Gas Turbine Units Research Articles

Assessment of the Carbon Footprint of Production of Construction Materials Used in Hydrogen Energy

The results of the analysis of production of construction materials used for manufacturing hydrogen life cycle equipment are presented. The aspects of the life cycle of the main construction materials (steel, aluminum, nickel, copper, titanium, platinum, carbon plastics) used in hydrogen power engineering are identified. The results of the carbon footprint assessment for the production of these materials are presented depending on the production technologies, the energy source used and the secondary raw materials. It is established that in the development of a hydrogen gas turbine unit (GTU) the main contribution to carbon footprint is made by titanium (50,9 %) and nickel (37,6 %) alloys, in spite of the fact that more than 50 % of GTU consists of steel. It has been determined that in the production of solid-polymer fuel cells the main contribution to the carbon footprint is made by the smallest construction materials — platinum (78,1 %) and carbon plastics (15,7 %) due to the fact that they have the largest carbon footprint per kg of produced material.

Performance of sCO2 Cycles for Waste Heat Recovery and Techno-Economic Perspective as Gas Turbine Bottoming Cycle

Abstract Supercritical carbon dioxide (sCO2) cycles are compact, cost-effective and widely adaptable to various heat sources, including the waste heat from gas turbine (GT) exhaust gases. While the addition of a steam cycle enhances the typical 40% efficiency of GTs up to 60%, their substantial investments render them less appealing for smaller GTs. This creates an opportunity for sCO2 cycles, but a comprehensive comparison of their performance with that of steam across a range of applications remains lacking. Moreover, their applicability to various industrial scenarios based on existing installations is missing from a techno-economic standpoint. To address these needs, four promising sCO2 cycles are evaluated and optimized using Aspen, and compared with the simple steam cycle. Their techno-economic performances are then investigated for 20 industrial GTs of different size up to the larger combined cycle gas turbine (CCGT) units incorporating amine-based carbon capture systems. Due to the significant investments required by the carbon capture unit, the implementation of a CC unit is only investigated for the largest CCGT units. The analysis yielded performance maps demonstrating comparable performances for sCO2 and steam cycles, as well as significant techno-economic advantages for sCO2 bottoming cycles for smaller GTs. However, when it comes to larger GTs combined with reheats and expansions steam cycles, sCO2 cannot outperform them in current technological standards. Nevertheless sCO2 cycles offers an attractive alternative, facilitating cogeneration. Among the different approaches designed to integrate the heat requirements of amine-based capture, steam cycles have always proved more suitable because of the thermal stability of amines. In conclusion, the research underscores the cost-effectiveness and adaptability of sCO2 cycles for heat recovery applications, particularly as bottoming cycles for smaller GTs, while larger GTs present a challenge. The work conducted sheds light on the substantial promise of sCO2 cycles, encouraging further exploration and implementation of these systems in the energy sector.

Adaptive robust self‐scheduling for a wind‐based GenCo equipped with power‐to‐gas system and gas turbine to participate in electricity and natural gas markets

AbstractIntegrating renewable energy, particularly wind generation, into power systems brings significant uncertainty and intermittency, challenging generation companies (GenCos) to maintain economic operations. This paper proposes a strategy for a wind‐based GenCo equipped with a gas turbine and a power‐to‐gas (PtG) system to balance wind variability. The gas turbine offsets power shortfalls by consuming natural gas, while the PtG system absorbs excess wind energy, converting it to natural gas and injecting it into the natural gas network as a form of storage. The GenCo operates in day‐ahead electricity and natural gas markets and the real‐time electricity market, addressing uncertainties from wind output, energy prices, and natural gas access. A tri‐level adaptive robust optimization model is introduced for the GenCo’s short‐term operational scheduling. At the first level, decisions related to the GenCo's participation in the day‐ahead electricity and natural gas markets are made. The second level deals with determining the worst‐case realization of the uncertainties, constrained by the budget of uncertainty and the limited range of variations of uncertain variables. The third level sets the operational strategy on the actual day, considering power and gas balance, as well as constraints for the wind farm, gas turbine, and PtG unit. A column & constraint generation (C&CG) algorithm is used to solve the model. Numerical results demonstrate the model’s effectiveness in various case studies, showing that the GenCo can manage wind uncertainties, benefit from arbitrage opportunities in electricity and gas markets, and improve economic outcomes. This approach supports the broader integration of renewable energy into power systems.

