Influence of increased primary air ratio on boiler performance in a 660 MW brown coal boiler

Accepted Manuscript Influence of increased primary air ratio on boiler performance in a 660MW brown coal boiler

Zixiang Li, Zhengqing Miao, Yan Zhou, Shurong Wen, Jiangtao Li PII:

S0360-5442(18)30590-5

DOI:

10.1016/j.energy.2018.04.001

Reference:

EGY 12639

To appear in:

Energy

Received Date:

11 December 2017

Revised Date:

28 March 2018

Accepted Date:

01 April 2018

Please cite this article as: Zixiang Li, Zhengqing Miao, Yan Zhou, Shurong Wen, Jiangtao Li, Influence of increased primary air ratio on boiler performance in a 660MW brown coal boiler, Energy (2018), doi: 10.1016/j.energy.2018.04.001

This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

ACCEPTED MANUSCRIPT 1

Influence of increased primary air ratio on boiler performance in a 660MW brown coal boiler

2

Zixiang Lia, Zhengqing Miaoa, Yan Zhoub, Shurong Wenb, Jiangtao Lic

3

a.

4

Shanghai 200240, People’s Republic of China

5

b.

North United Power Co. Ltd, Inner Mongolia, 010000, People’s Republic of China

6

c.

Shanghai Boiler Works Ltd, Shanghai 200240, People’s Republic of China

7

Abstract

Institute of Thermal Energy Engineering, School of Mechanical Engineering, Shanghai Jiao Tong University,

8

A computational fluid dynamics model was established based on a 660MW brown coal boiler, to study the effects of

9

primary air ratio (PAR) on boiler performance. To improve model prediction, moisture content in brown coal is specially

10

considered. Confidence in the model was established by carrying out mesh independence test and validation against real

11

life data and theoretical calculations. Then it was used to simulate 10 cases with different PAR. Results show that with

12

PAR increasing from 0.325 to 0.55, overall boiler performance deteriorates and total radiative heat flux decreases by

13

35.2MW. However, the temperature distribution and heat flux in main burners region and above separated over fire air

14

region show a parabolic trend. The results indicate that boiler performance deteriorates with PAR increasing, and well

15

explains why boiler thermal load is still reduced, even if PAR is increased to maintain the drying capacity in high moisture

16

content cases. Momentum ratio of primary and secondary air is pointed out to be the main cause of this phenomenon. At

17

last, a feasible solution is proposed to raise primary air temperature, not the ratio of it, to maintain the drying capacity.

18

Therefore, the adverse effects caused by increased PAR can be avoided.

19 20

Keywords: Brown coal boiler, Primary air ratio, Combustion performance, Numerical simulation 1. Introduction



Corresponding author. Tel: +86 21 3420 5683. E-mail address: [email protected] Notes: The authors declare no competing financial interest. 1

ACCEPTED MANUSCRIPT 21

At current consumption rate, global coal storage that can be mined will last at least 150 years and nearly 40% of it is

22

brown coal [1]. In china, the reservation of brown coal exceeds 130 billion tons, accounting for more than 13% of the

23

national total storage [2]. Generally, brown coal has some advantages like low mining cost, high volatile matter content

24

and low pollution forming elements. However, as a type of low rank coal, its features of high moisture content (MC), high

25

ash content and lower heating value significantly limit its application in power plants [3]. For example, the capacity

26

provided by large-scale lignite-fired power plants in China is lower than 3% of the national installed capacity [4]. Among

27

the above shortcomings, high MC is deemed to be the most adverse feature that results in lower power plant efficiency

28

(PPE), higher transportation costs and spontaneous combustion during storage [5][6].

29

So far, enormous works have been conducted to study the effect of MC on brown coal combustion behavior. The

30

greenhouse gases emission (CO2 for instance) was reported to be higher in brown coal boilers due to its lower boiler

31

efficiency [7][8], as a 1% increase in PPE can result in up to a 2.5% reduction in CO2 emissions [9]. Tahmasebzadehbaie

32

et al [10] reported that the emission decrement when thermal efficiency was increased, is due to less fuel consumption in

33

higher PPE condition. Tahmasebi et al [11] found the ignition of lignite particles takes more time when MC is increased

34

and the same conclusion was reported by Binner et al [12]. This was interpreted as the evaporation of water takes time and

35

the steam zone formed in the vicinity of particles inhibits the particles temperature from increasing [11]. Prationo et al [13]

36

found that the volatile flame was enlarged by the evaporated moisture and the coal flame intensity was weaker than dried

37

coal, as the volatile cloud was diluted by the evaporated water. As more high grade heat released by coal combustion was

38

absorbed by water evaporation, the overall boiler efficiency was then decreased [14]. Tian et al [15] found a slight decrease

39

in incident radiation in the main burners’ region with the increase of MC. Kurose et al [16] found that the unburned carbon

40

fraction at the furnace outlet increases with the increase of MC.

41

Considering the negative impacts of MC on brown coal combustion behavior, pre-drying technologies are used to

42

reduce water content in the raw coal. Some literatures reviewed the recent development of drying technologies [6][17][18], 2

ACCEPTED MANUSCRIPT 43

and many researches was conducted to investigate the improvement of PPE when pre-drying technique was employed and

44

pre-dried coal is burned. It is estimated that an optimized drying process in future brown coal power plant may increase

45

the total PPE by 4%-6% [19]. Through a theoretical model, Liu Ming et al [20] estimated that the overall PPE could be

46

raised by 1.87% when MC was pre-dried to 19.5% from 39.5%. Wang et al [21] reported that the auxiliary power can be

47

decreased by 3.8%, when MC was reduced from 40% to 25%. Xu et al [22] investigated a lignite pre-drying system

48

incorporated with a supplementary steam cycle, and found that the net PPE can be improved by 2.6% and the cost of

49

electricity can be reduced by 1.26$/MWh. Agraniotis et al [19] investigated the co-firing of raw brown coal and pre-dried

50

brown coal in a 590MW utility boiler and found that the net PPE can be increased by 5.9% when 100% pre-dried lignite is

51

fired and 1.5% when 25% pre-dried lignite is co-fired.

52

Although pre-dried coal has great advantages over the raw wet brown coal, pre-drying process consumes large amount

53

of energy [23] and may cause spontaneous ignition due to its high sensitive volatile content [3]. Besides, not all the power

54

stations were equipped with pre-drying system when they were firstly built. For those boilers without pre-drying facilities,

55

raw brown coal is directly fed into the mill system and then heated and dried in it. In the mill system, when MC is greater

56

than the design value, the energy provided by primary air (PA) cannot dry the coal particles to the design level if PA

57

temperature is remained unchanged. This results in an accumulation of pulverized coal in the mill system and consequently

58

blocks the coal pulverizing system [14]. A feasible solution is to use the air-preheating method, i.e. heat recirculation, to

59

preheating the inlet air and increase the primary air temperature [24]. However, the practical operation in power plant is to

60

raise the primary air ratio (PAR) to increase the total energy input in the mill system. This forced action causes PAR to

61

deviate from the design value, and thus alters the original aerodynamics condition and combustion performance. Several

62

researches have been conducted to investigate the influence of PAR on the combustion characteristics in boiler with swirl

63

burners [25][26][27], but few literature was focused on the direct burners. Long et al [28] investigated the influence of a

64

slightly elevated PAR on the combustion performance in a dual-circle tangential ultra-supercritical boiler, and found out 3

ACCEPTED MANUSCRIPT 65

that PAR had great impact on the combustion characteristics.

