Desired Dynamic Equation for Primary Frequency Modulation Control of Gas Turbines

Gas turbines play core roles in clean energy supply and the construction of comprehensive energy systems.The control performance of primary frequency modulation of gas turbines has a great impact on the frequency control of the power grid.However,there are some control difficulties in the primary frequency modulation control of gas turbines,such as the coupling effect of the fuel control loop and speed control loop,slow tracking speed,and so on.To relieve the abovementioned difficulties,a control strategy based on the desired dynamic equation proportional integral(DDE-PI)is proposed in this paper.Based on the parameter stability region,a parameter tuning procedure is summarized.Simulation is carried out to address the ease of use and simplicity of the proposed tuning method.Finally,DDE-PI is applied to the primary frequency modulation system of an MS6001B heavy-duty gas turbine.The simulation results indicate that the gas turbine with the proposed strategy can obtain the best control performance with a strong ability to deal with system uncertainties.The proposed method shows good engineering application potential.

Development of Cast Superalloys for Gas Turbines in China

As in other countries,significant achievements in the research of cast superalloys for many years have also been obtained in China.These results are important contribu- tion to the development of aero and land-based gas tur- bine engines.

Preparation and property of seal coating for gas turbine compressor

Double-layer structure of seal coating which consisted of a Ni5Al bond coating and a Ni25 graphite top coating were prepared on steel substrate of gas turbine compressor cylinder block.Bond coating was prepared by atmospheric plasma spraying and top coating was prepared by flame spraying.The microstructure,mechanical properties and abradability of the coating were characterized by scanning elec-tron microscope(SEM),hardness tester,universal testing machine,thermal shock testing machine and abradability testing machine.The res-ults show that the overall spraying structure of the seal coating is uniform,the nickel metal phase is the skeleton supporting the entire coat-ing,and the coating is well bonded without separation.The seal coating has a bonding strength of not less than 7.7 MPa,excellent thermal stability,and thermal shock resistance cycle numbers at 500℃more than 50;the scratch length,deepest invasion depth and wear amount of the coating increase with rise of test temperature,with almost no coating adhesion,indicating that the seal coating has excellent abradability.

Performance assessment of simple and modified cycle turboshaft gas turbines

This paper focuses on investigations encompassing comparative assessment of gasturbine cycle options.More specifically,investigation was caried out of technical performanceof turboshaft engine cycles based on existing simple cycle(SC)and its projected modifiedcycles for civil helicopter application.Technically,thermal efficiency,specific fuel consump-tion,and power output are of paramount importance to the overall performance of gas urbineengines.In course of carrying out this research,turbomatch software established at CranfieldUniversity based on gas turbine theory was applied to conduct simulation of a simple cycle(baseline)two-spool helicopter turboshaft engine model with free power turbine.Similarly,some modified gas urbine cycle configurations incoporating unconventional components,such as engine cycle with low pressure compressor(LPC)zero-staged,recuperated enginecycle,and intercooled/recuperated(ICR)engine cycle,were also simulated.In doing so,designpoint(DP)and off-design point(OD)performances of the engine models were established.Thepercentage changes in performance parameters of the modified cycle engines over the simplecycle were evaluated and it was found that to a large extent,the modified engine cycles withunconventional components exhibit better performances in terms of thermal efficiency andspecific fuel consumption than the traditional simple cycle engine.This research made use ofpublic domain open source references.

A combined technique of Kalman filter, artificial neural network and fuzzy logic for gas turbines and signal fault isolation

The target of this paper is the performance-based diagnostics of a gas turbine for the automated early detection of components malfunctions. The paper proposes a new combination of multiple methodologies for the performance-based diagnostics of single and multiple failures on a two-spool engine. The aim of this technique is to combine the strength of each methodology and provide a high success rate for single and multiple failures with the presence of measurement malfunctions. A combination of KF(Kalman Filter), ANN(Artificial Neural Network) and FL(Fuzzy Logic) is used in this research in order to improve the success rate, to increase the flexibility and the number of failures detected and to combine the strength of multiple methods to have a more robust solution. The Kalman filter has in his strength the measurement noise treatment, the artificial neural network the simulation and prediction of reference and deteriorated performance profile and the fuzzy logic the categorization flexibility, which is used to quantify and classify the failures. In the area of GT(Gas Turbine) diagnostics, the multiple failures in combination with measurement issues and the utilization of multiple methods for a 2-spool industrial gas turbine engine has not been investigated extensively.This paper reports the key contribution of each component of the methodology and brief the results in the quantification and classification success rate. The methodology is tested for constant deterioration and increasing noise and for random deterioration. For the random deterioration and nominal noise of 0.4%, in particular, the quantification success rate is above 92.0%, while the classification success rate is above 95.1%. Moreover, the speed of the data processing(1.7 s/sample)proves the suitability of this methodology for online diagnostics.

