=Paper=
{{Paper
|id=Vol-1853/p08
|storemode=property
|title=Steam generator performance by means of over fire
air and reburning techniques
|pdfUrl=https://ceur-ws.org/Vol-1853/p08.pdf
|volume=Vol-1853
|authors=Pietro Monforte
|dblpUrl=https://dblp.org/rec/conf/system/Monforte17
}}
==Steam generator performance by means of over fire
air and reburning techniques==
Steam generator performance by means of over fire
air and reburning techniques
Pietro Monforte
Department of Biological, Geological and Environmental Science
University of Catania Catania, Italy
monforte.ptr@gmail.com
Abstract—In the present paper. a mathematical model of a II. N OMENCLATURE
combustion steam generator is presented. The model of power
plant was implemented using GE GateCycle code. The effects m1 Air flow rate main burners;
of Over Fire Air and Reburning combustion techniques on the
plant performance were studied using from both theoretical and m1s Stoichiometries air flow rate main burners;
experimental approach. Experimental data were studied and mRS Stoichiometries air flow rate main burners;
represented depending on the combustion parameters. Moreover. mOF A Air flow rate OFA;
a numerical model of the steam generator and of the power plant m1f uel Fuel flow rate main burners;
was developed in order to predict the global plant performance. mRBf uel Fuel flow rate main burners;
Simulation results of showed a good accuracy between experi-
mental and theoretical data particularly in terms of reduction of mf uel Total fuel flow rate;
thermal specific fuel consumption. i Global excess air;
Q Overall heat transferred to the water;
Index Terms—Over Fire Air, Reburning, Steam generators,
Power Plants. Overall Efficiency. At Total heat exchange area;
Krad Combined radiative and convective heat
transfer coefficient;
I. I NTRODUCTION s Stefan-Boltzman Constant;
h Convective film coefficient;
I N order to reduce NOx emissions by fuel oil fed steam
generators in power plants a strong combustion control
through combustion modification process is needed. Among all
TG,ef f
TW,ef f
Effective gas temperature;
Effective wall temperature;
the possible technologies Over Fire Air (OFA) and Reburning TG , W Arithmetic average of hot and cold
(RB) have proved to be an effective way on NOx emission temperatures;
reducing method. According to these methods part of the εGS Emissivity of gas suspension;
fuel and combustion air are added separately into the post εCOAL Emissivity of coal particles;
flame region instead of the main combustion zone. Thus. a εOIL Emissivity of oil droplets;
three stages combustion process is realized [1]–[3]. In RB εSOOT Emissivity of soot;
zone a part of Flue Gas Recirculation (FGR) is injected with εG Emissivity of gas includig CO2 and H2 O;
reburning fuel (thermal power ratio in the range 5 to 20 ) εW Emissivity of the wall;
to form a stage (second stage) characterised by rich mixture CS Fraction of the cold surface area couled by
[4]–[6]. water tubes;
In the RB zone downstream the combustion zone. post Gwgh Gas temperature weighting factor;
combustion air is added to complete the main combustion. The W wgh Wall temperature weighting factor;
main difference between staged combustion (OFA) [7]–[9] and TG,Exit Furnace exit temperature;
Reburning is related to the different local stoichiometries that Tadb Adiabatic flame temperature;
is possible to achieve in the furnace with the two techniques TW,in Wall (water/steam) inlet temperature;
[10]–[12]. According to this method. most of the fuel is burned TW,out Wall (water/steam) outlet temperature;
with a stoichiometric fuel to air ratio. in the main burner Acorr Area correction factor;
zone. favours differently from OFA. the presence of uniformly GGRBF Recycle Gas injected from bottom of the
dispersed O2 entering the reburn zone [13]–[15]. The presence furnace;
of oxygen aids the decomposition of HCN to NCO. that is one GGRRB Recycle Gas injected with Reburning
of the principal and limiting steps on its way to N2 [16]–[18]. fuel;
As drawbacks of the technique are the same of the staged SH Super-Heated (radiative);
combustion: the risk of corrosion in the reburning zone, due SH-HT Super-Heated high temperature (convective);
to the reducing conditions. becomes real if the fuel has high SH-LT Super-Heated low temperature (convective);
sulphur content [19], [20]. RH Reheated;
ECO Economizer;
Copyright c 2017 held by the authors.
