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HIGH MOISTURE COAL – EFFECT OF
BLENDING ON BOILER PERFORMANCE
Pradip chanda, AGM (PMI)
Import coal blending is inevitable for Indian
power sector
0.66
0.42
0.57
1.24
3.14
4.53
6.56
6
8.71
9.87
9.44
10.31
8.69
11.56
21.7
25.2
27.76
37.92
44.28
0.36 0.22
0.28
0.59 1.37
1.85
2.61 2.37
3.27 3.54
3.21 3.37
2.66
3.33
5.78
6.32 6.57
8.28
9.08
0.00
1.00
2.00
3.00
4.00
5.00
6.00
7.00
8.00
9.00
10.00
0
5
10
15
20
25
30
35
40
45
50
FY-92
FY-93
FY-94
FY-95
FY-96
FY-97
FY-98
FY-99
FY-00
FY-01
FY-02
FY-03
FY-04
FY-05
FY-06
FY-07
FY-08
FY-09
FY-10
%age
CoalImport(milliontons)
Rising Coal Imports-Non Coking Coal
Imports Imported coal as %age of domestic coal
Blending of high moisture coal for Indian power
boiler -issues
• Deterioration of mill performance .
• Heat loss in the Boiler due to high moisture
• Possibility of slag formation due to blending.
Outline of the study
• Mill Temperature modeling
• Flame temperature modeling
• Furnace temperature modeling
• Ash slagging modeling
• Determining blending ratio
Mill temperature model
• The mill temperature is modelled from mass and
heat balance.
• Model described by Jian-Lin Wei et al [16] modified
for incorporating moisture component of coal used
as
Where K1to K17 are determined through Genetic
algorithm
Flame temperature model
• The flame temperature is modelled from mixed
adiabatic temperature of the constituent burning
gases.
using the equation become
, T= (Tadb-Tref)
Xri =Reactant , Ypj= Product, Cp= Sp. Heat.
Tadb/Tref =Adiabatic flame temperature/ ref. temp
Pj
j
PjRi
i
Ri hYhX   TCh avgp  ,
   
i j
T
T
PPipPj
T
T
RRipRi
ad
ref
R
ref
dTcYdTcX ,,
Furnace temperature model
• The furnace zone flue gas temperature is modelled
as.
• = Mass flow rate, H/Δh= Enthalpy/ change in enthalpy
• σ = Stiffen Boltzman const. ε = Flame emissivity
• Aww = Water wall area. Tfl = Flue gas temp.
flfl
wwadwwashashairairfuelfuelfuelfuel
reffl
CM
TTAhMhMHMhM
TT

 )()(
)(
44



M
Simulating the model for a 500 MW boiler
• Two coal sample data (one of domestic coal and one
from high moisture imported coal) used for flame
temperature model simulation.
• Numbers of blended scenario created with change
in blending ratio.
• Mass fraction of fuel component determined separately
for each blend type and used as input to the model.
• Model is simulated on excel spread sheet**. (Emissivity of the
flame calculated from mean beam length and furnace geometry. The value obtained is
0.67. The fly ash specific heat capacity is assumed as 0.227 Kcal/deg K.)
• Result shows that with increment in blending ratio, flame
and furnace temperature slightly reduces
• However, the coal mill outlet temperature gets
significantly reduce.
• This because of cumulative effect of reduction in 2ndary
air temperature as well as introduction of high moisture
in coal inlet
**The component –II (combustion) spread sheet of ‘Engineering
software’ (www.engineering-4e.com ) used for determining the
enthalpy of individual reactants and products.