Performance of small-scale aero-derivative industrial gas turbines derived from helicopter engines

This paper considers comparative assessment of simple and advanced cycle small-scale aero-derivative industrial gas turbines derived from helicopter engines.More particularly,investigation was made of technical performance of the small-scale aero-derivative engine cycles based on existing and projected cycles for applications in industrial power generation,combined heat and power concept,rotating equipment driving,and/or allied processes.The investigation was done by carrying out preliminary design and performance simulation of a simple cycle(baseline)two-spool small-scale aero-derivative turboshaft engine model,and some advanced counterpart aero-derivative configurations.The advanced configurations consist of recuperated and intercooled/recuperated engine cycles of same nominal power rating of 1.567 MW.The baseline model was derived from the conversion of an existing helicopter engine model.In doing so,design point and off-design point performances of the engine models were established.In comparing their performances,it was observed that to a large extent,the advanced engine cycles showed superior performance in terms of thermal efficiency,and specific fuel consumption.In numerical terms,thermal efficiencies of recuperated engine cycle,and intercooled/recuperated engine cycles,over the simple cycle at DP increased by 13.5%,and 14.5%respectively,whereas specific fuel consumption of these cycles over simple cycle at DP decreased by 12.5%,and 13%respectively.This research relied on open access public literature for data.

Dynamic simulation of gas turbines via feature similarity-based transfer learning

Since gas turbine plays a key role in electricity power generating,the requirements on the safety and reliability of this classical thermal system are becoming gradually strict.With a large amount of renewable energy being integrated into the power grid,the request of deep peak load regulation for satisfying the varying demand of users and maintaining the stability of the whole power grid leads to more unstable working conditions of gas turbines.The startup,shutdown,and load fluctuation are dominating the operating condition of gas turbines.Hence simulating and analyzing the dynamic behavior of the engines under such instable working conditions are important in improving their design,operation,and maintenance.However,conventional dynamic simulation methods based on the physic differential equations is unable to tackle the uncertainty and noise when faced with variant real-world operations.Although data-driven simulating methods,to some extent,can mitigate the problem,it is impossible to perform simulations with insufficient data.To tackle the issue,a novel transfer learning framework is proposed to transfer the knowledge from the physics equation domain to the real-world application domain to compensate for the lack of data.A strong dynamic operating data set with steep slope signals is created based on physics equations and then a feature similarity-based learning model with an encoder and a decoder is built and trained to achieve feature adaptive knowledge transferring.The simulation accuracy is significantly increased by 24.6%and the predicting error reduced by 63.6%compared with the baseline model.Moreover,compared with the other classical transfer learning modes,the method proposed has the best simulating performance on field testing data set.Furthermore,the effect study on the hyper parameters indicates that the method proposed is able to adaptively balance the weight of learning knowledge from the physical theory domain or from the real-world operation domain.

A data-driven approach for predicting long-term degradation of a fleet of micro gas turbines

Predictive health monitoring of micro gas turbines can significantly increase the availability and reduce the operating and maintenance costs.Methods for predictive health monitoring are typically developed for large-scale gas turbines and have often focused on single systems.In an effort to enable fleet-level health monitoring of micro gas turbines,this work presents a novel data-driven approach for predicting system degradation over time.The approach utilises operational data from real installations and is not dependent on data from a reference system.The problem was solved in two steps by:1)estimating the degradation from time-dependent variables and 2)forecasting into the future using only running hours.Linear regression technique is employed both for the estimation and forecasting of degradation.The method was evaluated on five different systems and it is shown that the result is consistent(r>0.8)with an existing method that computes corrected values based on data from a reference system,and the forecasting had a similar performance as the estimation model using only running hours as an input.

Fluid-Dynamics Analysis and Structural Optimization of a 300 kW MicroGas Turbine Recuperator

Computational Fluid Dynamics(CFD)is used here to reduce pressure loss and improve heat exchange efficiency in the recuperator associated with a gas turbine.First,numerical simulations of the high-temperature and lowtemperature channels are performed and,the calculated results are compared with experimental data(to verify the reliability of the numerical method).Second,the flow field structure of the low-temperature side channel is critically analyzed,leading to the conclusion that the flow velocity distribution in the low-temperature side channel is uneven,and its resistance is significantly higher than that in the high-temperature side.Therefore,five alternate structural schemes are proposed for the optimization of the low-temperature side.In particular,to reduce the flow velocity in the upper channel,the rib length of each channel at the inlet of the low-temperature side region is adjusted.The performances of the 5 schemes are compared,leading to the identification of the configuration able to guarantee a uniform flow rate and minimize the pressure drop.Finally,the heat transfer performance of the optimized recuperator structure is evaluated,and it is shown that the effectiveness of the recuperator is increased by 1.5%.

