Gas Turbine Performance Research Articles

Simultaneous Fault Diagnostics for Three-Shaft Industrial Gas Turbine

The study focused on the development of -gas turbine full- and part-load operation diagnostics. The gas turbine performance model was developed using commercial software and validated using the engine manufacturer data. Upon the validation, fouling, erosion, and variable inlet guide vane drift were simulated to generate faulty data for the diagnostics development. Because the data from the model was noise-free, sensor noise was added to each of the diagnostic set parameters to reflect the actual scenario of the field operation. The data was normalized. In total, 13 single, and 61 double, classes, including 1 clean class, were prepared and used as input. The number of observations for single faults diagnostics were 1092, which was 84 for each class, and 20,496 for double faults diagnostics, which was 336 for each class. Twenty-eight machine learning techniques were investigated to select the one which outperformed the others, and further investigations were conducted with it. The diagnostics results show that the neural network group exhibited better diagnostic accuracy at both full- and part-load operations. The test results and its comparison with literature results demonstrated that the proposed method has a satisfactory and reliable accuracy in diagnosing the considered fault scenarios. The results are discussed, following the plots.

Comparative Study of a Simulated and Real Life Reliability of Turbine Gas Path Diagnostics

Enhancing the performance of gas turbine requires the bringing together and optimization of the disciplines and expertise required to acquire an operationally competitive gas turbine engine. This study comprises comparative research between simulated and actual reliability of the gas path of a turbine engine. An innovative idea was introduced to reduce the gap between diagnostics processes via simulation and actual maintenance condition of the engine. The possible sources of errors were investigated by generating real error distribution. This research study explores the comparative investigation conducted to evaluate the reliability of a turbine gas path through simulating varying scenarios and analyzing real-life performance data. The application of simulation tools is to enable the replication of operating conditions and accurately model the gas turbine components, providing insights into potential weaknesses and strength. Real-life performance data provides important information about actual system behavior, including the frequency and nature of failures. Comparative investigations allow for validation of simulation accuracy, refinement of models, and identification of discrepancies. The findings from these investigations contribute to the optimization of gas turbine reliability, leading to efficient, cost-effective power generation systems.

Recent Developments in the Aerodynamic Heat Transfer and Cooling Technology of Gas Turbines Endwalls

With an increased inlet gas temperature and the homogenization of the combustion chamber outlet temperature, the endwalls of gas turbines are exposed to extremely high heat loads. The complex flow structure of turbine endwalls makes it difficult to cool some regions of the endwalls, which can easily cause endwall ablation, reducing turbine aerodynamic performance and threatening the turbine’s safe operation. In order to improve the cooling and aerodynamic performance of gas turbines, the flow structure, heat transfer and film cooling characteristics of endwalls are analyzed in depth in this paper. This paper summarizes and analyzes the development of the aerodynamic heat transfer and film cooling of gas turbine endwalls in terms of geometric structures and flow boundary conditions and also presents new research directions. Based on the literature, the development and challenge of turbine endwall film cooling are also discussed.

Design and off-design performance analysis of supercritical carbon dioxide Brayton cycles for gas turbine waste heat recovery

The utilization of waste heat from marine gas turbines is an effective means of meeting future electric demands and achieving energy conservation and emission reduction. Meanwhile, the supercritical CO2 Brayton cycle, benefiting from its compact structure, is well-suited for power generation in limited spaces. Based on the reality that gas temperature and flow rate deviate from the design point with the variation of gas turbine operating conditions, this paper proposes a method for analyzing the off-design performance of supercritical CO2 cycles based on thermal source fluctuations rather than simply providing prescribed temperatures on the cycle side. This method allows for a clear understanding of the impact on the cycle when there are fluctuations in the thermal source. Firstly, the thermodynamic performance and economic viability of four types of supercritical CO2 cycles, namely simple regenerative, recompression, intercooling, and reheat, were optimized using a multi-objective genetic optimization algorithm. Subsequently, the off-design performance of these four cycles was investigated when the gas temperature and flow rate deviate from the design point. The results indicate that, compared to the decrease in gas temperature, the reduction in gas flow rate has a greater impact on the decline in cycle performance. Decreasing gas temperature enhances the exergy efficiency of all four cycles, while reducing gas flow rate initially increases and then decreases the exergy efficiency. The decrease in turbomachinery efficiency significantly contributes to the decline in cycle performance. When the gas flow rate exceeds 55% of the design value, it is recommended to adopt an intercooling cycle arrangement. Otherwise, a recompression cycle layout should be used.

