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Chemical Kinetic Models for Enhancing Gas Turbine Flexibility- Model Validation and Application

Felix Güthe, Martin Gassner, Stefano Bernero, Thiemo Meeuwissen, Torsten Wind GE Power

Baden, Switzerland

ABSTRACT In recent years, market trends towards higher power

generation flexibility are driving gas turbine requirements of operation at stable conditions and below environmental emission guarantees over a wide range of operating conditions, such as load, and for changing fuels. In order to achieve these targets, engine components and operation concept need to be optimized to minimise emissions (e.g. CO, NOx) and combustion instabilities, as well as to maximize component lifetime. Therefore the combination of field experience, experimental studies and theoretical modelling of flames with state of the art tools play a key role in enabling the development of such solutions.

For many applications the relative changes of reactivity due to changes in operation conditions are important thus in this report a few examples are shown, where chemical kinetics simulations are used to determine the reactivity and to predict engine behaviour. The predicted trends are validated by correlating them to validation data from high pressure test rigs and real gas turbine operational data. With this approach the full operational range from highest reactivity (flashback) to lowest reactivity (blow out or CO emission increase) are covered. The study is focused on the sequential combustor (SEV) of reheat engines and addresses both the safety margins with respect to highly reactive fuels and achievable load flexibility with respect to part load CO emissions.

The analysis shows that it is necessary to utilize updated kinetic mechanisms since older schemes have proved to be inaccurate. A version of the mechanism developed at NUI Galway in cooperation with Alstom and Texas A&M was used and the results are encouraging, since they are well in line with experimental test data and can be matched to GT conditions to determine, predict, and optimize their operational range.

This example demonstrates nicely how a development over several years starting from fundamental basic research over experimental validation finally delivers a product for power plants. This report therefore validates the kinetic model in combination with the approach to use modelling for guidance of the GT development and extending it fuel capabilities.

The GT24 / GT26 can not only be operated with H2 containing fuels, but also at very low part load conditions and with the integration of H2 from electrolysis (~power to gas ~PTG) the turndown capability can even be further improved. In this way the energy converted at low electricity prices can be stored and utilised at later times when it is advantageous to run the GT at lower loads increasing the overall flexibility. This development is well suited to integrate renewable energy at highly fluctuating availability and price to the energy provisioning by co-firing with conventional fuels.

INTRODUCTION

Market drivers

In today’s volatile utility markets, the challenges for the power generation business include not only highly efficient operation and strict emission compliance, but also an increasing demand for flexibility with respect to load and fuels. The integration of renewable energy is expected to even increase the demand for flexible power generation and storage, which requires balancing measures for load flexibility and energy storage. According to several recent studies on the German and European energy market, the fraction of negative residual electricity prices will rise from several 100 h per year to over 1000 h per year [1, 2, 3].

This gives rise to promising business opportunities for energy storage applications. For gas turbine (GT) power plants

Proceedings of ASME Turbo Expo 2016: Turbomachinery Technical Conference and Exposition GT2016

June 13 – 17, 2016, Seoul, South Korea

GT2016-57223

1 Copyright © 2016 by ASME

this could include power to gas applications [4, 5, 6], where excess power can be electrolysed to produce H2 that can be stored, transported and sold or consumed in GT at times when it is technically beneficial and economically rewarding [7, 8]. The economy of such applications depends on the value and the usage of the produced H2. Possible utilisations include the addition to the gas pipeline or usage for automotive mobility. Another application is to utilise the produced fuel in the gas turbine to reduce fuel costs.

Although this can also be achieved after methanisation, i.e. the use of H2 for reduction of CO2 to CH4, direct H2 usage allows higher efficiency of the overall process and additionally can be exploited to extend operational flexibility by enabling GTs to operate at conditions where they would normally not operate. It will be shown that the GT operation can be extended into the part load range at times when electricity prices are low and availability at low actual fuel consumption cost is rewarding.

Integrating PTG conversion into the scope of power plant operation can offer some interesting economic opportunities for highly flexible power plants. A prerequisite for this is a GT which is highly flexible with respect to load and fuel variations, which is capable to generate power from natural gas co-fired with H2 from electrolysis or even from gasification plants beyond what is currently considered possible [7, 8]. Apart such PTG applications, combusting fuels of varying composition is a relevant challenge for syngas applications (e.g. co-firing of refinery gases, or generated through gasification), and for power plants that are affected by major changes of the available gas (e.g. due to seasonal variation of suppliers through pipelines and/or LNG).

Technological challenges

The relevant parameters for gas turbine combustion include not only energetic and volumetric properties such as heating value and Wobbe index, but also its reactivity (i.e. ignition properties and flame speeds), which significantly affects flame stability and emissions. Since these characteristics are particularly sensitive to pressure, high pressure tests in engine conditions are usually considered a mandatory step in the development of new combustors or their upgrade. High pressure testing is yet complex and very costly, and is therefore to be kept at the strict minimum. In past years, this has motivated the development of accurate kinetic reaction models to capture the behaviour of a variety of fuel blends. The application of such models in the design phase has the potential to reduce development time and the need for extensive testing of new hardware or alternative operation concepts, and thus significant improve cost, quality and time-to-market.