Elimination of cracks in stainless steel casings via 3D printed sand molds with an internal topology structure

The important supporting component in a gas turbine is the casing,which has the characteristics of large size,complex structure,and thin wall.In the context of existing 3DP sand casting processes,casting crack defects are prone to occur.This leads to an increase in the scrap rate of casings,causing significant resource wastage.Additionally,the presence of cracks poses a significant safety hazard after the casings are put into service.The generation of different types of crack defects in stainless steel casings is closely related to casting stress and the high-temperature concession of the sand mold.Therefore,the types and causes of cracks in stainless steel casing products,based on their structural characteristics,were systematically analyzed.Various sand molds with different internal topology designs were printed using the 3DP technology to investigate the impact of sand mold structures on high-temperature concession.The optimal sand mold structure was used to cast casings,and the crack suppression effect was verified by analyzing its eddy current testing results.The experimental results indicate that the skeleton structure has an excellent effect on suppressing cracks in the casing.This research holds important theoretical and engineering significance in improving the quality of casing castings and reducing production costs.

Gas Valorization in the Republic of Congo: Production of Electricity from National Gas Reserves

The environmental impact of greenhouse gases based on natural gas flaring influences the rate of gas recovery around the world. In the Republic of Congo, the natural gas reserve in 2019 is estimated at 90 billion cubic meters (BCM). In this study, from the Congolese gas reserve we used five gas turbines with a capacity of 150 MW each;these five turbines consume 1.69 billion cubic meters (BCM)/year for the power of 273.750 MW and consumption of 6.57 billion kilowatt-hours. The results of this study revealed that an investment capital of 192,305,137 euros was required with a net profit of 9,581,250 euros at an annual rate of return of 4.98% with an investment payback period of approximately 20 years. This will allow the Congolese government to accomplish its policy of valuing gas and developing the country;the electricity produced by the National Petroleum Company of Congo (SNPC) will be sold to the Electrical Energy of Congo (E2C) at 0.06 euro/kWh.

Preparation and characterization of LPPS NiCoCrAlYTa coatings for gas turbine engine

NiCoCrAlYTa coatings have been deposited onto an aircraft gas turbine engine blade using a LPPS unit equipped with a computerized robot. Optimal processing conditions, including spray parameters, the trajectory of the robot, and the synchronized movements between the torch and the blade, have been developed for superior coating properties. Transferred arc treatment, providing a preheating and a cleaning of the substrate surface, enhances the adherence of the coatings to the substrate. The resulting LPPS coatings show dense and uniform characteristics with ideal hardness, and good corrosion resistance to cycle oxidation.

Fault Identification and Health Monitoring of Gas Turbine Engines Using Hybrid Machine Learning-based Strategies

Ahealth monitoring scheme is developed in this work by using hybrid machine learning strategies to iden-tify the fault severity and assess the health status of the aircraft gas turbine engine that is subject to component degrada-tions that are caused by fouling and erosion.The proposed hybrid framework involves integrating both supervised recur-rent neural networks and unsupervised self-organizing maps methodologies,where the former is developed to extract ef-fective features that can be associated with the engine health condition and the latter is constructed for fault severity modeling and tracking of each considered degradation mode.Advantages of our proposed methodology are that it ac-complishes fault identification and health monitoring objectives by only discovering inherent health information that are available in the system I/O data at each operating point.The effectiveness of our approach is validated and justified with engine data under various degradation modes in compressors and turbines.

Evaluation of the Influence of Ambient Temperature on the Performance of the Trans-Amadi Gas Turbine Plant

This paper examines the effects of ambient temperature on the Trans-Amadi gas turbine power station Phase II. The investigation took thirteen (13) months (January 2012 to January 2013) during which plant data were monitored and operational Logsheets like turbine logsheets, plant—auxiliaries’ logsheets and generator logsheets were studied. The gas turbine (GT) that was under investigation was GT-2: MS5001 Nuovopignone with designed installed capacity of 25.0 Megawatts (MW). The result of the study shows that a 1℃ rise of the ambient temperature is responsible for the following: 0% - 0.12% decrease in the power output, 0% - 0.12% increase in the power differential, 0% - 1.17% decrease in the thermal efficiency, 0% - 27.18% increase in the heat rate and 0% - 3.57% increase in the specific fuel consumption. An ambient temperature of 30℃ is found to yield minimal fuel consumption.