Multidimensional analysis and performance prediction of heavy-duty gas turbine based on actual operational data

This study aims to analyze and predict the degradation, safety and operational performance of a heavy-duty gas turbine based on actual operational data after running for a long time. The dataset consists of 288,039 operational records from the Ban Shan Power Plant. The data is screened using Pearson correlation coefficients and 2-means clustering. Then, efficiency degradation of compressor and gas turbine is conducted by decoupling operation state from degradation. Next, Long short-term memory(LSTM) is employed to build data-driven T-model based on algorithm structure similarity. Meanwhile, the safety requirements containing the compressor surge and turbine inlet temperature boundary are determined, which are considered in operational performance analysis. Results show that abnormal operation data is identified during operational times 37, 38, 39, 40, 41, 42, and 248. After 254,341 minutes, the compressor efficiency degrades nearly 1%. The surge margin of a compressor is a binary function of the corrected air mass flow and inlet guide vane (IGV). The pressure ratio of the working margin moves downward by 0.11 for each 1° increase in IGV. What’s more, the T-model demonstrates high accuracy and can predict operational performance at high environmental temperatures, with the accuracy of turbine outlet temperature within 0.995. The unit is particularly sensitive to IGV, natural gas flow mass, compressor inlet temperature, and turbine outlet gauge pressure. When the relative humidity is 68%, the electrical power is the highest and overall efficiency is the best. Overall, this study's approach has significant potential for multidimensional analysis and performance prediction.

Synergistic Effect of Physical Faults and Variable Inlet Guide Vane Drift on Gas Turbine Engine

This study presents a comprehensive analysis of the impact of variable inlet guide vanes and physical faults on the performance of a three-shaft gas turbine engine operating at full load. By utilizing the input data provided by the engine manufacturer, the performance models for both the design point and off-design scenarios have been developed. To ensure the accuracy of our models, validation was conducted using the manufacturer’s data. Once the models were successfully validated, various degradation conditions, such as variable inlet guide vane drift, fouling, and erosion, were simulated. Three scenarios that cause gas turbine degradation have been considered and simulated: First, how would the variable inlet guide vane drift affect the gas turbine performance? Second, how would the combined effect of fouling and variable inlet guide vane drift cause the degradation of the engine performance? Third, how would the combined effect of erosion and variable inlet guide vane drift cause the degradation of the engine performance? The results revealed that up-VIGV drift, which is combined fouling and erosion, shows a small deviation because of offsetting the isentropic efficiency drop caused by fouling and erosion. It is clearly observed that fouling affects more upstream components, whereas erosion affects more downstream components. Furthermore, the deviation of performance and output parameters due to the combined faults has been discussed.

Improving Gas Turbine Efficiency through Ribbed Channel Designs: A CFD-Based Study

Abstract: In order to increase performance and efficiency, this research article investigates the usage of ribbed channels in gas turbines. It uses computational fluid dynamics (CFD) simulations to assess various rib shapes and attack angles and evaluate the thermal-hydraulic performance of ribs. According to the results, square-shaped ribs consistently perform better than alternative rib geometries in terms of efficiency, normalized skin friction coefficient ratio, and skin friction coefficient ratio. The work emphasizes how crucial metal temperature prediction is in gas turbine blades and vanes because of the complex interaction between fluid dynamics and flow. The results may be used to establish and optimize cooling plans for increased gas turbine performance and efficiency

Assessment of paper industry decarbonization potential via hydrogen in a multi-energy system scenario: A case study