Techno economic analysis and performance based ranking of 3–200 kW fuel flexible micro gas turbines running on 100% hydrogen, hydrogen fuel blends, and natural gas

Micro gas turbines ranging from 3 to 200 kW are vital for decentralized power generation due to their reliability, rapid load response, and adaptability to 100% hydrogen and hydrogen fuel blends. This paper conducts a techno-economic assessment of MGTs powered by hydrogen, focusing on their environmental, economic, and technical viability. Key factors include the transition from natural gas to hydrogen to achieve net-zero emissions and enhance grid stability. Despite hydrogen's higher initial costs, its declining production costs and cleaner combustion make it a promising alternative. The study utilizes five micro gas turbine models (3, 30, 65, 100, and 200 kW) to evaluate a techno-economic analysis using 100% hydrogen, a 30% hydrogen and 70% natural gas blend, and 100% natural gas as fuels. Technical results are supported by experimental data from the world's first 100% hydrogen-fired micro gas turbine unit in Stavanger, Norway. Standard cost estimations for capital, operation and maintenance, and fuel costs are provided. The study introduces a novel technique for cost estimation and assesses econometric indicators such as net present value, internal rate of return, return on investment, payback period, and cost-benefit analysis. It compares economic scenarios for 2024, 2030, and 2040, highlighting the impact of fuel price volatility and regulatory changes on micro gas turbine techno-economics. Micro gas turbines are ranked using the Technique for Order Preference by Similarity to Ideal Solution-Multi-Criteria Decision Making (TOPSIS-MCDM) method based on their techno-economic performance. The ranking of microturbines based on techno-economic analysis performance is a novel contribution of this paper. Finally, a sensitivity analysis on the five micro gas turbines is carried out by changing the hydrogen fuel price. This research provides a comprehensive framework for stakeholders to make informed investment decisions, ensuring a smooth transition to 100% hydrogen-based power generation. The findings support the adoption of hydrogen and natural gas blends as an interim solution towards achieving a hydrogen economy.

Robust resiliency-oriented planning of electricity-hydrogen island energy systems under contingency uncertainty

The capability of electricity-hydrogen island energy systems (EH-IESs) to accommodate contingency uncertainties due to common device failures and power interruptions during extreme events remains poorly developed. The present work addresses this issue by proposing a robust resiliency-oriented planning model for EH-IESs comprising alkaline electrolyzer units, proton exchange membrane fuel cells, and gas turbine units under contingency uncertainties. First, a detailed device model of the EH-IES is established with rated, derated, and shutdown states. Second, the uncertainty of device faults in the EH-IES is addressed in a two-stage adaptive robust planning framework, where capacity planning and system operation are optimized in the first and second stages, respectively. Finally, the proposed robust planning model is divided into a master problem and a sub-problem and is then solved using a nested column-and-constraint generation algorithm. The improved economy and resilience provided by the proposed approach are demonstrated via the results of numerical computations.

Sustainable Biomethanol and Biomethane Production via Anaerobic Digestion, Oxy-Fuel Gas Turbine and Amine Scrubbing CO2 Capture

Energy policies around the world are increasingly highlighting the importance of hydrogen in the evolving energy landscape. In this regard, the use of hydrogen to produce biomethanol not only plays an essential role in the chemical industry but also holds great promise as an alternative fuel for global shipping. This study evaluates a system for generating biomethanol and biomethane based on anaerobic digestion, biogas upgrading, methanol synthesis unit, and high-temperature electrolysis. Thermal integration is implemented to enhance efficiency by linking the oxy-fuel gas turbine unit. The integrated system performance is evaluated through thermodynamic modeling, and Aspen Plus V12.1 is employed for the analysis. Our findings show that the primary power consumers are the Solid Oxide Electrolysis Cell (SOEC) and Methanol Synthesis Unit (MSU), with the SOEC system consuming 824 kW of power and the MSU consuming 129.5 kW of power, corresponding to a production scale of 23.2 kg/h of hydrogen and 269.54 kg/h of biomethanol, respectively. The overall energy efficiency is calculated at 58.09%, considering a production output of 188 kg/h of biomethane and 269 kg/h of biomethanol. The amount of carbon dioxide emitted per biofuel production is equal to 0.017, and the proposed system can be considered a low-carbon emission system. Key findings include significant enhancements in biomethanol capacity and energy efficiency with higher temperatures in the methanol reactor.