Mill outlet temperature
74
76
78
80
82
84
86
0 5 10 15 20 25 30 35
Milloutlettempindegcen
Blend in %
Mill outlet temperature trend
Series1
Mass fraction
(mass/mass)
Blend
Case-I
90/10
Blend
Case-II
85/15
Blend
Case-III
80/20
Blend
Case-IV
70/30
Carbon 0.463259 0.461049 0.458839 0.454418
Hydrogen 0.048237 0.048516 0.048795 0.049353
Oxygen 0.003597 0.003699 0.003801 0.004005
Sulphur 0.028982 0.028205 0.027429 0.025875
Nitrogen 0.155964 0.155911 0.155857 0.15575
Moisture 0.299961 0.30262 0.30528 0.310598
Flame temp °K
EA-20%
η -0.90%
1889 1887 1884 1879
1878
1880
1882
1884
1886
1888
1890
0 5 10 15 20 25 30 35
FlameTemperatureinKelvin
Blending %
Flame temperature trend on blending
Cases Blend
Case-I
90/10
Blend
Case-II
85/15
Blend
Case-III
80/20
Blend
Case-IV
70/30
Mass of flue per Kg fuel
(EA- 20 %)
5.6 5.61 5.63 5.76
T (Fur Zone) °K
1372.12 1352.26 1345.96 1342.72
1340
1345
1350
1355
1360
1365
1370
1375
0 5 10 15 20 25 30 35
FlurnaceTemperatureinKelvin
Blending %
Furnace temperature trend on blending
Furnace Slagging possibility
• The ash fusion temperature (AFT) of blends increased
with increasing amounts of Al2O3, CaO, K2O, Na2O and
TiO2.
• as per Carpenter (1995) the base to acid ratio is
commonly used to predict the slagging propensity of a
coal. It is defined as:
• A value of the base to acid ratio between 0.4 and 0.7
indicates a high slagging propensity. Values outside
this range indicate a lesser likelihood to slag.
• The blended coal acid to base ratio is tabled in next
slide.
Ash quality in blended coal
Oxide
(%)
SiO2 TiO2 Al2O3 CaO MgO Fe2O3 MnO
K2O&Na2
0
Ratio(A)
Fe:Ca
Ratio (B)
Basic:
Acidic
(1) (2) (3) (4) (5) (6) (7) (8)
(6)/ (4) [(4)+(5)+
(6)+(8)]/
[(1)+(2)+
(3)]
Coal-I 54.80 1.88 24.50 3.57 1.87 9.08 0.10 1.50 2.54 0.19
Coal-II 52.00 0.00 31.80 2.70 4.70 4.90 0.00 2.70 1.81 0.18
Blend
(90/10) 54.73 1.84 24.69 3.54 1.94 8.98 0.10 1.53 2.53 0.20
Blend
(85/15/) 54.73 1.84 24.68 3.55 1.93 8.98 0.10 1.53 2.53 0.20
Blend
(80/20) 54.70 1.82 24.76 3.54 1.97 8.93 0.10 1.54 2.53 0.20
Blend(
75/25) 54.67 1.80 24.84 3.53 2.00 8.89 0.10 1.56 2.52 0.20
Ratio (A) range of slagging is from 0.3 to 3.0 with maximum slagging possibility near 1.0
Ratio (B) range of slagging is from 0.4 to 0.7
0.00
0.50
1.00
1.50
2.00
2.50
3.00
0 5 10 15 20 25 30
basic:Acidicindex
Coal blending %
Ash slagging study
Iron:Calcium
base to acid
Fig 3
Iron: Calcium ratio beyond the range from 0.3 to 1.0 indicate lesser likely hood of
slagging
Acid to base ratio beyond 0.4 to 0.7 indicated lesser likely hood of slagging.
Conclusion
• A study conducted on blending of high moisture imported
coal with Indian coal.
• Moisture in blended coal reduces flame temperature and mill
outlet temperature.
• Ash generation is less.
• The blend apparently not adversely effecting the slagging of
the ash.
Reference:
[1] Naveen Chandralal, D. Mahapatra, D. Shome and P. Dasgupta. Behaviour of low
rank high moisture coal in large stockpile under ambient condition. American
International Journal of Research in Formal, Applied and Natural Science, 14-
210, 2014.