Green hydrogen is currently regarded as a key catalyst for the decarbonization of energy-intensive industries. In this context, the pulp and paper industry stands out as one of the most demanding, given the simultaneous need for large amounts of heat and electricity usually satisfied via cogeneration systems. Given the urgent need for cost-effective solutions in response to the climate crisis, it is crucial to analyze the feasibility of retrofitting existing power plants to operate carbon-neutral. The aim of this work is to provide a techno-economic analysis for the conversion of a conventional cogeneration system to run on locally produced hydrogen. Building on the energy consumption of the paper mill, the operation of a hydrogen-fuelled gas turbine is modelled in detail. Based on these results, a multi-energy system model for the production of green fuel is presented, considering production via solar-powered PEM electrolyzers, storage in tanks and final use in the gas turbine. An optimal configuration for the system is defined, leading to the definition of a solution that ensures a cost of 6.41 /kg for the production of green hydrogen. Finally, a sensitivity analysis highlights the close dependence of the economic profitability of the Power-to-X system on the natural gas price. The results indicate that although positive performance is achieved, the cost of investment remains still prohibitive for systems of this size, and the high initial capital expenditure needs to be supported by incentive policies that facilitate the adoption of hydrogen in industrial applications making it competitive in the short term.

Application of Biogas from Quinoa, Wheat, and Andean Guinea Pig Residuals as Biofuels for Gas Turbines

This article shows the effect that biogases obtained from crop residuals from the Andean region have on the performance of a whole medium-sized electrical-generating gas turbine. This technology could be used to supply electricity in energy-depressed areas where biogas is the only accessible resource. The gas turbine worked with higher efficiencies when the obtained biogases were used compared to natural gas. The biofuel that presented the highest efficiencies was the one obtained from wheat residuals alone. Despite this fact, this biofuel would be the most prone to create aerodynamic problems in the stages of the gas turbine. In this work, it was found that the addition of guinea pig manure to different crop residuals created biofuels less prone to create aerodynamic problems in the compression and expansion stages. In particular, the studied biofuel that had the most similar aerodynamic behavior to the design natural gas case was the one obtained from guinea pig manure and quinoa residuals. On the other hand, this biogas presented the lowest efficiencies of the studied biofuels. Despite this fact, this biofuel showed higher efficiencies than the natural gas case. In the gas turbine combustion chamber, all the studied biofuels operated at lower temperatures than the ones with natural gas, even in the high-power range. This would be an important feature for the running of the combustion chamber and the high-pressure turbine superalloys.

Matrix cracking onset stress and strain as a function of temperature, and characterisation of damage modes in SiCf/SiC ceramic matrix composites via acoustic emission

The complex damage mechanisms that accumulate within SiC f /SiC ceramic matrix composites (CMCs) subject to thermal and mechanical stress are being investigated in anticipation of the material’s introduction into high performance gas turbine engines. Acoustic emission (AE) is recognised as a leading non-destructive evaluation (NDE) tool to this end, and was used in this study to determine the so-called matrix cracking onset stress under tensile load as a function of temperature up to a maximum of 1100°C. Onset stress was interpreted using three traditional measurements based on AE energy characteristics during monotonic tests to failure. Pattern recognition (PR) analysis was performed on the AE data, revealing a specific cluster of signals that correlated closely with the initial matrix cracking region of the stress-strain curve. Taken in isolation, the onset stress of this activity was significantly lower than the conventional value. PR results were investigated further, and isolated clusters were linked to damage modes anticipated at other specific regions of the stress history. A secondary series of experiments was performed on specimens representing the individual constituents of the CMC (single-phase SiC flexural bars, Hi-Nicalon™ fibre bundles and SiC f /SiC mini-composites) in attempts to further validate the corresponding AE signal characteristics. Matrix cracking and interphase debonding/sliding damage modes could be identified consistently, while fibre breaks remained difficult to isolate under the current experimental conditions.