42
IV. M ATHEMATICAL M ODELLING
In order to study the effects of OFA and RB methods
III. R EBURNING M ETHOD on steam generators efficiency. a mathematical model of the
The studied boiler is fed with fuel oil and/or natural gas, studied power plant was implemented within GE GateCycle
tangentially fired (according to Fig. 1) equipped with 20 environment. GE GateCycle is a computer program based
burners located in 5 levels [21]–[23]. on mass and energy balances that performs detailed steady
state and off design analyses of thermal power station. As
it is possible to see in Fig. 3. the mathematical model of
power plant in the original configuration was tested using
experimental data obtained during on design performance tests
[30]–[34].
Fig. 1. Burner elevation setup.
The original configuration of the boiler was modified re- Fig. 3. OFA ports setup.
ducing the 5 burner levels to 4. Moreover. in the original
fifth one burners were replaced by 4 fuel injectors [24]–[26]. Combustion air for the steam generator equipment is split
OFA injection nozzles were installed in the upper part of the into both primary and secondary combustion air respectively.
furnace located in the front and on the lateral surface of boiler Two main configurations were analysed according to the
following the disposition showed in Fig. 2. same level of power plant (320 MWe ). The main operating
parameters are the total fuel input, fuel mixture specification,
reburning zone stoichiometry and excess air specification. The
combustion chamber is divided into three regions in which
RS1, RS2, RS3 (according to the definition RS3 includes
RS2 and RS2 includes RS1 parameter) represent different
parameters defined as in Eq. 1, 2 and 3.
m1
RS1 = (1)
m1S
m1
RS2 = (2)
m1S + mRS
m1 + mOF A
RS3 = =i (3)
m1S + mRS
Fig. 2. OFA ports setup. Gibbs free energy minimisation of the constituents was
used to calculate the exhaust gas composition. Radiation of
In order to provide the best configuration between the gaseous combustion product such as H2 O and CO2 is taken
minimal interventions on the pressure parts and the respect into account automatically using from Eq. 4 to Eq. 8.
of the chemical and physical limitations such as temperature
4 4
profiles. the disposition of the reburning injectors and post- Q = Acorr At Krad (TG.ef f − TW.ef f ) (4)
combustion air nozzles were selected accurately. FGR flow
rate used to control the RH temperature. is injected from 1 Cs h
the bottom of the boiler. This fact has a great importance Krad = 1 1 + 4 (5)
Cs εW + εGS − 1 4σTW,ef f
to further NOx emissions reduction [27]–[29]. In order to
perform the injection of reburning fuel, the technique requires TG,ef f = Gwgh TG,exit + (1 − Gwgh )Tamb (6)
more recirculated gas flow rate than OFA. Thus. recirculation
fans were replaced with more powerful ones because of the
different running conditions. TW,ef f = Wwgh TW,exit + (1 − Wwgh )Tamb (7)
43
Efficiency of the steam generator and net cycle heat rate of
plant have been calculated. Diagrams in Fig. 7 and 8 show
εGS = 1 − (1 − εG )(1 − εsoot )(1 − εoil )(1 − εcoal ) (8) these results as a function of fuel mixture.
The analogy with Hottel model is evident. Thus. taking into
account it. the evaluation of global emissivity of the exhaust
gas was calculated with Eq. 9.
εG = εCO2 + εH2 O − δε (9)
Fig. 4, 5, 6 show the calculated fraction of heat absorbed
by different sections of the boiler in function of combustion
configuration according to several fuel mixtures.
Fig. 7. Calculated Steam Generator Efficiency.
Fig. 4. Heat absorption in different boiler sections as a function of combustion
configurations.
Fig. 8. Net Cycle Heat Rate as function of fuel mixtures and combustion
configurations.