Well suited for applications as outlined above are efficient and flexible modern GTs like reheat GT26 / GT24 with sequential combustion [9]. As described earlier (e.g. [10]), they consist of two consecutive combustors separated by a high pressure turbine that operate in different regimes. They are developed for low emissions and high flexibility and a load

change between the combustors allows stable operation over a wide range of fuels and load points. These GTs have been shown to cope with a variety of fuels and allow for emission-compliant operation at very low loads [9, 10, 11], and are selected here as an example for applying kinetic models in the design phase.

Kinetic models for GT combustion

As emphasised in this paper, proper engineering tools are required to optimise the operation concept for the power plant and enable flexible operation with reactive fuels, as well as running at minimum load while still being compliant with emissions regulations (minimum environmental load ~MEL). Since combustion thereby plays a major role, an approach to obtain a quick prediction tool based on simple 1D-chemical kinetic calculations is described here. The results demonstrate the validity of the whole approach, for which a validated chemical reaction mechanism is a mandatory prerequisite.

In order to demonstrate the importance of using an appropriate kinetic mechanism for the problem at hand, two different kinetic mechanisms are selected for comparison. The first is the widely used GRI3.0 model [12] which – despite its known deficiencies – still seems to serve as standard for many applied researchers in the engineering community. At the ASME Turbo Expo over the last 3 years, it has been cited at least 84 times (28/32/24 in 2015/2014/2013) and has been picked as best choice in over 80% of the cases. A screening of the papers has yet indicated that it is highly debatable if GRI is really the best choice in about half of these applications. Only 17 papers (of 84 ~20%) compare results to other mechanisms. Several mention the GRI shortcomings (i. e. [13, 14]). Some larger comparative studies on H2 and syngas chemistry have also been undertaken in different sources [15, 16] and validated against various experiments. A number of different more recent mechanisms have been shown to clearly outperform the GRI3.0.

Among these were the models of Curran’s group of National University of Galway (NUIG), which is chosen as a representative of the modern, more accurate chemistry. As explained in detail in the literature ([17] and references therein), such chemistry resolves the competition between the main chain branching reaction H + O2 O + OH and the propagation reaction, H + O2 (+M) M + HO2 + M, which become more important at high pressures. In the present paper, the kinetic model comparison therefore is reduced to only two models for clarity to allow the description of the engine validation approach.

The validation of the chemical models for the correct conditions is crucial when using the model predictions for GT operations. The model used here is based on the work done in former years incrementally increasing confidence by validation on all levels of maturity [18, 19, 17, 21] with the engine validation demonstrated here. The kinetic model is under continuous improvement at NUI Galway and is referred to as NUIG model. We have used a version of the AramcoMech1.3


(2013) [20], with minor modifications for improved numerical convergence (on the formulation of third body reactions). To give an impression of the importance of choosing the right model and of the improvements that has been made to the chemical kinetics in matching GT conditions some results are compared to the GRI3.0 model [12].

One advantage of the GRI is however that it offers a wide range of conditions and species at relatively low numerical complexity, which is still remarkable. For example, the direct modelling of NOx formation is excluded in this approach which focusses on reactivity and CO emissions. Updated kinetics should also focus on a test and eventual improvement of the nitrogen chemistry in connection to the improved hydrocarbon chemistry, which is out of scope of this paper.

Development steps

The development of new combustion features can be separated into several steps: 1. As first step of the fuel flexible GT plants development, the

combustion behaviour has to be predicted using proper chemical kinetics tools including kinetics at GT condition for natural gas and hydrogen fuels, since many older chemical mechanisms are not accurate enough. The chemical parameters of interest are calculated for GT conditions [18]

2. The next step includes the validation in the laboratory [19] and for wider conditions included in the chemical kinetics mechanism [17]. The mechanisms are developed in cooperation with the National University of Galway (NUIG) and Texas A & M University (TAMU) over the last decade to update the hydrocarbon chemistry for higher alkanes and to include H2 as fuel.

3. A further step in the development is the high pressure (HP) validation [21] on full scale test rigs, which is highlighted in this work.

4. As last step (4) the field engine validation and experience in commercial operation can lead to validated co-firing concepts for C2+. Based on the validation results, the confidence gained with the implemented tools and process can enable the extension of such concepts to include H2 fuels.

Objective

With the objective to demonstrate the utility and benefits of such an approach, this paper recapitulates the major validation (and field application) steps of a detailed kinetic reaction mechanism for natural gas blends including significant amounts of higher hydrocarbons (C2+) and hydrogen. The benefits of such an approach for the design of new products and upgrades targeting fuel and load flexibility is demonstrated at the example of the GT26 / GT24 gas turbine family. This work demonstrates the fuel flexibility with the goal to further increase the load flexibility utilising the fuel flexible combustor and the converted renewable energy (PTG-H2) at lowest cost to

operate independently over an even wider range of energy prices while remaining connected to the grid.

OPERATIONAL PRINCIPLES AND BOUNDARIES OF REHEAT COMBUSTORS

The combustor of reheat engines can be operated over a wide range of conditions, such as fuel composition and power output at very high efficiency. Limiting the operation of a gas turbine combustor are the lean blow-off limit (often indicated by increasing pulsations or CO emissions as a precursor and finally leading to flame blow out) and at the rich limit flashback events which risk to reduce the lifetime of combustor and burner hardware. In reheat engines, the two combustors are coupled [9] through the fact that the first combustor’s output (temperature and composition) is determining the sequential combustor’s input. Consequently both combustors have to be optimized and kept in the stable operation range, but through their coupling both follow the same trend (with fuel reactivity) allowing an elegant compensation and the fuel split between first and second fuel flow even offers additional freedom.