66

In this paper, the influence of overly increased PAR on boiler performance was studied and the decrease of boiler

67

efficiency was linked to the momentum ratio of primary air to secondary air flow. For this purpose, a computational fluid

68

dynamics (CFD) model was established on the basis of a 660MW brown coal utility boiler. The simulation cases were

69

conducted based on the operational parameters of Shangdu power plant, located in Inner Mongolia, China. The model was

70

firstly validated by comparing the simulation results with reference data, then it was used to investigate the influence of

71

PAR on coal combustion behavior and boiler performance. Results show that PAR has a significant influence on the

72

combustion behavior, a deviation of PAR will cause a deterioration of overall boiler performance. The findings find out

73

why the boiler efficiency was still reduced, even if PAR was increased to meet the requirement of drying capacity in the

74

mill system. It is pointed out that the momentum ratio of PA and secondary air (SA) is the main factor that affects the in-

75

furnace combustion behavior. The boiler performance deteriorates severely when the momentum of PA and SA are too

76

close, which should be avoided in real boiler operation. When high moisture brown coal is used, a feasible solution is

77

suggested to increase the temperature of PA, rather than the ratio of it, to meet the increasing requirement of drying capacity

78

in the mill system. So that the adverse effects of increased PAR can be avoided.

79

2. Boiler description and Computational methodology

80

2.1 Boiler configuration and operational condition

81

In this paper, the simulation domain was established based on a 660MW wall-fired brown coal utility boiler, located

82

in Inner Mongolia, China. As schematically shown in Fig.1a, the boiler was 68.5m in height with an almost square cross-

83

section of 20.0x20.3m. In the furnace roof region, platen super-heater (PSH) and rear super-heater (RSH) were also taken

84

into consideration. Heat transfer tubes were simplified into plate panels with the same area. Other convection surfaces

85

behind the furnace exit including re-heater, air-preheater, and economizer were neglected because of their negligible impact

86

on the in-furnace combustion process. 4

ACCEPTED MANUSCRIPT 87

As depicted in Fig.1a, PA1-PA6 were 6 sets in-service main burners (MBs) on each wall, i.e. upper main burners

88

(UMB), intermediate main burners (IMB) and lower main burners (LMB). In order to enhance the mixing of air and coal

89

particles, 9 sets of SA nozzles, i.e. SA1-SA9, were set up above and below each MB. The separated over fire air (SOFA)

90

nozzles were situated in the SOFA region. MBs and SA nozzles were wall-installed, while SOFA nozzles were mounted

91

tangentially at four corners. Detailed installation information of burners and air nozzles can be found in Fig.1b.

92

Under the boiler maximum continuous rating condition, 536.1t/h raw brown coal was consumed to produce 1913 t/h

93

steam at 25.4 MPa and 571℃. Correspondingly, the flow rate of PA and SA for the design firing case was 254.3kg/s and

94

528.2kg/s respectively. Boiler efficiency was estimated as 92.10% based on the lower heating value on a received basis.

95

Coal properties used in the simulation process were consisted with those in actual operation, as listed in Table 1. The

96

particle size distribution is modeled with the Rosin-Rammler function, which had been validated for powder size prediction

97

previously [29]. The model parameters are minimum diameter, maximum diameter, mean diameter and spread number,

98

which has a value of 10μm, 1100μm, 90μm and 1.13, respectively.

99

2.2 Boundary conditions and cases set up

100

In CFD simulation work, the boundary conditions are vital to solve a specific steady-state problem. There were mainly

101

three types boundary condition employed in this paper, namely the velocity-inlet, the pressure-outlet and the wall condition.

102

The velocity-inlet defined the way of air input, includes MBs, SA nozzles and SOFA nozzles, detailed information is given

103

in Table 2. For the gas phase, a “non-slip” boundary condition was employed on the walls [28], including furnace wall

104

(FW), PSH and RSH. Since the temperature variation of the working medium inside the heat absorbing tubes was not

105

dramatic, the wall temperature of each individual part was assumed to be a constant. According to the working medium’s

106

temperature, the temperature of FW, PSH and RSH was set to be 750K, 850K, and 893K respectively. The emissivity of

107

all walls was set to be 0.8. The domain exit was considered as a pressure-outlet with a light negative pressure of 200pa,

108

and the backflow temperature through the exit was set to be 1200K. 5

ACCEPTED MANUSCRIPT 109

To study the effects of PAR on boiler performance, 10 different simulation cases were conducted in this work. As

110

listed in Table 2, case 1 was the design firing condition and case 10 was the actual unfavorable firing scenario. For all

111

cases, the excess air coefficient was 1.18 and the SOFA rate was fixed to 20%. The primary air was uniformly distributed

112

to each MB (24 in total), for instance, 1.53% air was introduced into the furnace through each MB in case 1, where PAR

113

was set to be 32.5%. However, the secondary air was distributed unevenly among SA nozzles, because the area of SA2,

114

SA5 and SA8 was bigger than other SA nozzles as shown in Fig.1a. The distribution principle was to keep the air velocity

115

identical in each SA nozzles. For example in case 1, 1.82% air was injected through each large SA nozzle (12 in total), and

116

1.07 % was injected through the each small SA nozzle (24 in total). The temperature of PA and pulverized coal particles

117

was 338K while the temperature of SA and SOFA was 671K. Since the area of PA and SA wind boxes were immutable,

118

the velocity was adjusted to meet the variation of PAR, detailed information is list below.

119

2.3 Simulation methodology and models selection

120

The simulation work presented was carried out by ANSYS FLUENT, version 15.0. Appropriate sub-models were

121

selected according to the best of our knowledge, and all of them were already validated in open literature [30][31][32]. A

122

detailed description of the computational modeling was presented below.

123

2.3.1 Gas-solid two-phase flow model

124

In pulverized coal boiler, the low particle-to-gas ratio makes it ideally to be considered in an Eulerian-Lagrangian

125

approach [33]. In Eulerian-Lagrangian approach, the continuous phase is solved in the Eulerian reference frame in the same

126

manner as for single phase, and the individual discrete phase particles are tracked therein.

127

2.3.1.1 Gas phase

128 129 130

The continuous gas phase is modeled with the Reynolds-averaged Navier-Stokes equations. For a three dimensional steady state convection-diffusion problem, the governing equations take the following general form: ∂(𝜌𝑢𝜙) ∂(𝜌𝑣𝜙) ∂(𝜌𝑤𝜙) ∂ + ∂𝑦 + ∂𝑧 = ∂𝑥 ∂𝑥

(𝛤∂𝜙∂𝑥) + ∂𝑦∂ (𝛤∂𝜙∂𝑦) + ∂𝑧∂ (𝛤∂𝜙∂𝑧) + 𝑆 6

(1)

ACCEPTED MANUSCRIPT 131 132

As shown in Table 3, depending on variable 𝜙, the above Eq. (1) presents the transport equation of continuity, momentum, energy, turbulence kinetic energy and its rate of dissipation.

133

To close the Reynolds-averaged Naiver-Stokes equations, the standard k-ε model was selected because of its good

134

performance and stability [34]. In this model, two additional variables – turbulence kinetic energy (𝑘) and its rate of

135

dissipation (𝜀) are calculated. The turbulent viscosity 𝜇𝑡 is calculated as 𝜌𝐶𝜇𝑘 𝜀, and the model constants are 𝐶1𝜀=1.44,

136

𝐶2𝜀=1.92, 𝐶𝜇=0.09, 𝜎𝑘=1.0, 𝜎𝑠=1.3.