Transfer condition assessment of gas turbines via double multi-task Gaussian process

Predictive maintenance and health management are crucial means to enhance the operational reliability and safety of gas turbines, with time series condition assessment being a pivotal step in this process. However, the complexity of gas turbine and the harsh operating conditions raise the high cost and significant difficulty in acquiring data via sensors, which pose challenges for the conventional data-driven time series modeling methods. These result in the scarcity of available historical data and the deteriorate of condition assessment accuracy. To this end, this paper proposes an end-to-end, probabilistic transfer learning approach based on multi-task Gaussian process (MTGP) for the condition assessment of gas turbines with limited sensor data. For achieving effective transfer condition assessment, the proposed method, named double MTGP (dMTGP), employs (i) a recurrent neural networks (RNN) projector to extract the explicit evolution patterns, (ii) adopts the MTGP module to transfer knowledge from the source domain to the target domain, and (iii) presents a recursive MTGP strategy to have shared knowledge transferred cross outputs. Finally, the superiority and robustness of the proposed method are comprehensively validated against state-of-the-art competitors on four practical gas turbine units.

Advanced exergoeconomic analysis and mathematical modelling of the natural gas fired gas turbine unit used for industrial cogeneration system

In this study, mathematical model of advanced exergoeconomic analysis (ADEXEC) basing on advanced specific exergy cost (ADSPECO) and advanced exergy-cost-energy-mass (EXCEM) (ADEXCEM) methods are applied to the industrial cogeneration system (COGEN) which consists of natural gas fired gas turbine unit (with combustion chamber (CC), turbine (GT) and air compressor (AC)), pipe line (PL), wall (WD) and ground (GD) tile dryers under the dead state conditions of 10 °C, 15 °C, 20 °C, 25 °C and 30 °C. According to ADSPECO analysis; although CC ($6.97/GJ) has the lowest unit fuel exergy cost among the components, it has the highest exergy destruction cost rate ($252,391/hour at 30 °C) due to its high exergy destruction value. Although more than 40 % of the exergy destruction cost rate in the COGEN system is detected in CC, WD (105.541 $/h at 30 °C) and GD (107.499 $/h at 30 °C) which together account for more than 67 % of COGEN's avoidable exergy destruction are understood to be the first components to focus on. The fact that the exergy destruction cost rates of all components except PL is higher than the exogenous part of the endogenous part at all dead state temperatures reveals the weakness of the relationship between the components.

Predictive modeling of combined cycle power plant performance using a digital twin-based neural ODE approach

This study presents a novel digital twin-based predictive modeling approach to enhance the operation, maintenance, and management of combined cycle power plants. The research aimed to accurately forecast the combined cycle power (CCP) output, a critical performance indicator, to support intelligent decision-making for plant operators and engineers. The proposed framework leverages a neural ordinary differential equation (NODE) model integrated within a digital twin architecture to capture the complex, nonlinear dynamics of combined cycle gas turbine unit (CCGU) system. The predictive model was trained and validated using multivariate time-series data collected from a CCGU, achieving high accuracy with an R2_score of 0.993, a mean absolute percentage error of 0.325 %, and a root mean squared error of 1.518. Importantly, the NODE model demonstrated superior forecasting capabilities compared to traditional machine learning techniques. The digital twin (DT) concept enables seamless real-time data integration, physics-based models, and advanced data analytics to facilitate comprehensive CCGU lifecycle management. This novel approach provides operators with reliable, real-time insights to optimize plant performance, reduce maintenance costs, and improve overall sustainability. The generalization of the NODE model to an independent CCGU unit validated its applicability across diverse power plant configurations, highlighting the originality and practical value of the research. The key contribution of this work is the development of a digital twin-based predictive modeling framework centered on the innovative use of neural ordinary differential equations to enhance the operation and maintenance of critical energy infrastructure. This research advances the state-of-the-art in intelligent asset management for the built environment.