Figure 1: EV Flashback: Increased reactivity in the EV burner flow field causes the flame to move upstream

First (EV) combustor: Flashback and Lean Blow-Off

The first combustor is usually operated at lower temperature and uses an aerodynamic stabilization mechanism like a vortex stabilized premixed combustion (EnVironmental vortex - EV) and produce hot gas as inlet into the high pressure turbine (HPT) and sequential combustor (SEV). The reactivity of the EV is dominated by the turbulent flame speed (st) and parameters that influence that, like turbulence and laminar flame speed (sl). The latter is changing with fuel composition and with hot gas temperature Thg. Mixing quality and stability can also be influenced by the staging ratio of the two fuel stages within the EV burner. An increase of reactivity causes the flame to move upstream against the gas flow as schematically indicated in Figure 1.

For aerodynamically stabilized flames, when increasing reactivity an operation point can be reached where the flame jumps to a new location, as indicated by thermocouple readings, changes in pressure drop and sudden increase of NOx formation in the performed tests that have been reported earlier [21]. H2 contents of over >50%vol have been tested at base


load and part load conditions and largely increased Thg (+200K). Although signs of flame movements were observable at high Thg, no damage on burners was observed and the H2 content was limited by the fuel supply system rather than the burner performance.

Figure 2 Relative experimental EV-NOx values (NOx at TREF=1 for natural gas) for interpolated to fixed Thg = Tref . plotted vs. fuel content (C2+ & H2) and plotted vs. Wobbe index

The EV burner has proven to be robust against reactivity changes due to fuel composition variation. NOx emissions seem to scale with reactivity due to changes in flame position but no clear impact of changes in the Wobbe index can be identified (Figure 2). Plotted are data from series of reference fuel (natural gas) and additions of H2, N2, C2+ and C2+&H2, where C2+ is the sum of all higher hydrocarbons in the fuel composition and H2 is the hydrogen content. The NOx shown are not directly measured but interpolated from HP data series to correspond to the same Thg. NOx values are given relative to the reference of natural gas. The increase of NOx for higher H2

content has been described by several authors (i. e. [22]). For the EV this is best explained by moving the flame into the less well mixed region resulting in partly higher local temperatures near the flame region. The slight increase of post flame NOx formation time seems not significant or sufficient to explain the NOx increase. A possible chemical effect due to changes in the chemical formation mechanism with H2 (i. e. involving NNH intermediates) has been invoked, but has not been experimentally substantiated, nor seems likely for GT conditions. A possible explanation would need to either explain increased prompt formation, which at GT condition is assumed to be low, or explain increased post flame NOx, which is dominant in GTs, but only little dependent on H2 in the fuel. Further careful studies on the increased NOx formation with H2 fuels are therefore required to increase the understanding of H2-cofiring flames.

While the data plotted vs. Wobbe index seem to be uncorrelated, the plot vs. C2+&H2 reveals some correlation with higher NOx for fuels of higher reactivity, assuming a linear relationship to C2+&H2 and similar contribution of C2+ and H2 to reactivity. A more accurate description could eventually improve the match, but within the required accuracy and for the sake of simplicity a linear index is preferred for concentrations < 60% C2+&H2. The NOx increase can be compensated by reducing Thg, which is also required for the reduction of SEV inlet conditions. Note that also the lean blow out (LBO) limit shifts with fuel reactivity.

On the low reactivity end the burner limit is given by the flame moving away from the stabilizing vortex out of the burner into the combustor. This can be accompanied by eventual pulsations and CO increase before actual blow out. Both limits can be related to the turbulent flame speed st and are subject to ongoing studies for a wide range of conditions, fuels [23, 24 and references therein] and pressures.

The Wobbe index is useful to assess the impact of fuel changes on fuel pressure drop for given burners and fuel handling systems. The same quantity also impacts jet penetration when fuel is injected into the burner, but any impact on burner mixing and NOx emission of the EV-burner is secondary compared to the flame moving according to its reactivity.

The correlation to C2+&H2 is not perfect but shows a reasonable trend. Note also that the scaling of fuel composition with reactivity does not have to be linear, nor has the addition of different fuel components (C2, C3, or H2) to be of similar magnitude. Therefore the scaling of NOx with the combined index C2+&H2 is remarkably good and useful for adjustment of GTs.

SEV combustor: Flashback and CO emissions

The SEV (Sequential EnVironmental) is an auto-igniting combustor where fuel is injected into the hot exhaust gas of the high pressure turbine (see [9] for details). The combustion of the gas then consists of several (overlapping) phases and time scales, which are governed by different parameters: ignition,


heat release and CO burnout. The kinetics in the ignition phase are principally dependent on the temperature and composition of the reactants (i.e. THPT_out ( ~TSEV_in), fuel/air ratio, fuel composition and temperature). The ignition time tignition determines the flame position within the combustor. The heat release and CO oxidation time scales are mainly governed by the hot gas temperature (Thg) as well as fuel composition. The inlet temperature influences the auto-ignition delay time and therefore the residence time after ignition. This again is indirectly controlling the CO burnout.