137

2.3.1.2 Particulate phase

138 139

2

The discrete phase model (DPM) is used to simulate the particulate phase, where the trajectory of a discrete phase particle is calculated by solving the momentum equations in a Cartesian system as Eq. (2): 𝑑𝑢𝑝

140 141

𝑑𝑡

=

18𝜇 𝐶𝐷𝑅𝑒 2 𝜌 𝑑 24 𝑝 𝑝

(𝑢 ‒ 𝑢𝑝) +

𝑔(𝜌𝑝 ‒ 𝜌)

(2)

𝜌𝑝

Herein, the right side of Eq. (2) are drag force term and gravity force term, respectively. Particle Reynolds number is: 𝑅𝑒 = 𝜌𝑑𝑝|𝑢𝑝 ‒ 𝑢| 𝜇

142

(3)

143

Besides, particles dispersion caused by fluid turbulence is included by using the stochastic tracking model [35]. In

144

stochastic tracking approach, the particles turbulence dispersion is predicted by replacing the mean fluid velocity 𝑢 with

145

the instantaneous fluid velocity 𝑢 + 𝑢 (𝑡) in above Eq. (2) and Eq. (3).

146

2.3.2 Devolatilization model

'

147

When heated up, the volatile matters released from coal particles before coal combustion process. The devolatilization

148

process is simulated with the two-competing rates model proposed by Kobayashi [36], in which the devolatilizaiton rate is

149

determined by two competing rates that controls the devolatilization process in different temperature range.

150

Low temperature range:

ℛ1 = 𝐴1𝑒

High temperature range:

ℛ2 = 𝐴2𝑒

‒

(𝐸1 𝑅𝑇𝑝)

(4)

‒

(𝐸2 𝑅𝑇𝑝)

(5)

Then these two rates are weighted to yield an expression for the overall devolatilization rate as: 7

ACCEPTED MANUSCRIPT 𝑚𝑣(𝑡)

151 152

(1 ‒ 𝑓𝑤,0)𝑚𝑝,0 ‒ 𝑚𝑎 =

(

8 ‒1

(6)

13 ‒ 1

,7.42 × 10 𝑠

The pre-exponential factors 𝐴1,𝐴2 are 9.71 × 10 𝑠 5

)

∫𝑡 (𝛼1ℛ1 + 𝛼2ℛ2)𝑒𝑥𝑝 ‒ ∫𝑡 (ℛ1 + ℛ2)𝑑𝑡 𝑑𝑡 0 0

, and the activation energy constant 𝐸1,𝐸2 are

5

153

1.93 × 10 𝑗/𝑚𝑜𝑙, 3.47 × 10 𝑗/𝑚𝑜𝑙 respectively [37]. According to the recommendation of Kobayashi et al [36], the yield

154

factor 𝛼1 is assumed as the mass fraction of volatile matter in approximate analysis, and 𝛼2 is set to be unity.

155

2.3.3 Combustion model

156

2.3.3.1 Volatile matters combustion

157

The combustion of volatile matters is modeled with an equilibrium mixture fraction – probability density function

158

model, where the instantaneous thermochemistry state of the fluid system is related to a conserved scalar quantity known

159

as the mixture fraction:

160 161

𝑓=𝑍

𝑍𝑖 ‒ 𝑍𝑖,𝑜𝑥

(7)

𝑖,𝑓𝑢𝑒𝑙 ‒ 𝑍𝑖,𝑜𝑥

In this model, the transport equations of density-averaged mixture fraction and its variance are solved as: ∂ (𝜌𝑓 ) + ∇ ∙ ∂𝑡

162

(𝜌𝑢𝑓 ) = ∇ ∙

∂ ∂𝑡

(𝜌𝑓'2 ) + ∇ ∙ (𝜌𝑢𝑓'2 ) = ∇ ∙

163

(

(

𝜇𝑙 + 𝜇𝑡

𝜇𝑙 + 𝜇𝑡 𝜎𝑡

)

(8)

∇𝑓 + 𝑆𝑚

𝜎𝑡

'2

∇𝑓

) + 𝐶 𝜇 ∙ (∇𝑓) ‒ 𝐶 𝜌 𝑓 2

𝑔 𝑡

𝜀 '2 𝑑 𝑘

(9)

'

164

Where 𝑓 = 𝑓 ‒ 𝑓. The model values for the constants 𝜎𝑡, 𝐶𝑔 and 𝐶𝑑 are 0.85, 2.86, and 2.0, respectively.

165

During the simulation process, the mixture fraction distribution is obtained directly by solving Eq. (8) and Eq. (9),

166

and then the values of mass fraction of each species, density and temperature can be obtained accordingly as Eq. (10): 1

167 168 169 170

𝜙𝑖 = ∫0𝜙𝑖(𝑓,𝐻)𝑝(𝑓)𝑑𝑓

(10)

2.3.3.2 Char oxidation To model char oxidation, a heterogeneous reaction is assumed to occur on char surface with first-order global Arrhenius rates, as listed in following reaction (I):

171

𝐶ℎ𝑎𝑟 + 0.5𝑂2→𝐶𝑂

(I)

172

𝐶𝑂 + 0.5𝑂2→𝐶𝑂2

(II)

8

ACCEPTED MANUSCRIPT 173

The rate of char combustion is described with the kinetic-diffusion single-film approach, which can be written as: 𝑑𝑚𝑝

174 175

𝑑𝑡

2

𝐷0 = 2.53 × 10 ‒

177

ℛ = 𝐶2𝑒

180

2.3.4 Heat transfer model

185 186

𝑅𝑇

×

[(𝑇𝑝 + 𝑇∞) 2]

(12)

𝑑𝑝

)

𝑝

(13)

1

2

3

(14)

𝑞𝑟 =‒ 3(𝑎 + 𝜎 ) ‒ 𝐶𝜎 ∇𝐺 𝑠

𝑠

Where the incident radiation 𝐺 can be determined by Eq. (15): ∇∙

((

) ‒ 𝑎𝐺 + 4𝑎𝑛 𝜎𝑇 = 0

∇𝐺

2

4

(15)

3 𝑎 + 𝜎𝑠) ‒ 𝐶𝜎𝑠

The emissivity of gas mixture is represent by the Weighted Sum of Gray Gases Model (WSGGM), in which the gas mixture is treated as a gray body. The total emissivity and absorption coefficient are described as following:

187

𝜀 = ∑𝑖 = 0𝑎𝜀,𝑖(𝑇)(1 ‒ 𝑒

188

𝑎𝜀,𝑖 = ∑𝑗 = 1𝑏𝜀,𝑖,𝑗𝑇

189

0.75

The P-1 model [39] is used to model the radiation heat transfer, in which the radiation heat flux 𝑞𝑟 is calculated as:

182

184

(

𝐸

‒7

2

respectively, as recommended in ref [38].