V. E XPERIMENTAL A NALYSIS
One of the important aspects of a global evaluation of the
Reburning technology is the analysis of the impact of this
process on thermal performance [35]–[37].
For the complete characterisation of OFA and RB configu-
rations more than 100 tests were carried out for a detailed
Fig. 5. Heat absorption in different boiler sections as a function of combustion
configurations.
evaluation of chemical and thermal boiler performance. In
order to study the impact of the RB technique on thermal
performance and pollutant emissions from the steam generator,
OFA and OFA + RB tests were carried out using different oil
and natural gas fuels mixture. In particular, 100%, 50%, 36%,
and 25% fuel oil thermal power ratio were used during the
tests.
Tests were conducted controlling the stoichiometry of the
staged combustion in the three zones. In order to compare the
two technologies, OFA and OFA + RB and study the effects
on the boiler performances SH and RH water spray and boiler
load were monitored. The exhaust gas was conditioned and
analysed for CO, NOx , O2 and carbon particulate concentra-
tion. Test conditions are reported in the table reported from
Fig. 9 to 13.
Fig. 6. Heat absorption in different boiler sections as a function of combustion The pollutant emissions from the steam generator are re-
configurations. ported in Fig. 14, 15, 16 and 17 in OFA configuration and
44
Fig. 9.
Fig. 10.
Fig. 14. NOx ISO-Concentration maps in OFA configuration and 100% fuel
oil.
Fig. 11.
Fig. 12.
Fig. 13.
100% fuel oil as well as 50% natural gas, respectively. While Fig. 15. CO ISO-Concentration maps in OFA configuration and 100% fuel
in Fig. 18 and 19 emissions from the steam generator in oil.
Reburning configuration and 100% fuel oil are reported.
theoretical and experimental results it is possible to conclude
VI. C ONCLUSIONS that:
In the present paper, the effects of OFA and RB combustion 1) Using OFA technique it is possible to maintain the con-
techniques on emissions composition and on the overall effi- trol capacity of NOx and CO concentration in exhausts
ciency of a steam generator were investigated. On the basis of when steam generator is fed with of fuel oil and natural
45
Fig. 16. NOx ISO-Concentration maps in OFA configuration and 50% natural
gas. Fig. 18. NOx ISO-Concentration maps in Reburning configuration and 100%
fuel oil.
Fig. 17. CO ISO-Concentration maps in OFA configuration and 50% natural
gas.
Fig. 19. CO ISO-Concentration maps in Reburning configuration and 100%
fuel oil.
gas combination
2) If the fuel is exclusively oil (case total fuel oil), the use 4) Numerical model developed for steam generator and
of RB technique becomes mandatory power plant has demonstrated a good accuracy in the
3) Numerical model developed for steam generator and comparison between experimental data and theoretical
power plant has demonstrated a good accuracy in the results carried out through several simulation tests with
comparison between experimental data and theoretical respect to thermodynamic state of steam and global plant
results carried out through several simulation tests with efficiency
respect to thermodynamic state of steam and global plant 5) Numeric analysis highlighted that a different distribu-
efficiency tion of heat absorption in the radiative and convective
46
zones of steam generator is obtained. In particular, OFA [22] F. Famoso, R. Lanzafame, P. Monforte, C. Oliveri, and P. Scandura, “Air
configuration allows radiative heat transfer while RB quality data for catania: Analysis and investigation case study 2012-
2013,” vol. 81, 2015, pp. 644–654.
technique performs convective heat transfer. [23] G. La Rosa, C. Clienti, and F. L. Savio, “Fatigue analysis by acoustic
emission and thermographic techniques,” Procedia Engineering, vol. 74,
pp. 261–268, 2014.
R EFERENCES [24] G. La Rosa and F. L. Savio, “A first approach to the experimental study
of fracture parameters in opening and mixed mode by caustics,” Procedia
[1] S. Brusca, R. Lanzafame, A. Marino Cugno Garrano, and M. Messina, Engineering, vol. 109, pp. 418–426, 2015.