Figure 3: SEV operation margin from [21]. SEV burner and schematic flame position on the left and temperature level on the right

The operational limits of the SEV are flashback on the high reactivity end and LBO, which is usually indicated by gradual rise in CO for the sequential combustor, rather than pulsations or instantaneous flame loss. The latter turns out to be a convenient feature of the reheat flame. The flashback has been discussed earlier [21] and has been investigated through the experiment illustrated in Figure 3. Depending on the flame reactivity the flame moves upstream towards the injector. When the inlet temperature is increased (Figure 3 upper left) also the thermocouple reading (Figure 3 middle left) increases proportional to the increase of heat input by the vitiated air, but also tign decreases so that the flame approaches the thermocouple and additional heat input increases the thermocouple reading indicating the vicinity of the flame tip. This is visible as kink in the TC reading. The Delta TC curve (Figure 3 lower left) shows schematically the difference between the expected temperature caused only by TSEVin increase and the measurement. Although no damages to the burner have been detected, this point was used as boundary to limit the operation of the burner and has been termed flashback.

The low reactivity limit of operation is determined by the completion of the CO oxidation within the gas turbine. In conditions where CO emissions are becoming relevant (i.e. low loads, with Thg significantly below design level), the oxidation rate is decidedly slowed down by the immediate reduction of temperature in the subsequent turbine. Further reaction downstream the combustor exit can be neglected (at low Thotgas) and only the CO oxidation within the combustor is relevant. This is different for hot conditions at high loads where the

equilibrium CO can be above the emissions target, but oxidation rates are high enough to allow further equilibration towards low CO value within the turbine. At engines with turbines this effect can indeed be verified. On HP-rigs, the CO values depend on the details of the sampling. The single burner high pressure rig described here ([21] and Figure 5- Figure 7) samples at high pressure and quenches the gas quickly yielding CO values near the equilibrium values at exit temperatures. Note that the low reactivity limit is not necessarily equal to the lean limit (as in the first combustor) but the auto ignition flame is rather sensitive on the Tinlet.

Based on time scales, a qualitative criterion (Equation 1) was formulated [25] for CO emissions. The criterion relates the combustor residence time (tres) to the chemical time scales of ignition (tign) and burnout (tburnout). Ignition is thereby mainly depending on the inlet temperature and burnout mainly depending on the hot gas temperature of the SEV combustor (~TLPT in):

) ... fuel,,() fuel,..,( __ hotgasburnoutCOINSEVignres TtTtt

Equation 1 In general, CO emissions can be low (near the equilibrium)

when the residence time is longer than the required overall reaction time to equilibrium, i.e. the time for the ignition and oxidation of CO. If measured within the combustor of a high pressure rig the equilibrium serves as good reference, while within a GT, (and for higher Thotgas) the CO values continue to decrease through the turbine.

MODELLING APPROACH

For sequential combustion both combustors have to be kept within the stability limits of each combustion system. What at first sight seems to be an additional constraint, but actually turns into an advantage, is the coupling of the first and the sequential stage. A change of fuel reactivity can be compensated with a change of fuel split between the two burners retaining the combustor stable at constant power.

In modelling these effects, it is assumed here that exact matching of flame shape and position is not required for an accurate prediction of trends with varying fuels and inlet conditions. The hypothesis is rather that scaling according to physical principal parameters seems useful to predict GT behaviour and emissions. Other than for NOx predictions, where mixing plays a major role, assuming premixed conditions appear sufficient for the LBO and CO predictions in the reactor calculations when coupled to experimental validation. Any a priori quantitative CO prediction would have to include more physical effects like mixing, leakages of cold streams or quenching effects on CO oxidation.

The relative reactivities of the two combustors can be calculated using chemical kinetics simulations like the laminar flame speed solver PREMIX or the perfectly stirred reactor (PSR) for the first (EV) combustor operating at lean premixed conditions and a plug flow reactor (PFR) for the reheat combustor (SEV). Solvers used are from either the Chemkin


Pro program package from Reaction Design/Ansys or corresponding open source software like Cantera. The examples shown here for the sequential combustor refer to PFR calculations only.

Premix combustor model

The reactivity in the first premix combustor (i. e. EV) can be described by the laminar flame speed sl calculated for example with the PREMIX code or the PSR extinction time tPSR_ext , which is defined [21] as the shortest residence time of a PSR that allows ignition to take place. In turbulent flow fields the extension to the turbulent flame speed st seems desirable. For natural gas mixtures st correlations (described in [23, 24]) are useful while they tend to be less accurately validated for predictions of H2 and C2+ containing fuels over varying Tinlet and Thg. Especially for the atmospheric testing and extrapolations to higher pressures this leaves some gaps to be filled by expensive full scale testing.

To understand the influence of different fuels or other parameters on the stability of the burners the chemical reactivity needs to be scaled in the turbulent field.

Sequential combustor model

For the sequential combustor one combustion limit is given by the highest reactivity or shortest allowable tign, which is referred to as flashback, while the lower end of reactivity LBO is indicated by insufficient CO burnout and the rise CO emissions. In the simulation within the PFR this is resembled by the combination of tign and tburnout as indicated in Equation 1.