183

(11)

The pre-exponential factor 𝐶2 and the activation energy 𝐸 are 4.97 × 10 𝑘𝑔/(𝑚 ∙ 𝑠) and 8.54 × 10 𝑗/𝑚𝑜𝑙

179

181

𝑀𝑤,𝑜𝑥 𝐷𝑜 + ℛ

Where the diffusion rate coefficient 𝐷𝑜 and kinetic rate coefficient ℛ is defined as Eq. (12) and Eq. (13):

176

178

𝜌𝑅𝑇∞𝑌𝑜𝑥 𝐷𝑜ℛ

=‒ π𝑑𝑝

𝐼

𝐽

𝑗‒1

‒ 𝜅𝑖𝑝𝑠

)

(16) (17)

2.3.5 Consideration of moisture content

190

As was reported in open literatures that mentioned in the introduction part, MC has great effects on the combustion

191

performance of coal particles. So it is of great importance to take the moisture content into consideration in the simulation

192

work. In this paper, moisture content in brown coal was specially considered by specifying the species of volatile products

193

and liquid water when defining the coal inlet boundary condition. When heated up, the moisture inside coal particles will

194

firstly evaporates and then the devolatilization process begins, leaving the char and ash component in coal particles. 9

ACCEPTED MANUSCRIPT 195

According to the research of Bradley et al [40], the devolatilization process was finished in two steps. After the evaporation,

196

the tar component and primary volatiles were released from coal particles at first, then the tar species evolved into soot and

197

secondary volatiles. The whole process and mass fraction of each volatile species were calculated and clearly illustrated in

198

the following Fig.2.

199

The gas flow filed equations were firstly solved assuming that the coal particles were absent, which converged after

200

less than 2000 iterations. Based on the cold flow calculations, the coal combustion simulations were then carried out. The

201

convergence criterion was achieved when residuals of all parameters were below 10-5.

202

2.4 Mesh independence test and models validation

203

Predictably, a successive refinement of the mesh system will take us asymptotically towards the correct solution [41].

204

However, the computing cost increases correspondingly when the mesh system is refined. In order to make a balance

205

between the calculation accuracy and the computing cost, mesh independency is checked before the formal calculation. It

206

is conducted within four mesh systems, containing 3.27 million (#1), 3.92 million (#2), 4.53 million (#3) and 5.09 million

207

(#4) hexahedral cells respectively. Due to the relatively high flow gradient and combustion intensity in MBs’ region, mesh

208

refinement is mainly performed here. As shown in Fig.3, the distribution profile of area-weighted average velocity in MBs’

209

region was selected as the criterion of mesh quality because of its great influence on the mixing behavior and combustion

210

performance [29]. When compared with coarse mesh system #1 and #2, the velocity difference between fine mesh system

211

#3 and #4 is very small, especially in the dotted frame area. Thus we can assume that the accuracy of solution is not mesh-

212

dependent anymore when mesh system was further refined from #3 to #4 [42]. Therefore the #3 mesh system is selected

213

in the following simulation work presented.

214

The validation of this simulation model was ensured through comparing the simulation results with reference data.

215

Since backflow phenomenon may occur at the domain exit in the simulation process, parameters at the hypothetical furnace

216

exit, denoted as the data reference plane in Fig.1a, were selected to validate the model. As listed in Table 4, the superscript 10

ACCEPTED MANUSCRIPT 217

a presented the real-life data provided by Shangdu power plant, which were measured online when the boiler was operated

218

under extremely large primary air ratio, i.e. case 10 in this paper. Due to the slight fluctuation of online measured parameters,

219

the values presented was the average of data acquired in a long term operation. The flue gas temperature was selected

220

because it reflected the combustion performance and heat transfer process inside the furnace, and the velocity was selected

221

due to its great effects on the rear convective heating surfaces in real boiler operation, air preheater for instance. The

222

superscript b denoted the results calculated on the basis of element conservation, when the boiler was operated under design

223

case 1. For example, the mass of H2O was calculated as the summation of H2O(g) converted from the element H and those

224

evaporated from the moisture content, then it was divided by the total flus gas amount to obtain the H2O mass fraction.

225

Since H2O(g) was included in the total flue gas amount, the mass fraction of O2, H2O, CO2 presented in Table 4 was on a

226

wet basis. As can be seen that the discrepancy between CFD results and reference data is small (with 5%), so that the

227

selected models were quite acceptable.

228

On the basis of mesh independence test and model validation, a level of confidence in the current CFD model can be

229

established.

230

3. Results and discussion

231

When brown coal with higher MC is used, the pulverized coal particles cannot be heated to the design temperature,

232

even if PAR was increased to raise the drying capacity in the mill system. Thus, the temperature of primary air / pulverized

233

coal mixture (PA/PC) decreases in large PAR scenarios. According to the feedback of Shangdu power plant, the

234

temperature of PA/PC that enters the furnace through MBs is reduced to 331K, where it was designed to be 341K.

235

Meanwhile, the actual boiler thermal load is about 620MW which was expected to be 660MW. Hence, the effects of PA/PC

236

temperature on coal combustion behavior and boiler performance were examined before the influence of PAR was

237

conducted.

238

As shown in Table 5, with PA/PC temperature increasing from 328K to 343K, the flue gas temperature at the 11

ACCEPTED MANUSCRIPT 239

hypothetical furnace exit increases about 0.32% while the concentration of unburned char particles (UCPs) decreases by

240

0.74%. Meanwhile, the overall radiative heat flux on all heating surfaces is increased by 0.67%. It can be concluded that

241

when PA/PC temperature is increased in a small range, the combustion behavior and boiler performance are improved very

242

slightly. However, the insignificant difference of these parameters means that the PA/PC temperature is not the main cause

243

of boiler thermal load reduction. Therefore, the following parts are focused on the effects of increased PAR.

244

3.1 Combustion temperature distribution

245

3.1.1 Temperature distribution contour on the vertical and horizontal cut

246

Fig.4 and Fig.5 represents the temperature distribution contour on the vertical cut at Z=0 and on the horizontal cut at

247

Y=8.93m respectively. We can see from Fig.4 that the temperature distribution patterns are basically the same for all cases.

248

In the ash hopper zone, the temperature is very low as less coal particles is combusted here [32]. As shown in Fig.5, the

249

coal combustion occurs mainly on a tangential circle, formed by the combined effects of the impact extrusion of gas flow,

250

restriction from FW, the jet entrainment and the centrifugal force [43], the temperature in the near wall region is much

251

higher than that in the central zone. Above SOFA region, the temperature decreases gradually along the furnace height.

252

This is because the heat absorbed by FW is larger than the heat released from coal combustion, as the combustion fraction

253

decreases along the furnace height.

254

Taking the furnace as a whole, as Fig.4 depicts, the combustion temperature decreases gradually with PAR increasing.

255

However, the temperature variation is different in MBs’ region and the region above SOFA. In MBs’ region, with PAR

256

increasing continuously, the high temperature zone decreases at first and then goes up again slightly. On the contrary, as

257

indicated by the red dash line, the area size of high temperature zone above SOFA region increases when PAR is slightly

258

increased and then decreases step by step when PAR exceeds a certain value, 0.425 in this paper. This can be interpreted

259

as, when PAR is increased moderately, the combustion behavior in MBs’ region deteriorates and more unburned particles

260

are then consumed above SOFA region. So that the high temperature zone decreases in MBs’ region and increases above 12

ACCEPTED MANUSCRIPT 261

SOFA region. However, when PAR is further increased, the combustion performance gets improved somehow in MBs’

262

region, so that the temperature increase slightly in MBs’ region and decreases above SOFA region. Nevertheless, as shown

263

in Fig.5, although the temperature level shows a re-increase trend when PAR is overly increased, the high temperature zone

264

is spread on the furnace wall, which will result in undesired problem, like slagging and high temperature corrosion on the

265

water wall tubes.