[2] Shimogori, Yoshizako, Mark Richardson, Characteristics of Coal Ash Emissivity
in high temperature atmosphere- ISME International Journal, series B, Vol
4.9, No. 2, 2006
[3] Chanǵan Wang, Yinhe Liv, Xiaoming Zhang, Defuche A study on Coal properties
and combustion characteristics of blended coals in Northwestern China–
Energy & Fuels, American Chemical Society publication, 2011
[4] Yonghua Li. A new Distinguish Method of Blending of Coals slagging
characteristics-, Energy & Power Engineering, 2011
[5] Prabir Basu, Cen Kefa, Louis Jeslin. Boilers and Burners, Springler, 1999
[6] Terry Wall, Liza Elliot, Dick Sanders, Ashley Conroy A review of the state of the
art in Coal blending for power generation –, University of
Newcastel, Australia, 2011
[7] Lecture presentation by Dr. P.M.V. Subbarao. A cause- Effect analysis of
Furnace heat transfer – IIT, Delhi
[8] Energy Conversion with plot 1.1 – Engineering software Demo version,
www.engineering- 4e.com
[9] Report of the group for studying range of blending of imported coal with
domestic coal. Central Electricity Authority, India, 2013
[10] The coal resource, A comprehensive overview of coal. World coal
Institute, UK.
[11] Mikael Höök, Werner Zittel, Jörg Schindler, Kjell Aleklett. Global coal
production outlooks based on a logistic model. Fuel, volume 89, issue
11, Nov 2010, Pg 3546-3558.
[12] Protosh Saxena, The optimum mix- impact of coal quality variation on powe
r plant. Power Line July 2013.
[13] A Chandra and H Chandra. Impact of Indian and imported coal on Indian
Thermal power Plant. Journal of Scientific and industrial research, volume
63, 2004, pg 156-162.
[14] NTPC's Study on Blending and Right Mix of Imported Coal, 2007
[15] C Choudhury, R.K. Raot and S. Narendra. Use of high moisture imported
coal in NTPC Simhadri- A case study. International O&M conference,
NTPC, 2013
[16] Jian-Lin Wei, Jihong Wang and Q.H. Wu. Development of a multisegment
coal mill model using an evolutionary computation technique. IEEE
Transactions on Energy conversion, Vol.22, No.3, 2007.
THANK YOU

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Blending with high moisture coal an approach

  • 1. HIGH MOISTURE COAL – EFFECT OF BLENDING ON BOILER PERFORMANCE Pradip chanda, AGM (PMI)
  • 2. Import coal blending is inevitable for Indian power sector 0.66 0.42 0.57 1.24 3.14 4.53 6.56 6 8.71 9.87 9.44 10.31 8.69 11.56 21.7 25.2 27.76 37.92 44.28 0.36 0.22 0.28 0.59 1.37 1.85 2.61 2.37 3.27 3.54 3.21 3.37 2.66 3.33 5.78 6.32 6.57 8.28 9.08 0.00 1.00 2.00 3.00 4.00 5.00 6.00 7.00 8.00 9.00 10.00 0 5 10 15 20 25 30 35 40 45 50 FY-92 FY-93 FY-94 FY-95 FY-96 FY-97 FY-98 FY-99 FY-00 FY-01 FY-02 FY-03 FY-04 FY-05 FY-06 FY-07 FY-08 FY-09 FY-10 %age CoalImport(milliontons) Rising Coal Imports-Non Coking Coal Imports Imported coal as %age of domestic coal
  • 3. Blending of high moisture coal for Indian power boiler -issues • Deterioration of mill performance . • Heat loss in the Boiler due to high moisture • Possibility of slag formation due to blending.