Gas Turbine Off-Design Performance Adaption Based on Cluster Sampling

An accurate gas turbine performance model is important for system performance evaluation. To minimize the simulated performance error, an adaption method using coefficients of scaling factors is applied to tune the component characteristic maps and make the gas turbine model meet measurements of a few randomly sampled points. However, the field data are non-homogeneously distributed. In this situation, randomly selecting a few sampling may lead to the inappropriate correction of the component characteristic maps and lower the prediction accuracy of model. Firstly, the coefficients of scaling factors are introduced to construct the performance adaption optimization problem of the gas turbine model. Secondly, the k-means clustering algorithm is applied to divide the 146 field data points into 10 different categories, and then the points closest to the cluster centers are selected to form the sampling set. Thirdly, a particle swarm optimization algorithm is used to search the optimal scaling factors. As a result, the model error decreases from 2.947% to 0.610%. Finally, the proposed method is validated with the remaining field data of a real E-class gas turbine. The average predicted error is 0.466%. Compared with the performance results obtained by random sample, the model based on cluster sampling shows a better accuracy.

Co-pyrolysis of sewage sludge with lignocellulosic and algal biomass for sustainable liquid and gaseous fuel production: A life cycle assessment and techno-economic analysis

Biowastes are marked sources of global greenhouse gas emissions, however, locally accessible biowaste could be a sustainable source for biofuel production to generate clean energy. This study examined the environmental sustainability and economic feasibility of using co-pyrolysed sewage sludge (SS) with lignocellulosic and algal biomass for liquid and gaseous fuel production from the perspective of life cycle assessment and techno-economic analysis. Wastewater-grown microalgae, sawdust, and wheat straw were selected as co-feed materials, and three mixing ratios (25, 50, and 75 wt%) of each feedstock with SS were examined. Wastewater-grown microalgae and SS were obtained from wastewater treatment plants (WWTPs), which were assumed to be near the pyrolysis plant facility, obviating the need for transportation. An Aspen simulation was used to estimate the amount of energy recovered from the pyrolysis as gaseous fuel for electricity and heat generation via gas turbines. A sensitivity analysis was conducted to identify future considerations for SS co-pyrolysis to make it a more environmentally and economically viable industrial process for producing liquid and gaseous fuels. The co-pyrolysis of SS with biomass reduced the overall environmental burden, with sawdust co-pyrolysis outperforming wheat straw and microalgal co-pyrolysis. All scenarios achieved a high net positive energy balance (from 2,595 to 6,323 kWh/1,000 kg bio-oil) and reduced global warming potential (GWP) (from −793 to −1,970 kg CO2 eq/1,000 kg bio-oil). Sawdust co-pyrolysis resulted in the highest GWP reduction (from −1,510 to −1,970 kg CO2 eq/1,000 kg bio-oil) and energy recovery (from 5,551 to 6,323 kWh/1,000 kg bio-oil). Energy recovery from gaseous fuel through gas turbine operation generated a process energy demand of 23 %–224 %. Sawdust co-pyrolysis exhibited the highest net present worth (NPW) of 6.16 million CAD. Sensitivity analysis demonstrated that the GWP and terrestrial ecotoxicity potential were affected by the transportation of sawdust and wheat straw. Overall, the co-pyrolysis of SS with both lignocellulosic and algal biomass is sustainable and economically feasible for producing liquid and gaseous fuels and treating hazardous waste originating from WWTPs, thereby facilitating environmental sustainability and a circular economy from the sale of pyrolysis products. Broader implication of this study is using effective catalysts to further strengthen the sustainability and increase the profitability of the co-pyrolysis process, which has not been yet investigated.