266

3.1.2 Average temperature distribution profile along the furnace height

267

Fig.6 shows the mass-weighted average temperature distribution on the horizontal cross-section along the furnace

268

height. Owing to the alternant input of low temperature PA and SA, the average temperature profile fluctuates in MBs’

269

region. We can see that the variation of average temperature is different when PAR is in the range from 0.325 to 0.425 and

270

the range from 0.450 to 0.550. In MBs’ region, when PAR is below 0.425, the average temperature decrease evidently with

271

PAR increasing. For instance, the temperature difference between case 1 and case 5 is 144.3K at Y=16m. However, when

272

PAR continues to rise from case 6 to case 10, the temperature in MBs’ region remains stable. As the near wall temperature

273

is much higher than that in the central zone, when PAR is moderately increased from case 1 to case 5, the influence of

274

temperature decrease in the near wall region is greater than the temperature increase in central zone, so that the average

275

temperature decreases gradually. However, in case 6 to 10, the modest increase of near wall temperature is neutralized by

276

the temperature decrease in the central zone, so that the average temperature remains almost unchanged. Above SOFA

277

region, the average temperature increases from case 1 to 5, and then decreases from case 6 to 10. For example, the

278

temperature difference between case 6 and 10 is 51.6K at Y=35m. This can be attributed to that the size of high temperature

279

zone increases gradually from case 1 to case 5, as was shown in Fig.4, and then decreases from case 6 to 10.

280

The data shown in Fig 6 are used to calculate the average temperature in the intensive combustion region, where Y

281

ranges from 5 to 20m, for each case. Then the average temperature difference between case 1 and other cases is obtained

282

and shown in Table 6. We can find that when PAR exceeds 0.375, the average temperature in this region is reduced by at 13

ACCEPTED MANUSCRIPT 283

least 49K when compared with case 1. As the radiative intensity is in proportional to the fourth power of temperature, the

284

temperature decrease in this region will notably deteriorate the overall heat transfer process, as will be shown in Fig.7

285

3.1.3 Mechanisms of how increased PAR affects the combustion temperature

286

To sum up, the combustion temperature inside the furnace shows a parabolic variation trend with PAR increasing, but

287

how the increased PAR affects the in-furnace combustion performance still remains unclear. Thus, three possible

288

mechanisms for this phenomenon are discussed in detail as following.

289

(1) Difference in total air energy input. With PAR increasing, the secondary air ratio decreases correspondingly. Since

290

primary air temperature is lower than that of SA, the total energy input carried by air is thus reduced. For wet air, the

291

specific enthalpy can be calculated by temperature and moisture content as Eq. (18): 𝐼 = (1.01 + 1.84𝑑)(𝑇𝑎𝑖𝑟 ‒ 273.15) + 2500𝑑

292

(18)

293

According to above Eq. (18), primary air and secondary air enthalpy is calculated to be 80.32𝑘𝑗/𝑘𝑔 and 420.08𝑘𝑗/𝑘𝑔

294

respectively. Then the total enthalpy input carried by air is calculated as the mass-weighted summation of primary air and

295

secondary air flow as:

296

𝑄𝑎𝑖𝑟 = 𝑞𝑚,𝑎𝑖𝑟 ∙ [𝐼𝑃𝐴 ∙ 𝑃𝐴𝑅 + 𝐼𝑆𝐴(1 ‒ 𝑃𝐴𝑅 ‒ 0.2)]

(19)

297

The total air enthalpy 𝑄𝑎𝑖𝑟 under each cases are calculated and presented in Table 2. For the worst combustion case 5,

298

the decrement of 𝑄𝑎𝑖𝑟 is 0.266x105𝑘𝑗/𝑠 when compared with the design case 1. Meanwhile, the energy of brown coal fed

299

into the furnace is 2.02x106𝑘𝑗/𝑠. The reduction of 𝑄𝑎𝑖𝑟 is only 1.30% of the total energy input, which means it cannot be

300

the main cause of the lower furnace temperature and poor combustion performance in large PAR scenarios. Besides, 𝑄𝑎𝑖𝑟

301

decreases monotonously with the increase of PAR, which cannot explain the temperature increase in the near wall region

302

under cases with extremely large PAR.

303 304

(2) Momentum ratio of primary air to secondary air. The momentum of primary air flow and secondary air flow is calculated as Eq. (20) and Eq. (21), respectively. 14

ACCEPTED MANUSCRIPT

305

𝑃𝑃𝐴 = 𝑞𝑚,𝑎𝑖𝑟 ∙ 𝑃𝐴𝑅 ∙ 𝑣𝑃𝐴

(20)

𝑃𝑆𝐴 = 𝑞𝑚,𝑎𝑖𝑟 ∙ (1 ‒ 𝑃𝐴𝑅 ‒ 0.2) ∙ 𝑣𝑆𝐴

(21)

Then the momentum ratio between primary air flow and secondary air flow is calculated as: 𝑃𝑃𝐴

306

𝑣𝑃𝐴

𝑃𝐴𝑅

𝑃𝑆𝐴 = 1 ‒ 𝑃𝐴𝑅 ‒ 0.2 ∙ 𝑣

𝑆𝐴

(22)

307

According to the research of Ahmed et al [44], the velocity ratio between primary fuel stream and secondary air stream

308

plays an important role in the mixing process, and the combustion performance depends largely on the mixing process of

309

coal and supplementary air [42][45]. Therefore when the momentum of PA and SA is too close, the mixing and combustion

310

of pulverized coal becomes worse. The momentum ratio

311

explain the change process of combustion temperature mentioned above. From case 1 to 5, the momentum ratio changes

312

towards 1, indicating that the momentum of PA and SA is getting close. Correspondingly, the high temperature zone shown

313

in Fig.4 decreases gradually. While from case 6 to 10, the momentum ratio gets away from 1, which means the momentum

314

difference of PA and SA is enlarged, so that the temperature in the near wall region goes up again slightly.

𝑃𝑃𝐴

𝑃𝑆𝐴 is calculated and listed in Table 2, which can be used to

315

(3) Pulverized coal concentration and supplementary air. In fact, the momentum difference is also great in cases with

316

extremely large PAR, like case 9 and case10, but the combustion temperature is still at a relatively low level. This is because

317

the overly increased PAR lowers the concentration of pulverized coal in primary fuel stream. In these cases, per unit mass

318

of coal particles is surrounded by more low temperature PA, so that more heat is needed to heat up coal particles before

319

the ignition and combustion process. So that the combustion performance is still not as good as the design case, even if the

320

mixing process is improved.

321

3.2 Heat flux distribution

322

3.2.1 Heat flux spatial distribution contour on the furnace wall

323

To generate steam with high temperature and high pressure, the heat released from coal combustion is absorbed by

324

the working medium inside the water tubes located at FW and other heating surfaces. Therefore, the heat flux distribution 15

ACCEPTED MANUSCRIPT 325

on these heating surfaces will notably affect the overall boiler efficiency. Fig.7 depicts the spatial distribution contour of

326

heat flux on FW, which represents the intensity of the heat transfer process. The negative values mean that FW absorbs

327

heat from the high temperature flues gas. The spatial distribution of heat flux on FW is asymmetric due to the burners are

328

installed away from the centerline of FW. Since the high temperature zone is primarily located in the mid part of the

329

furnace, Y ranges from 0 to 25m, the heat flux intensity is much higher in this region. As the figure depicts, the most

330

intensive heat transfer process occurs in the design firing case 1. With the increase of PAR, the heat transfer intensity

331

decreases gradually at first. However, when PAR exceeds 0.425, the heat flux on FW increases again slightly, but still not

332

as high as case 1 and 2.