According to the approach outlined above, the PFR is thereby defined as an adiabatic reactor with perfectly mixed conditions of the hot gas flow downstream, the high pressure turbine (HPT), the fuel gas and the cooling air. In the lower part of the Figure 4, the evolution of CO is shown for two cases that represent part load conditions. Compared to the reference case (blue), a second case (red) is defined with lower TSEV_in (thus longer tign) and higher Thg (thus shorter tburnout) to illustrate the different effects. The ignition time tign can be defined on the profile of temperature (e.g. 3/4 of T-rise) or species (e. g. CH, CH2, or CO) and the burnout time tburnout can be defined as CO passing a value of e.g. 1.5 times the equilibrium value. All definitions seem equivalent but should be used consistently for comparisons.

For a more quantitative assessment of the CO burnout, Equation 1 can be reformulated to provide a dimensionless quantity that characterises the time required for complete burnout vs. the time available in the combustor. This quantity is termed the reduced reaction time (RTR) (Equation 2) and defined by normalising the ignition and oxidation times to a scale representing the residence time:

res

burnoutCOign

t

ttRTR _

Equation 2

As a rough estimate, the residence time scale is assumed proportional to the ratio of hot gas volume flow at the combustor exit (including also cooling air) and the geometrical volume of the combustor. Theoretically, a value of RTR = 1 represents just sufficient time for complete burnout, and higher values indicate insufficient residence time and thus incomplete conversion of CO. Due to the simple representation of the SEV combustor (i.e. a closed, uncooled plug-flow reactor, perfectly mixed inlet conditions, usage of average quantities instead of detailed local conditions), this phenomenological approach does not attempt a direct prediction of CO emissions from reaction kinetics. Instead, it provides a non-dimensional indicator quantifying the relative influence of the governing phenomena, to which CO emissions can be correlated.

Figure 4 PFR model and CO-time profile of the SEV combustor and characteristic time scales.

VALIDATION WITH RIG DATA

Experimental validation of the kinetic predictions are done at engine hardware and full scale combustors at the DLR high pressure facilities in Köln and are in part described in [21]. The SEV-rig operates with a hot gas generator to match inlet conditions of the sequential combustor in the GT. Tests were done for a wide range of fuels, changing C2+, H2, N2 and fuel temperature as well as operating conditions.

Two types of tests are highlighted here: 1. For the flashback testing the test was started with a given

SEV-fuel at low TSEVinlet. As explained in Figure 3, TSEVinlet was then increased to force the flame to move upstream as observed on the thermocouple reading. From the continuous data recordings (~1 Hz) the corresponding condition were extracted and calculated (Figure 5).


2. For the LBO tests CO was carefully measured for each fuel at defined TSEVinlet and Thg allowing sufficient time for equilibrated emission measurements (Figure 6).

Flashback behaviour

The flash back test were conducted [21] for natural gas fuels with up to 45%vol H2 and 35%vol C2+ added. With this procedure ca. 20 cases were recorded were the flame was in the vicinity of the thermocouple indicating a similar flame position and varying TSEVin. The experimental cases thus yielded 20 conditions near flashback which should correspond to similar chemical reactivity. These experimental cases (for given fuel and TSEVin) were analysed using the PFR model including a given fraction of cooling air from lance and burner model using the two different kinetic mechanisms. The obtained values for tign all correspond to the same flame position.

They were sorted into bins and analysed for variance and mean. In Figure 5 they were plotted as histogram (note the log scale) for the distance that is derived from multiplication of tign with the mean burner velocity. Even for events were the flame has been detected to be near the burner thermocouple no burner damage has been found. All experiments were displayed in one graph using the simulation with two different version of chemical kinetics.

Figure 5: Ignition distance (~flame position) determined experimentally and modelled with two kinetic models displayed as histogram and probability distribution calculated from the flashback condition for different fuels (C2+, H2 and N2) and burner temperature (log spacing)

The position of the thermocouple is given as black square around 0.22m and very near the centre of the distribution of ignition events for the NUIG model (events shown in red bars- centre shown by the green arrow). The GRI3.0 results are shown as blue bars and are 2-3 times shorter. Also the accuracy to predict the ignition position for different fuels show relatively small scatter (10%) with the NUIG model while the

GRI data seem less consistent (25% scatter). The scatter is given by the standard deviation relative to the mean. A low scatter corresponds to accurate matching of reactivity changes due to either fuel or Tinlet variations according to the described approach. An ignition “length” near the actual Tc measurement indicates good quantitative agreement. For comparison a Gaussian distribution from mean and standard deviation is plotted as lines (blue –dashed for GRI and red continuous for NUIG) and actual events are indicated by symbols.

The comparison of the magnitude and the scatter of results indicates the importance of the accurate kinetic model for predictions of burner behaviour in GT operation. The GRI 3.0 seems not appropriate to lay out a combustor operation concept for varying fuels, while the NUIG gives satisfactory results without further tuning of parameters to reduce mismatch.