Gas turbine operating as part of a thermal power plant with hydrogen storages

Over the past few years, much attention has been paid to hydrogen energy. The development of hydrogen technologies leads to a reduction in the cost of both the hydrogen fuel itself and hydrogen systems, which leads to a wider use of this type of fuel in various branches of the fuel and energy complex. At the moment, the primary task is to increase the efficiency of combined cycle power units, reduce wear and tear of equipment during peak electricity consumption, reliable backup of energy supply, and reduce harmful emissions during the generation of heat and electricity. One of the modern methods for implementing these challenges is the use of energy storage devices. A new solution to this problem can be the introduction of hydrogen storage in the cycle of a thermal power plant. The article considers the modernization of a combined-cycle power unit with a gas turbine PG6111FA manufactured by « General Electric» with a rated power of 80 MW, a waste heat steam boiler manufactured by JSC « EnergoMashinostroitelny Alliance», and a steam turbine KT-33/36–7.5/0.12. During periods of night unloading, the effective efficiency of the power unit drops, so it is necessary not to unload the equipment, but to turn on the electrolyzers for the production of hydrogen fuel for further use in hydrogen fuel cells. The operating time of the hydrogen system with an electrolyzer is not limited in time, the operation of the electrolyzer takes place during night unloading periods (from 4 to 7 h a day), while the hydrogen storage works constantly, in this mode of operation, the service life is about 15 years, for stable operation it is necessary hydrogen fuel and periodic maintenance. An important component of the hydrogen system is a hydrogen battery with minimal storage losses, in contrast to traditionally installed thermal storage. Studies of the use of hydrogen storage in the circuits of thermal power plants have shown their effectiveness, including their implementation allows you to increase the efficiency, reduce the cost of own needs of the power plant, reduce emissions in the production of electricity, a leveled load schedule allows you to increase the life of the gas turbine, as the turbine works in basic mode. The use of accumulators in thermal power plants increases the competitiveness among traditional energy generation systems.

Hierarchical control of hybrid energy storage system in shipboard gas turbine power system with multiple pulsed power loads

Transient power fluctuations may occur in shipboard DC microgrids when switching a pulsed power load (PPL). However, shipboard power systems (SPSs) are isolated power grids with relatively low inertia and capacity, making them unable to respond immediately to sudden changes in pulsed loads, thereby resulting in considerable disturbances and even instability of the system. To mitigate such disturbances effectively, it is recommended to introduce energy storage devices to SPSs. In order to better leverage the buffering characteristics of energy storage devices, this paper establishes a simulation model of the SPS, which includes a micro gas turbine generator, a hybrid energy storage system (HESS), multiple PPLs and an energy management system (EMS). The HESS comprises a battery and a flywheel. Furthermore, a hierarchical coordinated control strategy for HESS in shipboard DC microgrids under multiple pulsed load conditions is proposed, which includes both an upper-layer control and a lower-layer control. The upper layer makes logical judgments through voltage difference and selects the appropriate energy storage mode for power supply. The lower layer adopts a series fuzzy logic control. To validate the effectiveness of the proposed control strategy, two scenarios of transient power mutation and total power demand exceeding the rated power of the generator were simulated by connecting different PPLs to the DC bus at different times. The results indicate that the control strategy effectively realizes the coordinated operation of HESS and gas turbine, as well as power allocation between flywheel and battery within HESS. Moreover, it reduces the frequency of charging and discharging of battery, improves battery life, and prevents the generator from running beyond the rated power.

Innovative Framework for Robustness Analysis of Blade Multicavity Squealer Tip Aerothermal Performance

Gas turbines are subject to various geometric and operational uncertainties, which are often overlooked in conventional research. Therefore, conclusions derived from a deterministic approach may not accurately reflect the actual gas turbine operation. To address this issue, this paper presents an effective uncertainty quantification framework for evaluating the aerothermal performance robustness of the multicavity squealer tip. Moreover, a novel visualization method is developed to analyze the uncertainty flow and thermal fields. The findings suggest that conventional research tends to overestimate the aerodynamic performance of the multicavity squealer tip. The installation of ribs can exacerbate the chaotic tendency of the flowfield, leading to a significant reduction in the aerodynamic performance robustness of the squealer tip during actual operation. However, the heat transfer performance robustness of the multicavity squealer tip is substantially enhanced due to the inability of the flowfield uncertainty to transfer to the thermal field through the ribs. Furthermore, the study reveals high heat flux fluctuations in the region near the ribs root, which highlights the importance of considering thermal fatigue risks in the design of multicavity squealer tips.