“Dynamic analysis of combustion turbine running on synthesis gas,” [25] M. Calı̀, G. Sequenzia, S. M. Oliveri, and G. Fatuzzo, “Meshing angles
International Journal of Applied Engineering Research, vol. 10, no. 21, evaluation of silent chain drive by numerical analysis and experimental
pp. 42 244–42 253, 2015. test,” Meccanica, vol. 51, no. 3, pp. 475–489, 2016.
[2] S. Brusca, R. Lanzafame, and M. Messina, “Design and performance of a [26] W. Duo, V. Uloth, I. Karidio, D. Leclerc, J. Kish, and D. Smgbeil,
straight-bladed darrieus wind turbine,” International Journal of Applied “Experimental study of dioxin formation and emissions from power
Engineering Research, vol. 10, no. 16, pp. 37 431–37 438, 2015. boilers burning salt-laden wood waste,” vol. 1, 2008, pp. 400–440.
[3] ——, “Wind turbine placement optimization by means of the monte [27] M. Calı̀, D. Speranza, and M. Martorelli, “Dynamic spinnaker per-
carlo simulation method,” Modelling and Simulation in Engineering, formance through digital photogrammetry, numerical analysis and ex-
vol. 2014, 2014. perimental tests,” in Advances on Mechanics, Design Engineering and
[4] V. Chiodo, G. Zafarana, S. Maisano, S. Freni, A. Galvagno, and F. Ur- Manufacturing. Springer, 2017, pp. 585–595.
bani, “Molten carbonate fuel cell system fed with biofuels for electricity [28] W. Duo, I. Karidio, and V. Uloth, “Reducing fossil fuel use in hogged
production,” International Journal of Hydrogen Energy, vol. 41, no. 41, fuel power boilers,” Pulp and Paper Canada, vol. 109, no. 6, pp. 25–35,
pp. 18 815–18 821, 2016. 2008.
[5] A. Galvagno, M. Prestipino, G. Zafarana, and V. Chiodo, “Analysis [29] C. Kaplan, G. Patnaik, and K. Kailasanath, “Universal relationships in
of an integrated agro-waste gasification and 120 kw sofc chp system: sooting methane-air diffusion flames,” Combustion Science and Tech-
Modeling and experimental investigation,” vol. 101, 2016, pp. 528–535. nology, vol. 131, no. 1-6, pp. 39–65, 1998.
[6] S. Brusca, R. Lanzafame, A. Marino Cugno Garrano, and M. Messina, [30] K. Aung, M. Hassan, and G. Faeth, “Flame stretch interactions of lami-
“On the possibility to run an internal combustion engine on acetylene nar premixed hydrogen/air flames at normal temperature and pressure,”
and alcohol,” vol. 45, 2014, pp. 889–898. Combustion and Flame, vol. 109, no. 1-2, pp. 1–24, 1997.
[7] S. Brusca, R. Lanzafame, and M. Messina, “Flow similitude laws applied [31] C. Kaplan, C. Shaddix, and K. Smyth, “Computations of enhanced soot
to wind turbines through blade element momentum theory numerical production in time-varying ch4/air diffusion flames,” Combustion and
codes,” International Journal of Energy and Environmental Engineering, Flame, vol. 106, no. 4, pp. 392–405, 1996.
vol. 5, no. 4, pp. 313–322, 2014. [32] R. Bilger, “Reaction rates in diffusion flames,” Combustion and Flame,
vol. 30, no. C, pp. 277–284, 1977.
[8] ——, Low-speed wind tunnel: Design and build, 2011.
[33] G. LO SCIUTO, G. CAPIZZI, S. COCO, and R. SHIKLER, Geometric
[9] S. Brusca, R. Lanzafame, A. Marino Cugno Garrano, and M. Messina,
Shape Optimization of Organic Solar Cells for Efficiency Enhancement
“Effects of pressure, temperature and dilution on fuels/air mixture
by Neural Networks. Cham: Springer International Publishing, 2017,
laminar flame burning velocity,” vol. 82, 2015, pp. 125–132.
pp. 789–796.