  • 4. Outline of the study • Mill Temperature modeling • Flame temperature modeling • Furnace temperature modeling • Ash slagging modeling • Determining blending ratio
  • 5. Mill temperature model • The mill temperature is modelled from mass and heat balance. • Model described by Jian-Lin Wei et al [16] modified for incorporating moisture component of coal used as Where K1to K17 are determined through Genetic algorithm
  • 6. Flame temperature model • The flame temperature is modelled from mixed adiabatic temperature of the constituent burning gases. using the equation become , T= (Tadb-Tref) Xri =Reactant , Ypj= Product, Cp= Sp. Heat. Tadb/Tref =Adiabatic flame temperature/ ref. temp Pj j PjRi i Ri hYhX   TCh avgp  ,     i j T T PPipPj T T RRipRi ad ref R ref dTcYdTcX ,,
  • 7. Furnace temperature model • The furnace zone flue gas temperature is modelled as. • = Mass flow rate, H/Δh= Enthalpy/ change in enthalpy • σ = Stiffen Boltzman const. ε = Flame emissivity • Aww = Water wall area. Tfl = Flue gas temp. flfl wwadwwashashairairfuelfuelfuelfuel reffl CM TTAhMhMHMhM TT   )()( )( 44    M
  • 8. Simulating the model for a 500 MW boiler • Two coal sample data (one of domestic coal and one from high moisture imported coal) used for flame temperature model simulation. • Numbers of blended scenario created with change in blending ratio. • Mass fraction of fuel component determined separately for each blend type and used as input to the model.
  • 9. • Model is simulated on excel spread sheet**. (Emissivity of the flame calculated from mean beam length and furnace geometry. The value obtained is 0.67. The fly ash specific heat capacity is assumed as 0.227 Kcal/deg K.) • Result shows that with increment in blending ratio, flame and furnace temperature slightly reduces • However, the coal mill outlet temperature gets significantly reduce. • This because of cumulative effect of reduction in 2ndary air temperature as well as introduction of high moisture in coal inlet **The component –II (combustion) spread sheet of ‘Engineering software’ (www.engineering-4e.com ) used for determining the enthalpy of individual reactants and products.
  • 10. Mill outlet temperature 74 76 78 80 82 84 86 0 5 10 15 20 25 30 35 Milloutlettempindegcen Blend in % Mill outlet temperature trend Series1
  • 11. Mass fraction (mass/mass) Blend Case-I 90/10 Blend Case-II 85/15 Blend Case-III 80/20 Blend Case-IV 70/30 Carbon 0.463259 0.461049 0.458839 0.454418 Hydrogen 0.048237 0.048516 0.048795 0.049353 Oxygen 0.003597 0.003699 0.003801 0.004005 Sulphur 0.028982 0.028205 0.027429 0.025875 Nitrogen 0.155964 0.155911 0.155857 0.15575 Moisture 0.299961 0.30262 0.30528 0.310598 Flame temp °K EA-20% η -0.90% 1889 1887 1884 1879 1878 1880 1882 1884 1886 1888 1890 0 5 10 15 20 25 30 35 FlameTemperatureinKelvin Blending % Flame temperature trend on blending
  • 12. Cases Blend Case-I 90/10 Blend Case-II 85/15 Blend Case-III 80/20 Blend Case-IV 70/30 Mass of flue per Kg fuel (EA- 20 %) 5.6 5.61 5.63 5.76 T (Fur Zone) °K 1372.12 1352.26 1345.96 1342.72 1340 1345 1350 1355 1360 1365 1370 1375 0 5 10 15 20 25 30 35 FlurnaceTemperatureinKelvin Blending % Furnace temperature trend on blending
  • 13. Furnace Slagging possibility • The ash fusion temperature (AFT) of blends increased with increasing amounts of Al2O3, CaO, K2O, Na2O and TiO2. • as per Carpenter (1995) the base to acid ratio is commonly used to predict the slagging propensity of a coal. It is defined as: • A value of the base to acid ratio between 0.4 and 0.7 indicates a high slagging propensity. Values outside this range indicate a lesser likelihood to slag. • The blended coal acid to base ratio is tabled in next slide.