NUMERICAL CALCULATIONS OF GASEOUS REACTING FLOWS IN A MODEL OF GAS TURBINE COMBUSTORS

This paper describes the numerical calculations of gaseous reaction flows in a model of gas turbine combustors. The profiles of hydrodynamic and thermodynamic patterns in a three-dimensional combustor model are obtained by solving the governing differential transport equations. The well-established numerical prediction algorithm SIMPLE, the modified k-ε turbulence model and k-ε-g turbulent diffusion flame model have been adopted in computations. The β function has been selected as probability density function. The effect of combustion process on flow patterns has been investigated. The calculated results have been verified by experiments. They are in remarkably good agreement.

Off-Design Performance of Gas Turbine Power Units with Alternative Load-Control Strategies

Gas turbine power units,as an effective way to cope with the severe challenge of renewable energy accommodation in power grids,arouse the interest of power enterprises in the deep peak-load regulation performance.Two common alternative load-control strategies including constant turbine inlet temperature(TIT)and constant turbine exhaust temperature(TET)regulations were taken into consideration.To comparatively investigate the part-load performance under these strategies,both mathematical and physical models were set up successively to serve as a validation and complementary to each other.For the mathematical model of compressor with inlet guide vane(IGV),combustor and turbine,stage-stacking method based on blade average geometric parameter,energy conservation and turbine stage model were adopted respectively.For the physical model,design and off-design analysis were carried out based on GT PRO and THERMOFLEX respectively.The simulation result of mathematical model validated the reliability of the physical model.Based on this,the influence of ambient temperature and different load-regulating strategies on the off-design performance of gas turbine power units was studied in THERMOFLEX.The results in the case of a PG 9351FA gas turbine show that the ambient temperature has a great impact on system performance,i.e.,every 5℃ increase in the ambient temperature produces a reduction of 3.7%in the relative full-load output and 1.1%in the relative efficiency respectively;when the gas turbine operates under constant TIT strategy,TET starts to rise till it reaches the maximum allowable value with the load rate decreasing,and IGV keeps at the minimum angle with both TIT and TET decreasing when the load rate is lower than 65%;when the gas turbine operates under constant TET strategy,TIT drops slightly at load rate of above 60%while both TIT and TET evidently decrease below 60%load rate operating along the constant corrected speed line at the minimum allowable IGV opening;gas turbine effi-ciency is greatly affected by load rate and the performance degradation is more obvious especially in lower load rate regions;constant TET strategy is superior in the operating efficiency to constant TIT strategy under part-load conditions.

Cloud Based Monitoring and Diagnosis of Gas Turbine Generator Based on Unsupervised Learning

The large number of gas turbines in large power companies is difficult to manage.A large amount of the data from the generating units is not mined and utilized for fault analysis.This study focuses on F-class(9F.05)gas turbine generators and uses unsupervised learning and cloud computing technologies to analyse the faults for the gas turbines.Remote monitoring of the operational status are conducted.The study proposes a cloud computing service architecture for large gas turbine objects,which uses unsupervised learning models to monitor the operational state of the gas turbine.Faults such as chamber seal failure,load abnormality and temperature anomalies in the gas turbine system can be identified by using the method,which has an accuracy of 60%–80%.

Research on Modeling and Control of a 100 kW Micro Bio-Gas Turbine

In order to know about the influences of disturbance on the operating performance, the present work developed the overall dynamic simulation model of the micro gas turbine and investigated the control system under the disturbances of environmental temperature and unit load. The response processes of main parameters have been obtained. It found that the compressor pressure ratio and the fuel flow rate increase in the case of natural gas being replaced by pine gas. When the system reaches a new steady state, the main parameters change to different values. The output power decreases with the declining of the air mass flow when the ambient temperature rises, the biomass gas mass flow rate increases under the regulation of the control system to maintain the output power and rotating speed in which the thermal efficiency reduces by 1.40%. The thermal efficiency enhances with the increase of output load. The control system can quickly and effectively act to maintain the key parameters at desired value.

Associated Gas Utilization Using Gas Turbine Engine, Performance Implication—Nigerian Case Study

Typically, crude oil production in Nigeria always accompanied by surface production of associated gas. With little associated gas recovery facilities in place, majority of associated gas is continuously flared with few portions re-injected into the reservoir for enhance oil recovery (EOR). In addition to environmental hazards, wasting substantial amount of produced associated gas is deemed detrimental to a country currently generating less than 54% of its electric power requirement. Onsite power generation as one of the many means of utilization of associated gas has been conceived. Conversely, the availability and performance of the gas turbine engine for onsite associated gas utilization requires evaluation owing to variations in associated natural gas composition globally and the dependency of associated gas production on reservoirs and oil production activities. This paper presents an analytical investigation of gas turbine engine inspired by GE LMS100 frame engine for onsite utilization of associated gas in Nigeria. Gas turbine performance results are presented and performance parameters are compared against typical commercial natural gas grade.