500 kW closed cycle gas turbine unit with different working fluids

This article considers a 500 kW closed cycle gas turbine unit. In contrast to open or semi-closed cycles, a closed cycle implies a working fluid circulating continuously within a closed loop. In other words, a working fluid (any working fluid) with the required initial parameters depending on the properties of the selected working fluid is injected into a closed circuit consisting of a compressor, heat exchangers of various purposes and a turbine. A unit with recirculation of combustion products at high pressure can be created based on existing units with minor modifications. Instead of emission into the atmosphere, the exhaust gases enter the high-temperature heat exchanger, where it gives heat to the closed-cycle gas turbine unit. First of all, the application of such units is relevant at compressor stations in conjunction with the gas turbine drive of the blower. The study involved thermal calculation of a closed-cycle gas turbine unit with different working fluids: carbon dioxide, helium and argon. The main objective is to study the advantages and disadvantages of alternative working fluids with their subsequent comparison. Since the main chemical and physical properties of alternative working fluids differ from the classical ones, there is a possibility of obtaining higher parameters of the unit. According to the results of calculations it is established that the most promising working fluid is carbon dioxide, because this can be used at a wide range of temperatures and pressures. It should also be noted that the consumption of carbon dioxide is the lowest compared to other working fluids. The efficiency of such an installation is 28%, but there is a possibility of improvement if regeneration is added.

Thermodynamic and Economic Analyses of a Novel Cooling, Heating and Power Tri-Generation System with Carbon Capture

The combined cooling, heating, and power (CCHP) system has attracted increasing attention due to its potential outstanding performance in thermodynamics, economics, and the environment. However, the conventional CCHP systems are carbon-intensive. To solve this issue, a low-carbon-emission CCHP system (LC-CCHP) is firstly proposed in this work by integrating a sorption-enhanced steam methane reforming (SE-SMR) process. In the LC-CCHP system, CO2 is continuously captured by the calcium loop so that low-carbon energy can be generated. Then, the LC-CCHP system thermodynamic model, mainly consisting of a dual fluidized bed reactor which includes the SE-SMR reactor and a CaCO3 calcination reactor, a hydrogen gas turbine, a CO2 reheater, and a lithium bromide absorption chiller, is built. To prove that the LC-CCHP model is reliable, the system major sub-unit model predictions are compared against data from the literature in terms of thermodynamics and economics. Finally, the effects of reforming temperature (Tref), the steam-to-carbon mole ratio (S/C), the calcium-to-carbon mole ratio (RCC), the equivalent ratio for gas turbine (RAE), and the hydrogen separation ratio (Sfg) on total energy efficiency (ηten), total exergy efficiency (ηtex), and carbon capture capability (Rcm) are detected. It is found that the minimum exergy efficiency of 64.5% exists at the calciner unit, while the maximum exergy efficiency of 78.7% appears at the gas turbine unit. The maximum energy efficiency and coefficient of performance of the absorption chiller are 0.52 and 1.33, respectively. When Tref=600 °C, S/C=4.0, RCC=7.62, RAE=1.20, and Sfg=0.27, the ηten, ηtex, and Rcm of the system can be ~61%, ~68%, and ~96%, and the average specific cost of the system is 0.024 USD/kWh, which is advanced compared with the parallel CCHP systems.