333

The variation of heat flux intensity under different cases is consistent with the temperature distribution shown in Fig.4,

334

as the radiation intensity is proportional to the fourth power of the combustion temperature. The high temperature zone in

335

the near wall region decreases obviously from case 1 to 5 and then scales up again slightly from case 6 to 10 (Fig.4), so

336

that the heat transfer intensity enlarges in a small range after an initial rapid decrease. In pulverized coal boiler, the radiation

337

is absolutely dominant in the heat transfer process [43][46]. Therefore the reduction in heat transfer intensity will decrease

338

the amount of heat absorbed by the water wall tubes, as discussed in the following paragraph.

339

3.2.2 Variation of radiative heat flux on all heating surfaces

340

The following Fig.8 presents the variation of radiative heat flux on different heating surfaces, including FW, PSH and

341

RSH, where ALL denotes the sum of all these three parts. It’s noteworthy that each individual part represents a surface

342

group. For instance, the FW denotes a surfaces group, consisting of surfaces that covers from the bottom to the top of the

343

furnace on the four side walls. From Fig.8 we can see that with PAR increasing, the radiative heat flux on FW decrease at

344

first and then increases, the minimum value is 427.1MW when PAR is 0.425. However, the change of radiative heat flux

345

on PSH and RSH is exactly the opposite. As the figure depicts, the total radiation heat flux is reduced by 5.78%, from

346

609.1MW to 573.9MW, which is in conformity with the reality. Although the radiation heat flux on FW rise again when 16

ACCEPTED MANUSCRIPT 347

PAR exceeds 0.425, the overall radiative heat flux remains stable after an initial rapid reduction. This is due to the increase

348

of radiative heat flux on FW is counteracted by the decrease of it on PSH and RSH.

349

The variation of heat flux on these heating surfaces is identical with the temperature distribution shown in above

350

Fig.4, where the temperature above SOFA region decreases after an initial increase, and the temperature in the near wall

351

region decrease at first and then goes up again. As majority of the heat released from coal combustion is designed to be

352

absorbed by water wall tubes located on FW, the decreases of heat flux on FW will result in an obvious decrement of total

353

heat absorption, and thus lowers the boiler efficiency. Meanwhile, the increase of heat flux on PSH and RSH may lead to

354

an over-temperature on the heat absorbing tubes of PSH and RSH. In some extra cases, the severe over-temperature of

355

tubes will result in tube failure and even unplanned boiler shut down [47][48].

356

3.3 Distribution of oxygen and carbon oxide

357

The distribution profile of O2 and CO mass fraction under different cases are plotted in Fig.9 and Fig.10, respectively.

358

The residual O2 reflects the utilization efficiency of oxidant, and the CO mass fraction can be used as an effective criteria

359

for the coal combustion sufficiency. Due to the intensive O2 consumption and newly supply of fresh air, O2 mass fraction

360

in Fig.9 shows several peaks and valleys in MBs’ region. In the SOFA region, O2 mass fraction firstly increases due to the

361

input of separated over fire air, and then remains at a relatively high level since the combustion intensity decreases above

362

the SOFA region. For CO mass fraction, we can see from Fig.10 that it is relatively high in MBs’ region, because the

363

combustion here is intensive and the oxidant is in a low level. In the SOFA region, CO content decreases gradually and

364

reaches to a very low level in the furnace roof region. This can be explained as the input of fresh air and the consumption

365

of CO along the furnace height.

366

From Fig.9, we can see that O2 mass fraction increases gradually when PAR varies from 0.325 to 0.425, and then

367

decreases gradually when PAR is in the range from 0.45 to 0.55. It means the oxidant utilization becomes worse when PAR

368

is increased from case 1 to case 5, and then the utilization efficiency gets better again from case 6 to 10. Similar conclusion 17

ACCEPTED MANUSCRIPT 369

can be obtained from CO mass fraction profile. As Fig.10 shows, CO content increases gradually at first with PAR

370

increasing, and thereafter decreases when PAR exceeds 0.425. This can be explained as the coal combustion gets worse at

371

first when PAR is slightly increased and after that, the combustion gets improved again.

372

We can find that the temperature variation shown in Fig.4 matches well with the distribution profile of O2 and CO

373

mass fraction depicted in Fig.9 and Fig.10. As shown in case 1 to 5, when combustion process becomes worse, the oxidant

374

utilization gets worse and CO content increases, thus the combustion temperature decreases correspondingly. On the

375

contrary, when the combustion gets better in case 6 to 10, the O2 and CO content decreases and the combustion temperature

376

arises again. Detailed reason of why O2 and CO shows such a variation trend with PAR increasing has been presented

377

previously in above section 3.1.3.

378

3.4 Unburned char particles

379

3.4.1 Mass fraction distribution of unburned char particles

380

As was reported [8][11], the release and combustion of volatile matters gets started and finished quickly in the vicinity

381

of the burners, so that the mass concentration of unburned char particles (UCPs) is selected to represent the utilization of

382

fuel. Fig.11 shows the contour of UCPs’ concentration in the very middle of MBs’ region (Y=8.93m). As the figure depicts,

383

UCPs are predominantly concentrated at the tangential circle formed in the furnace. With PAR increasing, the concentration

384

of UCPs increases gradually at first and then decreases slightly, but still maintains at a very high level. The variation of

385

UCPs’ concentration coincides well with the distribution of temperature, O2 and CO content discussed above, as the

386

combustion efficiency of char particles determines the utilization of O2, and thus affects the combustion temperature level

387

and CO generation process.

388

3.4.2 Unburned char particles at the furnace exit

389

As the parameters in MBs’ region cannot fully reflect the overall combustion performance inside the furnace, the

390

variation of UCPs’ concentration at the hypothetical furnace exit, denoted as data reference plane in Fig.1a, is illustrated 18

ACCEPTED MANUSCRIPT 391

in Fig.12. As can be seen, the concentration of UCPs at the hypothetical furnace exit increases slightly when PAR is

392

increased from 0.325 to 0.45, and then enlarges obviously when PAR varies from 0.45 to 0.55. As described in section

393

3.1.1, when PAR is increased in a small range, coal combustion deteriorates in MBs’ region, but the unburned coal particles

394

are then burned above SOFA region, so that the increase of UCPs’ concentration is not evident. However, when PAR is

395

further increased, the overall combustion performance continuously to deteriorate, even if the combustion process in MBs’

396

region gets improved slightly. Therefore, more coal particles leave the furnace exit without being burned, resulting in an

397

obvious increase of UCPs’ concentration.

398

The elevation of UCPs’ concentration diminishes the utilization of fuel energy, thus the combustion temperature

399

decreases and the heat transfer intensity is weaken in those cases with high UCP s’ concentration, as shown in Fig.4 and

400

Fig.7. In addition, the increase of UCPs’ concentration will inevitably augments the amount of fly ash. The increase of fly

401

ash content will cause a severe deposition on the following convective heating surfaces and jeopardizes the overall heat

402

transfer coefficient, due to its low thermal conductivity of ash deposition layer [49][50]. In some extra situation, the fly ash

403

deposition may result in an unplanned shutdown of the boiler units [51].

404

4. Conclusions

405

In this paper, a three dimensional CFD model was established based on a 660MW wall-fired pulverized coal boiler.