  • 14. Ash quality in blended coal Oxide (%) SiO2 TiO2 Al2O3 CaO MgO Fe2O3 MnO K2O&Na2 0 Ratio(A) Fe:Ca Ratio (B) Basic: Acidic (1) (2) (3) (4) (5) (6) (7) (8) (6)/ (4) [(4)+(5)+ (6)+(8)]/ [(1)+(2)+ (3)] Coal-I 54.80 1.88 24.50 3.57 1.87 9.08 0.10 1.50 2.54 0.19 Coal-II 52.00 0.00 31.80 2.70 4.70 4.90 0.00 2.70 1.81 0.18 Blend (90/10) 54.73 1.84 24.69 3.54 1.94 8.98 0.10 1.53 2.53 0.20 Blend (85/15/) 54.73 1.84 24.68 3.55 1.93 8.98 0.10 1.53 2.53 0.20 Blend (80/20) 54.70 1.82 24.76 3.54 1.97 8.93 0.10 1.54 2.53 0.20 Blend( 75/25) 54.67 1.80 24.84 3.53 2.00 8.89 0.10 1.56 2.52 0.20 Ratio (A) range of slagging is from 0.3 to 3.0 with maximum slagging possibility near 1.0 Ratio (B) range of slagging is from 0.4 to 0.7
  • 15. 0.00 0.50 1.00 1.50 2.00 2.50 3.00 0 5 10 15 20 25 30 basic:Acidicindex Coal blending % Ash slagging study Iron:Calcium base to acid Fig 3 Iron: Calcium ratio beyond the range from 0.3 to 1.0 indicate lesser likely hood of slagging Acid to base ratio beyond 0.4 to 0.7 indicated lesser likely hood of slagging.
  • 16. Conclusion • A study conducted on blending of high moisture imported coal with Indian coal. • Moisture in blended coal reduces flame temperature and mill outlet temperature. • Ash generation is less. • The blend apparently not adversely effecting the slagging of the ash.
  • 17. Reference: [1] Naveen Chandralal, D. Mahapatra, D. Shome and P. Dasgupta. Behaviour of low rank high moisture coal in large stockpile under ambient condition. American International Journal of Research in Formal, Applied and Natural Science, 14- 210, 2014. [2] Shimogori, Yoshizako, Mark Richardson, Characteristics of Coal Ash Emissivity in high temperature atmosphere- ISME International Journal, series B, Vol 4.9, No. 2, 2006 [3] Chanǵan Wang, Yinhe Liv, Xiaoming Zhang, Defuche A study on Coal properties and combustion characteristics of blended coals in Northwestern China– Energy & Fuels, American Chemical Society publication, 2011 [4] Yonghua Li. A new Distinguish Method of Blending of Coals slagging characteristics-, Energy & Power Engineering, 2011 [5] Prabir Basu, Cen Kefa, Louis Jeslin. Boilers and Burners, Springler, 1999 [6] Terry Wall, Liza Elliot, Dick Sanders, Ashley Conroy A review of the state of the art in Coal blending for power generation –, University of Newcastel, Australia, 2011 [7] Lecture presentation by Dr. P.M.V. Subbarao. A cause- Effect analysis of Furnace heat transfer – IIT, Delhi [8] Energy Conversion with plot 1.1 – Engineering software Demo version, www.engineering- 4e.com [9] Report of the group for studying range of blending of imported coal with domestic coal. Central Electricity Authority, India, 2013
  • 18. [10] The coal resource, A comprehensive overview of coal. World coal Institute, UK. [11] Mikael Höök, Werner Zittel, Jörg Schindler, Kjell Aleklett. Global coal production outlooks based on a logistic model. Fuel, volume 89, issue 11, Nov 2010, Pg 3546-3558. [12] Protosh Saxena, The optimum mix- impact of coal quality variation on powe r plant. Power Line July 2013. [13] A Chandra and H Chandra. Impact of Indian and imported coal on Indian Thermal power Plant. Journal of Scientific and industrial research, volume 63, 2004, pg 156-162. [14] NTPC's Study on Blending and Right Mix of Imported Coal, 2007 [15] C Choudhury, R.K. Raot and S. Narendra. Use of high moisture imported coal in NTPC Simhadri- A case study. International O&M conference, NTPC, 2013 [16] Jian-Lin Wei, Jihong Wang and Q.H. Wu. Development of a multisegment coal mill model using an evolutionary computation technique. IEEE Transactions on Energy conversion, Vol.22, No.3, 2007.