Isothermal turbines − New challenges. Numerical and experimental investigations into isothermal expansion in turbine power plants

The efficiency of power plants with steam or gas turbines depends on the efficiencies of a thermodynamic cycle and devices implementing this cycle. In the case of high power outputs, we cannot expect a significant increase in the efficiency of individual devices. Therefore, what remains is to increase the efficiency of the implemented thermodynamic cycle − the complex Rankine cycle in the case of steam turbines or the extended Brayton cycle in gas turbine units. The efficiencies of these cycles depend on the hot reservoir temperatures, limited by the materials used. The solution seems to be the thermodynamic cycles with the highest efficiency within given temperature limits, the „generalized Carnot cycles”. About gas turbines, such a cycle is the Ericsson cycle. The most difficult element of this cycle is carrying out high-temperature expansion. So far, there is no literature data on a technical device implementing this process. In this article, we present a method for designing turbine nozzles for isothermal expansion and the results of experimental tests of the first isothermal turbine. In the case of gas microturbines with a regenerator, isothermal expansion can increase efficiency from 24% to 28% up to 36%. An increase in efficiency of several to a dozen percentage points is expected for Organic Rankine Cycle (ORC) turbines. Due to such significant increases in energy generation efficiency, an isothermal turbine may become a future solution for energy systems.

INTEGRATION OF HYBRID ENERGY PLANT OPERATION

Integrated use means the use of several energy sources, all at the same time or in some combination. At the same time, it is possible to use exclusively renewable sources, which significantly limits user capabilities. More common and justified from many points of view is the use of both renewable and traditional sources, autonomous (universal boilers, diesel generators, gas turbine units, etc.) or centralized (power grid) sources. A correct assessment of such a combined energy system also requires taking into account the main component of the system - the consumer, that is, taking into account the features of the local network and nearby consumers, which will have a direct or tangible indirect effect on the operating mode of the complex of renewable sources. To ensure adequate power quality, energy storage systems can be used, and the need for them depends on the discreteness of energy flows and the requirements for power quality. In foreign terminology, combined systems are often called hybrid, reflecting the diversity of both energy sources and methods of combining them (sometimes this name extends to arbitrary complexes). However, the term “hybrid power supply” usually refers to a combination of installations using renewable and traditional energy sources. The article presents a new hybrid energy system that provides private households with electricity, hot water supply, heating and hot air in the required temperature range for comfortable living. Together with a wind power generator and an electric water heater, a heat pump, electricity and heat accumulators are used, which allows: - reducing the cost of thermal energy by reducing material consumption and equipment costs, saving organic fuel; produce electricity and send the excess to the state power grid; reduce heat load and environmental pollution. The automation system allows you to control the hybrid installation without human intervention all year round.

Development of an Automated Control System for a Gas Turbine Unit

Development of an Automated Control System for a Gas Turbine Unit

Simulation Modeling of Subsynchronous Resonance of an Autonomous Power District with a Gas Turbine Unit

Simulation Modeling of Subsynchronous Resonance of an Autonomous Power District with a Gas Turbine Unit

The primary frequency modulation control strategy based on fuzzy active disturbance rejection control for gas turbines

Gas turbines play a core role in clean energy supply and construction of comprehensive energy system, and the control performance of primary frequency modulation (PFM) of gas turbine has a great impact on the frequency control of the power grid. However, there are some control difficulties in the PFM control of gas turbines, such as the coupling effect of fuel control loop and speed control loop, slow tracking speed and large variation of operating conditions. To relieve the above difficulties, a control strategy based on the fuzzy-modified active disturbance rejection control (F-MADRC) proposed in this paper. Based on the analyses of the parameter stability region for active disturbance rejection control (ADRC), fuzzy tuning rules of parameters for F-MADRC are designed. Finally, the proposed F-MADRC is applied to the PFM system of MS6001B heavy-duty gas turbine. The simulation results show that the gas turbine unit with the proposed method can obtain the best control performance of the PFM with strong ability to deal with system uncertainties. The proposed method shows good engineering application potential.

Performance Prediction of A Power Generation Gas Turbine Using An Optimized Artificial Neural Network Model

This paper presents the application of an Artificial Neural Network (ANN) based model for performance ‎prediction of a power generation gas turbine. The suggested model was optimized to provide a large ‎database for comparison between different ANN topologies. Then, based on the optimization results, the ‎Multi-Layer Perceptron (MLP) of two layers was constructed and utilized for this study as the best-‎optimized topology. Training of this model was done using historical operational data of a Rolls Royce ‎‎(RB21-24G) gas turbine unit. The outcome results from this model used for performance prediction show ‎good accuracy for different ambient conditions and variable power ratings. Then, a degradation study was ‎also introduced comparing measurements of the same gas turbine utilizing one year later, on-site ‎operational data, with the predicted values generated by the ANN model. The result shows consistency ‎between the measured data and the model results.‎