406

Confidence in the model was obtained by carrying out the mesh independence test and the validation against real life data

407

and theoretical calculations. Then it was used to simulate 10 cases where PAR varies from the design value 0.325 to the

408

actual operational value 0.55. The temperature, heat flux distribution, O2 mass fraction, CO mass fraction and UCPs’

409

concentration were selected to analyze the effect of PAR on the combustion performance. From the above results and

410

discussion, some particular conclusions can be drawn:

411

1.

412

A slight decrease of PA/PC temperature has very little influence on coal combustion performance inside the furnace and the overall boiler efficiency. 19

ACCEPTED MANUSCRIPT 413

2.

The increase of PAR has a great influence on the combustion performance. As a whole, the combustion process

414

deteriorates with the increase of PAR. However, in MBs’ region and the region above SOFA, the combustion

415

characteristics show a parabolic trend with PAR increasing.

416

3.

The reduction of total air energy input is not the main cause of the combustion behavior deterioration, since it accounts 𝑃𝑃𝐴

417

for only 1.30% of the total energy input. The variation of

418

degradation, due to its great effects on the mixing and combustion process.

419

4.

𝑃𝑆𝐴 is the main cause of the boiler performance

In cases with extremely large PAR, the reduction of pulverized coal concentration and the increase of ignition heat

420

constrain the improvement of combustion behavior. So that the combustion performance in cases with extremely large

421

PAR is still not as good as the design firing case.

422

Based on this research, it is suggested that the operation condition, where the momentum of PA and SA is too close

423

to each other, should be avoided, since the combustion performance under such conditions is the worst. A feasible solution

424

is proposed to solve the problem caused by the increase of moisture content in brown coal boiler. That is to raise the

425

temperature of PA that enters the mill system, to meet the increasing demand of drying capacity. In this way, PAR remains

426

at the design value and the reduction of boiler efficiency and boiler thermal load caused by increased PAR can be avoided.

427

Acknowledgements

428 429

This work was supported by the Technology Research Program of China Huaneng Group (Contract No. HNBFKJ2014-SC-05). Shangdu power plant is gratefully acknowledged for providing the real operational data. Nomenclature

𝑀𝑤,𝑜𝑥

molecular weight of oxidant

Abbreviation

𝑛

refractive index of the medium

CFD

computational fluid dynamics

𝑃𝑃𝐴

momentum of primary air flow

FW

furnace wall

𝑃𝑆𝐴

momentum of secondary air flow

MB

main burner

𝑃𝑃𝐴

MC

moisture content

PA

primary air

𝑄𝑎𝑖𝑟

total air energy input

primary air ratio

𝑞𝑚,𝑎𝑖𝑟

total mass flow rate of air

PAR

𝑃𝑆𝐴

momentum ratio between primary air and secondary air flow

20

ACCEPTED MANUSCRIPT PA/PC

primary air / pulverized coal mixture

𝑅

universal gas content

PPE

power plant efficiency

ℛ1

devolatilization rate at low temperature range

PSH

platen super-heater

ℛ2

devolatilization rate at high temperature range

RSH

rear super-heater

𝑆

generalized source term

SA

secondary air

𝑇𝑎𝑖𝑟

temperature of wet air, K

SOFA

separated over fire air

𝑇𝑝

particle temperature

UCP

unburned char particle

𝑢

fluid phase velocity

𝑢𝑝

velocity of discrete phase particle

Symbol 𝑎

absorption coefficient

𝑎𝜀,𝑖

'

velocity fluctuation value

emissivity weighting factor of 𝑖th gray gas

𝑢 (𝑡) 𝑣𝑃𝐴

𝑏𝜀,𝑖,𝑗

emissivity gas temperature polynomial coefficients

𝑣𝑆𝐴

secondary air velocity

𝐶

linear-anisotropic phase function coefficient

𝑌𝑜𝑥

mass fraction of oxidant

𝐶𝐷

drag coefficient

𝑍𝑖

mass fraction for element 𝑖

𝑐𝑝

specific heat capacity

𝑍𝑖,𝑓𝑢𝑒𝑙

mass fraction at fuel stream inlet

𝑑

moisture content in wet air

𝑍𝑖,𝑜𝑥

mass fraction at oxidizer stream inlet

𝑑𝑝

diameter of discrete phase particle

𝛼1

yield factor at low temperature range

𝑓

instantaneous mixture fraction

𝛼2

yield factor at high temperature range

𝑓

mean mixture fraction

Γ

generalized diffusion coefficient

𝑓

mean mixture fraction variance

𝜀

turbulence dissipation rate

𝑔

gravitational acceleration constant

𝜅𝑖

absorption coefficient of the 𝑖th gray gas

𝐻

mean enthalpy

𝜇

dynamic viscosity

𝐼

specific enthalpy of wet air

𝜇𝑙

laminar viscosity

𝐼𝑃𝐴

enthalpy of primary air

𝜇𝑡

turbulent viscosity

𝐼𝑆𝐴

enthalpy of secondary air

𝜌

fluid phase density

𝑘

turbulence kinetic energy

𝜌𝑝

density of discrete phase particle

𝑘𝑓

heat transfer coefficient

𝜎

Stefan-Boltzmann constant

𝑚𝑎

mass of ash content in the particle

𝜎𝑠

scattering coefficient

𝑚𝑝,0

initial particle mass

𝜙

universal variable

𝑚𝑣(𝑡)

volatile yield up to time 𝑡

𝜙𝑖

mean value of species mass fraction, density, etc.

'2

primary air velocity

430

References

431

[1] Yu JL, Tahmasebi A, Han YN, Yin FK, Li XC. A review on water in low rank coals: The existence, interaction with

432

coal structure and effects on coal utilization. Fuel Process Technol 2013;106:9–20. doi:10.1016/j.fuproc.2012.09.051.

433

[2] Liu M, Yan JJ, Chong DT, Liu JP, Wang JS. Thermodynamic analysis of pre-drying methods for pre-dried lignite-

434

fired power plant. Energy 2013;49:107–18. doi:10.1016/j.energy.2012.10.026.

21

ACCEPTED MANUSCRIPT 435

[3] Wang HM, You CF. Experimental Investigation into the Spontaneous Ignition Behavior of Upgraded Coal

436

Products. Energy fuels 2014;28;2267-71. doi:10.1021/ef402569s.

437

[4] Han XQ, Liu M, Wu KL, Chen WX, Xiao F, Yan JY. Exergy analysis of the flue gas pre-dried lignite-fired power

438

system based on the boiler with open pulverizing system. Energy 2016;106:285–300. doi:10.1016/j.energy.2016.03.047.

439

[5] Gao XZ, Man CB, Hu SJ, Xu XY, Che DF. Theoretical and Experimental Study on Spontaneous Ignition of Lignite

440

during the Drying Process in a Packed Bed. Energy & Fuels 2012;26:6876–87. doi:10.1021/ef3012239.

441

[6] Rao ZH, Zhao YM, Huang CL, Duan CL, He JF. Recent developments in drying and dewatering for low rank coals.

442

Prog Energy Combust Sci 2015;46:1–11. doi:10.1016/j.pecs.2014.09.001.

443

[7] Katalambula H, Gupta R. Low-grade coals: A review of some prospective upgrading technologies. Energy and

444

Fuels 2009;23:3392–405. doi:10.1021/ef801140t.