Analysis of Gas Turbine Performance based on Variation of Operating Load at PLTGU Panaran 1 Unit 1 PT.Mitra Energi Batam

Gas and steam power generation units often experience changes in load according to the requested electricity needs. Changes in generator workload will also affect the efficiency of the generator. The different efficiency in each workload will have an effect on the amount of heat rate production produced when compared. By calculating the efficiency at each load, it will be useful to find out the workload with the best performance. From the results of the enthalpy calculation process based on the temperature of each gas turbine process, in this study the gas turbine performance is calculated, and then it compares the turbine performance with variations in operating load. The turbine performance that will be calculated includes compressor power, turbine power, net power, thermal efficiency, compressor efficiency, combustion chamber efficiency, turbine efficiency, heat input, and heat rate. The results of the calculation of the highest average thermal efficiency at 27 MW load were 35.18%; the average compressor efficiency experienced the highest increase at 25 MW load of 83.24%, followed by an average increase in combustion chamber efficiency and an average decrease in turbine efficiency at each increase in load, as well as experiencing the lowest decrease in heat rate at 27 MW load conditions of 2,842 kJ/kWh

Deep learning framework for gas turbine performance digital twin and degradation prognostics from airline operator perspective

Digital twin technology has emerged as a research hotspot in the field of intelligent operation and maintenance of gas turbines. This paper proposes a data-driven Digital Twin approach for gas turbine performance monitoring and degradation prognostics from an airline operator perspective. The framework adopts a semi-supervised deep learning method to construct a data-driven Performance Digital Twin (PDT) rather than a physics-based performance model. The PDT-derived multi-dimensional health features is used to characterize the performance degradation and enhance the input features for the prognostics network. Specifically, domain knowledge from the asset operator perspective is incorporated into the prognostics model to improve the performance. The proposed approach is evaluated on real-world turbofan engines and the NCMAPSS dataset, achieving promising results compared to the state-of-art approaches. The developed data-driven prognostics framework provides a low-cost alternative to an expensive physics-based prognostics approach for gas turbine operators. It enables asset users to implement their own data-driven prognostics and maintenance strategies.

Modelling and Simulation of Micro Gas Turbine Performance and Exhaust Gaseous

Numerical simulation of cold flow and explosion in a Capstone C30 micro gas turbine is simulated using OpenFOAM. This study is aimed to investigate the combustion of non-premixed methane/air inside a micro gas turbine. The combustion characteristic inside a micro gas turbine with 100% methane is assumed for the fuel is studied with a three-dimensional model of micro gas turbine. The velocity of the flow increases significantly in the explosion simulation where the combustion of non-premixed methane/air mixture is initialised. The temperature in the micro gas turbine increased to 2400K at the downstream of inlets and reduces to 1500K at the combustion zone. High concentration of CO and CO2 is in the main reaction zone. The fraction of water vapours and hydroxyl on the other hand is lower compared to other species.

About the automation of procedures to assess the operation parameters of by-pass turbojet engines (BTJE)

During aircraft operation, the assessment of operation parameters with the different use of nomograms is completed. This approach is prevalent in the operation of aviation gas-turbine engines as part of aircraft power plants. In this case, for example, the assessment of engine operation parameters on the ground, depending on environmental conditions prior to start-up and run-up, is required. Reducing working hours of the aircraft power plants maintenance can be provided by the automation of the denoted procedures which purpose is the formation of the applicable list of values for assessed parameters while assigning available environmental conditions considering the required restrictions. To allow for the visualization and familiar conceptions of carried out assessments, it is advisable not to be limited to only documenting quantitative parameter estimations but also to provide them with graphical representations. The purpose of the article is not aimed at describing a complete algorithm of the engine operation parameters assessment but demonstrating a solution capability for the automation of the procedures for the engine operation parameters assessment on the ground as the task of search for a solution in the restricted conditions using the approximation 30 apparatus and piecewise approximations by the method of the smallest squares and the correlation criterion of significance. The examples of quantitative estimations for one of mass domestic engines are given. The described approach is applicable to a broad list of engines due to the common character of algorithms for the parameter assessment using nomograms. Software based on the tabular calculation processor from the LibreOffice package, Apache-licensed free software, is cross-platform.

Investigation of Regenerative Gas Turbine Performance under the Influence of Dynamic Atmospheric Conditions in India Using Energy and Exergy Analysis

Investigation of Regenerative Gas Turbine Performance under the Influence of Dynamic Atmospheric Conditions in India Using Energy and Exergy Analysis