The throughput capacity of the main gas pipeline when transporting gas-hydrogen mixtures

To determine the effect of hydrogen concentration in the gas-hydrogen mixture on the throughput capacity of the main gas pipeline and the volume of energy transported by it. The range of molar concentrations of hydrogen in the gas-hydrogen mixture up to and including 20%, which does not require significant technical modernisation of the system, was investigated.Performing theoretical studies and applying mathematical modelling methods to establish the regularities of thermo hydrodynamic processes in a gas pipeline, gas turbine and centrifugal blowers while transporting gas-hydrogen mixtures.In the example of a gas turbine unit widely used in the gas transmission system of Ukraine, it was found out that the molar content of hydrogen, if it does not exceed 20%, has a negligible effect on its rated power and other energy parameters. Adding hydrogen to natural gas with the above molar content will lead to a slight decrease in the pipeline system's capacity (up to 5%) and a significant reduction in the volume of energy transportation (up to 18%).The next stage of the study is to determine the impact of gas-hydrogen mixture properties on the pipeline capacity, taking into account changes in seasonal factors and the degree of system load.A method and software have been developed to predict the pipeline capacity and energy transfer volume for the transportation of gas-hydrogen mixtures, taking into account the influence of seasonal factors, gas-dynamic characteristics of blowers, and combinations of gas-pumping units at compressor stations.Modern international standards are used to calculate gas-hydrogen mixtures' physicochemical and thermodynamic properties under standard and operating conditions. The originality of the approach lies in the fact that the compressor station and the linear section of the gas pipeline are considered as a SLE gas-dynamic system.

Исследование новой микрофакельной горелки с помощью программы Ansys Fluent

A study of a new micro-flame burner device (MFBD) for the combustion chamber of a gas turbine unit (GTU) using the Ansys Fluent program is presented. Research objective: determination of the optimal operating modes of the investigated burner, initial air parameters for maximum combustion efficiency, examination of the uniformity of the temperature field, and the concentration of nitrogen oxides in the combustion chamber of the gas turbine unit with the MFBD. The features of the design and operation of the micro-flame burner device are described, as well as the stages of modeling combustion processes in the Ansys Fluent software. The calculations conducted using various simulation parameters in this program allowed the evaluation of the efficiency of the new MFBD, determination of the temperature field distribution, and the nitrogen oxide content in the combustion products. The nitrogen oxide emissions in the combustion products during different modes of operation did not exceed 9 ppm. This data will be useful for further optimization and development of GTUs taking into account the requirements of efficiency and environmental safety. The presented study demonstrates the application of Ansys Fluent in the development of new technologies in the field of combustion and energy

Thermal analysis of an integrated solar combined cycle power plant and its application in southern Iraq

Recently, simple cycle play a significant role in electric power production in Iraq. However, those units suffer from low thermal efficiency and low power output. In the present work, theoretical study is carried out aiming to improve the performance of (AL-Amara station 125MW). The present work includes three parts: the first part focus on the effect of ambient temperature on the performance of simple cycle including mass flow rate, power output, thermal efficiency and other parameters. In the second parts, a modification to simple cycle is implanted to be a combined cycle. The third part is studied the benefit of using solar unit for producing more steam to be supplied to the heat recovery steam generator wishing to produce more power and low emissing. Regarding, to simple gas turbine unit, the obtained results show that the mass flow rate is decreased nearly (10.8%) when the ambient temperature increased from (15-50) ºC. However, this reduction in mass flow rate of air is led to significant reduction in power output and thermal efficiency nearly (22.6%,13.2%) respectively. In the second parts, applying combine mode show a significant increase in power output and thermal efficiency nearly (32.5% and 32.3%) respectively. while the specific fuel consumption is decrease nearly (32.19%). Finally, the third parts when solar units are used, the gathered results show an acceptable increase for the amount of steam produced via solar units (21.02kg/s). The overall performance of the integrated cycle shows that the power output and the thermal efficiency increased nearly (11.28%and10%).