Figure 6: High pressure rig experimental CO values for

low load operation with varied fuel, TAT vs. Thg (lower graph) and vs TAT (upper graph)

CO emissions

The second criterion concerns the LBO which is indicated by increased CO emissions. Since the flame is not lost the GT can be operated close to a defined guarantee level at part load. Experimental CO-emissions (calibrated to 15% O2) for various fuels are plotted in Figure 6 vs Tinlet and Thotgas.


CO emissions at part load depend on TSEVin, fuel reactivity and on Thg. Natural gas is taken as reference (green line). Note that two different test runs yield almost identical results, which demonstrates the robustness of the rig. At reduced Thg (upper graph blue) the CO emissions increase for given TSEVin, thus reducing the CO emission compliant operation.

The lower graph shows the CO increase with decreasing Thg, which means decreased power output and fuel consumption. This can be mitigated in part by operating at higher TSEVin (red graph) or with more reactive fuel (yellow). The dilution with N2 is accompanied by a reduced mean mixing temperature (more cold fuel mixes with hot vitiated air) for the ignition process and leads to less reactive conditions and increased CO emissions. The largely reduced CO emission with 20% H2 fuel basically are promising for low load operation in compliance with environmental regulations.

While some trends are observable, an overall picture is yet difficult to extract from the graph. Only a selection of the available measurements has been chosen for the graph since some other data are referring to slightly different conditions and therefore should not be connected by one line. For example several C2+ points were not included.

A better understanding is obtained if all measurement points could be included into one larger validation dataset and compared against a single indicator for CO burnout. To achieve this, the reduced reaction time RTR (Equation 2) is calculated for measurement points at varied and fuel compositions and temperatures.

Figure 7: Experimental single burner HP rig CO

emission values (normalised to CO equilibrium at combustor exit) for low load operation with varied fuel (H2 and C2+ up to 45%), TAT and Thg vs. reduced reaction time (RTR) for the updated model (NUIG) and the GRI3.0 (insert) .

For complete burnout, the CO concentration is reaching the equilibrium value at the combustor exit regardless of the residence time or reaction rates. This is an important boundary case to refer the data to – at least for the high pressure rig. Since the equilibrium value is changing with Thotgas the data

would look more scattered if they were plotted as absolute values. In Figure 7 the CO values are normalised to that equilibrium value. Note that the CO emission values measured after the turbine in the real engine does not scale to the equilibrium value of the combustor exit but is determined by the quenching of CO oxidation within the turbine.

Figure 7 uses experimental rig data in connection with a model to determine the operation range of a real GT. The comparison of mechanisms highlight their relevance for the model accuracy and predictive power. This result can also be seen as a validation of the full modelling approach complementing the lab validation of the kinetic schemes and applying it to the full engine level.

For short RTR (and complete combustion) a value of 1 is expected but for some points actually lower values (by a factor 1-3) are measured. This depends on the specific probe and sample treatment since the CO concentration is still decreasing while cooling the extracted combusted gases within the sampling probe before it is quenched to a value that is finally detected. For hot temperature and high CO values this reduces the concentration further, while the effect is less important for low temperatures and higher CO values like the part load cases considered here, where the CO reaction is quenched before the combusted gases are sampled.

The CO values vs. RTR are plotted in Figure 7 for all part load operation points calculated with the NUIG model and the GRI3.0 model. Shown are data from three different test runs over all fuels (summarising H2, C2+, N2 and Tfuel variation) and temperature variation. The coherence of the data is not as good as for the flashback data but a clear correlation of CO emissions to RTR can be seen for the validated NUIG mechanisms while the GRI data are much more scattered. For high reactivity the CO values are near the equilibrium values as expected. In the logarithmic plot the CO-values seem to start increasing for RTR>1 while the GRI data scatters around half of that value. As indicted by the hand-drawn average line for low reactivity (high RTR) the CO values approach a fixed value where either all fuel is converted to CO or no reaction takes place at all, corresponding to low CO for very high tign.

This kind of plot enables to interpret all fuel variations with respect to a single indicator rather treating each fuel separately and therefore uses validation on a large data base. It validates the approach to use chemical kinetics simulations for full scale combustor behaviour and includes C2+, N2, but also H2, for which GT data are rare. It also highlights the importance to use the validated accurate model since this would not give useful correlations with the inaccurate model (i. e: the GRI 3.0).

The next step of validation of the approach is the application of the model to available operation data from a real GT, and thereby relate the findings from high pressure rig tests with H2 to engine validation.

ASSESSMENT WITH FLEET DATA

As a last validation step of the (kinetic and engine) models, its predictions are assessed with available adjustment and test


data from GT26 fleet engines. Compared to laboratory experiments (e.g. shock tubes) and combustor rig tests, engine data can be expected to show larger scatter due to a number of additional parameters whose influence cannot be accurately determined or controlled. GT26 / GT24 gas turbines are featured with annular combustion chambers that unite up to 24 individual burners in a mechanically sophisticated assembly [26]. Manufacturing and assembly tolerances, and resulting differences in cooling and leakage flows thereby cause marginal differences of the local flow conditions through the individual burners, which can affect the overall behaviour of the combustor. CO emissions are thereby particularly sensitive due to the strong influence of local conditions around the flame zone on the burnout. Apart from these direct influences, indirect effects are caused by the need for controlling the engines’ pulsation behaviour. As a specific measure, combustor staging, i.e. the creation of temperature inhomogeneities in the annular combustor to uncouple acoustic interactions to moderate pulsation levels, results in a few colder burners that produce over-proportionally more CO than compensated by the hotter-than-average combustion zones.

