization results that considers both immediate thermo-economic benefits and life consumption. Finally, the proposed system can facilitate similar power plants to adjust daily operations to achieve thermo-economic and lifing benefits