[10] M. Prestipino, V. Palomba, S. Vasta, A. Freni, and A. Galvagno, “A [34] F. Bonanno, G. Capizzi, G. L. Sciuto, D. Gotleyb, S. Linde, and
simulation tool to evaluate the feasibility of a gasification-i.c.e. system R. Shikler, “Extraction parameters and optimization in organic solar
to produce heat and power for industrial applications,” vol. 101, 2016, cell by solving transcendental equations in circuital models combined
pp. 1256–1263. with a neuroprocessing-based procedure,” in 2016 International Sympo-
[11] G. Cannistraro, M. Cannistraro, A. Cannistraro, A. Galvagno, and sium on Power Electronics, Electrical Drives, Automation and Motion
G. Trovato, “Reducing the demand of energy cooling in the ced, ”centers (SPEEDAM), June 2016, pp. 872–877.
of processing data”, with use of free-cooling systems,” International [35] R. Bilger, “The structure of diffusion flames,” Combustion Science and
Journal of Heat and Technology, vol. 34, no. 3, pp. 498–502, 2016. Technology, vol. 13, no. 1-6, pp. 155–170, 1976.
[12] ——, “Evaluation on the convenience of a citizen service district heating [36] Y. Xie, J. Wang, X. Cai, and Z. Huang, “Pressure history in the explosion
for residential use. a new scenario introduced by high efficiency energy of moist syngas/air mixtures,” Fuel, vol. 185, pp. 18–25, 2016.
systems,” International Journal of Heat and Technology, vol. 33, no. 4, [37] S. G. M. P. e. a. Capizzi, G., “Cascade feed forward neural network-
pp. 167–172, 2015. based model for air pollutants evaluation of single monitoring stations
[13] S. Brusca, F. Famoso, R. Lanzafame, A. Marino Cugno Garrano, and in urban areas,” International Journal of Electronics and Telecommuni-
P. Monforte, “Experimental analysis of a plume dispersion around cations,, vol. 61, no. 4, pp. 327–332, 2015.
obstacles,” vol. 82, 2015, pp. 695–701.
[14] S. Brusca, R. Lanzafame, A. Marino Cugno Garrano, and M. Messina,
“Laminar flame burning velocity of fuels/air mixture at different pres-
sure, temperature and equivalence ratio,” International Journal of Ap-
plied Engineering Research, vol. 10, no. 22, pp. 42 851–42 857, 2015.
[15] S. Brusca, F. Famoso, R. Lanzafame, S. Mauro, A. Garrano, and
P. Monforte, “Theoretical and experimental study of gaussian plume
model in small scale system,” vol. 101, 2016, pp. 58–65.
[16] S. Brusca, F. Famoso, R. Lanzafame, S. Mauro, M. Messina, and
S. Strano, “Pm¡inf¿10¡/inf¿ dispersion modeling by means of cfd 3d and
eulerian-lagrangian models: Analysis and comparison with experiments,”
vol. 101, 2016, pp. 329–336.
[17] S. Brusca, F. Famoso, R. Lanzafame, S. Mauro, A. Garrano, and
P. Monforte, “Theoretical and experimental study of gaussian plume
model in small scale system,” vol. 101, 2016, pp. 58–65.
[18] F. Famoso, R. Lanzafame, S. Maenza, and P. Scandura, “Performance
comparison between micro-inverter and string-inverter photovoltaic sys-
tems,” vol. 81, 2015, pp. 526–539.
[19] R. Lanzafame, P. Scandura, F. Famoso, and P. Monforte, “No2 concen-
tration analysis in urban area of catania,” vol. 45, 2014, pp. 671–680.
[20] R. Lanzafame, P. Scandura, F. Famoso, P. Monforte, and C. Oliveri, “Air
quality data for catania: Analysis and investigation case study 2010-
2011,” vol. 45, 2014, pp. 681–690.
[21] A. Caramagna, F. Famoso, R. Lanzafame, and P. Monforte, “Analysis of
vertical profile of particulates dispersion in function of the aerodynamic
diameter at a congested road in catania,” vol. 82, 2015, pp. 702–707.
47