The following paragraphs illustrate the validation of the kinetic models for an individual engine and a representative subset of the GT26 fleet. The validation is thereby only feasible with respect to CO behaviour and subject to available fuel composition on-site. A flashback assessment as carried out in the rig tests is not shown since fleet engines have not been instrumented for this purpose. They are inherently kept safe by appropriate control measures that ensure sufficient margin.

Individual engine characteristics

In analogy to the rig test data presented in Figure 7, Figure 8 shows measured CO emissions of a representative GT26 engine with respect to the normalised reaction time in the SEV combustor (Equation 2). The latter has been determined from the operation data and an appropriate model of the engine to determine the boundary conditions for the PFR. The SEV inlet temperature (TSEVin) and the fuel composition (only C2+) are directly measured, whereas the air composition, air and fuel flow are derived from design models considering ambient conditions and various measured parameters across the engine.

The data depicted in Figure 8 has been collected at different occasions spread over a full maintenance interval of the engine, i.e. from initial new commissioning until its first overhaul after 28’000 equivalent operation hours (EOH). The specific site has thereby been subject to large variations of fuel composition. In particular, the content of higher hydrocarbons (C2+) is varying between 0% to more than 9%mol, which significantly affects the reactivity of the fuel. The resulting impact on the ignition kinetics causes the CO emissions of the engine to vary by one order of magnitude for identical operation points. As illustrated by the graph, the relatively simple model presented in this paper is able to capture such large variations with reasonable accuracy if an appropriate kinetic model is used. The application of the NUIG-mechanism

collapses the data from these very different operation points and fuel composition within an accuracy of RTR ±0.2, which is reasonably accurate to be applied with confidence for predicting the engine behaviour. For a reduced reaction time near 1, a typical part load emission target of 100 [mg/m3] seems achievable. The overall correlation is similar to the HP test data (Figure 7). As shown in comparison in the upper left frame of the figure, the less accurate GRI3.0 mechanism fails to provide a distinctive relationship in the data, and results in the formation of several clusters. At the part load emission target of 100 [mg/m3], RTR seems to lie a factor 2-3 lower and is scattered over a wide range depending on the fuel.

Figure 8: Measured CO emissions (relative) at GT stack vs. normalised reaction time (RTR) for a specific engine with large variation of fuel C2+ content (colours). Data points span 3.5 years (28’000 EOH) of operation.

Fleet characteristics

In order to illustrate the validity of the models in the context of a wider gas turbine fleet, the assessment of the previous paragraphs is completed through a comparison of the characteristics of a representative ensemble of similar engines. The units considered for this purpose form a fleet of a specific GT26 rating with identical turbomachinery components, yet allowing for minor differences in some details of the combustor parts and their manufacturing process. Paired with minor differences in the assembly and accordingly the cooling and leakage flows, this affects the engines’ emission and pulsation behaviour. An engine-specific adjustment of the combustor staging and operational parameters is therefore required, which takes also site-specific conditions (e.g. ambient conditions, fuel composition) and requirements (local emission regulations, commercial operation strategies) into account.

Figure 9 summarises the CO behaviour of the selected GT26 fleet engines with respect to the C2+ content of the available fuel. The lines on the graph indicate the expected evolution of an engine’s relative load at constant RTR for


changing fuel gas reactivity. As demonstrated in the previous chapters, the RTR can thereby be considered representative for CO emissions. When fuel C2+ content is high, emission compliant relative load can be significantly reduced since the reduction of firing temperature (and therefore oxidation kinetics) is compensated by a faster ignition phase of the more reactive fuel components.

Figure 9: Comparison of fleet data with expected characteristics derived from reaction kinetics. Coloured points indicate fleet engines at a specific fixed CO emission limit (~MEL), lines (black: NUIG, grey: GRI3.0) represent design data at a constant RTR of 1 (full lines) ± 0.1 (dotted lines).

The black line, calculated using the NUIG model-mechanism, sketches a physical limit of the minimum achievable load level for a given C2+ content and CO emission limit (i.e. at RTR=1). The grey line represents the same characteristic calculated with the GRI3.0-mechanisms, which would predict much lower loads to be compliant with the same CO emission limit values.

These predictions are compared to the final adjustment of the engines (i.e. the points) after new commissioning or a major overhaul with replacement/reconditioning of hot gas parts. These points are coloured with respect to the SEV inlet temperature (TSEVin), which illustrates the differences of the individual adjustment of the units. Adjusting to higher TSEVin would reduce RTR and allow lower loads (shift to the left). This has been applied to a number of engines at low C2+ which are running at a sensibly higher temperature (orange/red points) in

order to allow for emission-compliant operation at lower loads. An upper limit at high TSEVin is given for lifetime reasons considering higher metal temperatures, whereas the flashback risk at reduced reactivity is not increased for slightly higher TSEVin. However, not all points in the graph have been optimized to low part load behavior. For the non-negligible number of points that are situated in the suboptimal domain (i.e. on the upper right of the characteristic line), the colouring of the data suggests that these engines are commissioned to lower TSEVin (and thus higher CO). This indicates that due to various (site specific) reasons, less emphasis has been put to operate the engine at lowest CO emissions in the low part load domain1. Despite the scatter, the data indicate that this simple combustor model based on the accurate NUIG reaction kinetics captures the overall behaviour of the fleet engines quite well when appropriate kinetic schemes are used. The grey line represents the same characteristic calculated with the GRI3.0-mechanisms, which obviously fails to characterise the behaviour of the fleet. Following the reasoning from the HP-tests the same prediction can be used for H2 co-firing when replacing C2+ by a C2+&H2 ordinate.

As demonstrated in Figure 9 reheat engines can not only operate at high reactivities due to C2+; the addition of C2+ can also extend the operational range of the GT in compliance with emission regulations and effectively reduces the minimum environmental load (MEL). The comparison with the HP single burner full scale test can be used to transfer the H2 experience to GTs and allows estimating the operation for H2 containing fuels. It further allows predicting an extended operation range utilising H2 addition, especially for C2+ poor fuels and shows the feasibility of PTG applications.

Figure 10: Schematic reduction of MEL with increased reactivity fuel

The advantage of PTG –H2 for low load operation is briefly sketched in Figure 10. The MEL can be expressed as fuel saved while remaining on the grid and emission compliant. The low load operation makes particular use of produced H2 since such operation points are enabled, which could not be

1 Other engine adjustment parameters (e.g. fuel staging, secondary air

flows etc.) are known to further influence the emission and pulsation behavior, but are omitted here since a systematic assessment is difficult to integrate in the simple models as applied here.


achieved without the H2 addition. This is economically rewarding in periods of negative spark spread (i.e. when fluctuating energy prices become lower than the unit’s cost of electricity) and if the capability of stabilizing the grid (e.g. wide load range between low load parking and maximum load with capability of fast load changes in between) is awarded financially. Such conditions are increasingly observed in the power markets due to the increasing share of renewable energy production and its inherent fluctuations in production.

CONCLUSIONS

Due to operational and fuel flexibility requirements and the importance of GT combustion to enable achieving such targets, key to successful product development is the availability of validated development approaches including accurate kinetic and combustion models. The current paper demonstrates that recent work on this topic, starting with fundamental research and extending the kinetic mechanism for combustion at relevant GT conditions and varying fuel compositions, can be successfully applied and validated both with single burner HP tests and operation data from fleet engines. Modern kinetic mechanisms such as the NUIG model (ARAMCO1.3) can be used to predict GT combustion behaviour for a wide range of fuel reactivity including C2+ and H2 fuels. Demonstrating that a popular mechanism such as GRI3.0 fails in this attempt, the paper thereby highlights that better care has to be taken by selecting the appropriate mechanism for the problem at hand. Despite its upmost importance and outstanding achievements for the combustion modelling, the GRI 3.0 is not well suited for GT conditions and should be replaced by other kinetic schemes. One such model is based around the NUIG model, which is still being optimised. For example steps to include also the nitrogen chemistry [27, 28] are promising.

In a comprehensive development cycle, fundamental studies on kinetics and the physical combustion process and validation work has been followed by experimental full scale burner validation up to engine pressures. Further field engine validation for C2+ fuels (where different fuels were available but not freely selectable) has demonstrated the prediction capacity of the models. The missing gap in the validation could be sufficiently closed by full scale high pressure tests with varied H2 content. The fuel flexibility with respect to C2+ and H2 was demonstrated with respect of the reheat combustion system to be possible with minimal output power changes. With the systematic characterisation and the improved understanding of the physical combustion processes the fuel flexibility of other GT frames can be understood and extended. This will be useful for several applications of H2 co-combustion. The usage of H2

from electrolysis and PTG on power plants in co-firing with natural gas can be combined with part load extension obtaining a further advantage of the H2 which could not be achieved with less reactive fuels. With this application the H2 is not only stored energy but also used with a specific advantage when utilising it by keeping a plant running at very low loads when

electricity prices are low and availability must be retained. In this scenario combustion in the GT is still crucial to the power generation schemes of the next decades, even at reduced fossil fuel consumption and carbon foot print this technology will be required for stabilization of the grid to allow the integration of renewable energy and their optimised utilisation. A large portion of the required flexibility in the energy market will have to be realised by gas turbines, which is expected to remain key technology in the next decades since it allows to efficiently stabilise the grid when integrating more and more renewables into the energy mix. In order to ensure this, further development of highly efficient and flexible gas turbines is a must, and fuel flexible combustion technology is a key enabler.

NOMENCLATURE

GT gas turbine PTG Power to gas EV EnVironmental (burner / combustor) SEV Sequential EnVironmental (burner /

combustor) HPT/LPT high pressure turbine / low pressure turbine Thg Hot gas temperature THPT_out

(~TSEV_in), Turbine outlet Temperature (HPT: High Pressure Turbine / LPT: Low Pressure Turbine)

tign Ignition delay time scale tburnout CO- oxidation time scale tres Residence time scale RTR reduced reaction time sl Laminar flame speed st Turbulent flame speed LBO lean blow out PSR perfectly stirred reactor PFR Plug flow reactor tPSR ext PSR extinction time C2+ relative content of higher alkanes C2+&H2 relative content of higher alkanes and H2 MEL Minimum Environmental Load

REFERENCES

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