445

[8] Taseska V, Markovska N, Causevski A, Bosevski T, Pop-Jordanov J. Greenhouse gases (GHG) emissions reduction

446

in a power system predominantly based on lignite. Energy 2011;36:2266–70. doi:10.1016/j.energy.2010.04.010.

447

[9]

448

of Victorian brown coals. Energy and Fuels 2013;27:6598–606. doi:10.1021/ef401649j.

449

[10]

450

the thermal efficiency and environmental emission of a gas-turbine cycle. Appl Therm Eng 2017;125:118–33.

451

doi:10.1016/j.applthermaleng.2017.06.120.

452

[11] Tahmasebi A, Zheng HL, Yu JL. The influences of moisture on particle ignition behavior of Chinese and Indonesian

453

lignite coals in hot air flow. Fuel Process Technol 2016;153:149–55. doi:10.1016/j.fuproc.2016.07.017.

454

[12] Binner E, Zhang L, Li CZ, Bhattacharya S. In-situ observation of the combustion of air-dried and wet Victorian

455

brown coal. Proc Combust Inst 2011;33:1739–46. doi:10.1016/j.proci.2010.07. 076.

Stokie D, Woo MW, Bhattacharya S. Comparison of superheated steam and air fluidized-bed drying characteristics

Tahmasebzadehbaie M, Sayyaadi H, Sohani A, Pedram MZ. Heat and mass recirculations strategies for improving

22

ACCEPTED MANUSCRIPT 456

[13] Prationo W, Zhang J, Cui JF, Wang YT, Zhang L. Influence of inherent moisture on the ignition and combustion of

457

wet Victorian brown coal in air-firing and oxy-fuel modes:Part 1:The volatile ignition and flame propagation. Fuel

458

Process Technol 2015;138:670–9. doi:10.1016/j.fuproc. 2015.07.008.

459

[14] Zeng DL, Hu Y, Gao S, Liu JZ. Modelling and control of pulverizing system considering coal moisture. Energy

460

2015;80:55–63. doi:10.1016/j.energy.2014.11.042.

461

[15] Tian ZF, Witt PJ, Schwarz MP, Yang W. Combustion of predried brown coal in a tangentially fired furnace under

462

different operating conditions. Energy and Fuels 2012;26:1044–53. doi:10.1021/ef2014887.

463

[16] Kurose R, Tsuji H, Makino H. Effects of moisture in coal on pulverized coal combustion characteristics 2001;80:2–

464

6. doi:10.1016/S0016-2361(01)00019-9.

465

[17] Osman H, Jangam S V., Lease JD, Mujumdar AS. Drying of Low-Rank Coal (LRC)-A Review of Recent Patents

466

and Innovations. Dry Technol 2011;29:1763–83. doi:10.1080/07373937.2011.616443.

467

[18] Nikolopoulos N, Violidakis I, Karampinis E, Agraniotis M, Bergins C, Grammelis P, et al. Report on comparison

468

among current industrial scale lignite drying technologies (A critical review of current technologies). Fuel 2015;155:86–

469

114. doi:10.1016/j.fuel.2015.03.065.

470

[19] Agraniotis M, Koumanakos A, Doukelis A, Karellas S, Kakaras E. Investigation of technical and economic aspects

471

of pre-dried lignite utilisation in a modern lignite power plant towards zero CO2 emissions. Energy 2012;45:134–41.

472

doi:10.1016/j.energy.2012.01.063.

473

[20] Liu M, Yan JJ, Bai BF, Chong DT, Guo XK, Xiao F. Theoretical Study and Case Analysis for a Predried Lignite-

474

Fired Power System. Dry Technol 2011;29:1219–29. doi:10.1080/07373937.2011.582559.

475

[21] Wang WC. Laboratory investigation of drying process of Illinois coals. Powder Technol 2012;225:72–85.

476

doi:10.1016/j.powtec.2012.03.034.

23

ACCEPTED MANUSCRIPT 477

[22] Xu C, Xu G, Fang YX, Zhou LY, Yang YP, Zhang DK. A novel lignite pre-drying system incorporating a

478

supplementary steam cycle integrated with a lignite fired supercritical power plant. Energy Procedia 2014;61:1360–3.

479

doi:10.1016/j.apenergy.2015.01.083.

480

[23] Liu M, Wu DY, Xiao F, Yan JJ. A novel lignite-fired power plant integrated with a vacuum dryer:System design

481

and thermodynamic analysis. Energy 2015;82:968–75. doi:10.1016/j.energy.2015.01.106.

482

[24] Tahmasebzadehbaie M, Sayyaadi H. Efficiency enhancement and NOx emission reduction of a turbo-compressor

483

gas engine by mass and heat recirculations of flue gases. Appl Therm Eng 2016;99:661–71.

484

doi:10.1016/j.applthermaleng.2016.01.095.

485

[25] Chen ZC, Li ZQ, Jing JP, Wei HD, Chen LZ, Wu SH, et al. Experiment Investigations on the Performance of a

486

Centrally Fuel Rich Swirl Coal Combustion Burner: Influence of Primary Air Ratio. Int J Chem React Eng 2008;6:1–19.

487

doi:10.2202/1542-6580.1682.

488

[26] Jing JP, Li ZQ, Zhu QY, Chen ZC, Ren F. Influence of primary air ratio on flow and combustion characteristics and

489

NOx emissions of a new swirl coal burner. Energy 2011;36:1206–13. doi:10.1016/j.energy.2010.11.025.

490

[27] Li ZQ, Li S, Zhu QY, Zhang XQ, Li GP, Liu Y, et al. Effects of particle concentration variation in the primary air

491

duct on combustion characteristics and NOxemissions in a 0.5-MW test facility with pulverized coal swirl burners. Appl

492

Therm Eng 2014;73:857–66. doi:10.1016/j.applthermaleng.2014.08.041.

493

[28] Sha L, Liu H, Jiao F, Cao QX, Xin N, Wu SH. The research of the influence of primary air ratio on the combustion

494

in a lignite-fired Ultra Supercritical boiler. Asia-Pacific Power Energy Eng Conf APPEEC 2009:1–5.

495

doi:10.1109/APPEEC.2009.4918904.

496

[29]

497

Loy Yang A brown coal power station. Fuel 2012;102:646–65. doi:10.1016/j.fuel.2012.06.028.

Al-Abbas AH, Naser J, Dodds D. CFD modelling of air-fired and oxy-fuel combustion in a large-scale furnace at

24

ACCEPTED MANUSCRIPT 498

[30] Smith TF, Shen ZF, Friedman JN. Evaluation of Coefficients for the Weighted Sum of Gray Gases Model. J Heat

499

Transfer 1982;104:602. doi:10.1115/1.3245174.

500

[31] Minier J-P. On Lagrangian stochastic methods for turbulent polydisperse two-phase reactive flows. Prog Energy

501

Combust Sci 2015;50:1–62. doi:10.1016/j.pecs.2015.02.003.

502

[32] Zhang DL, Meng CW, Zhang H, Liu PY, Li ZH, Wu YX, et al. Studies on heat flux distribution on the membrane

503

walls in a 600MW supercritical arch-fired boiler. Appl Therm Eng 2016;103:264–73.

504

[33] Dodds D, Naser J, Staples J, Black C, Marshall L, Nightingale V. Experimental and numerical study of the pulverised-

505

fuel distribution in the mill-duct system of the Loy Yang B lignite fuelled power station. Powder Technol 2011;207:257–

506

69. doi:10.1016/j.powtec.2010.11.007.

507

[34] Silaen A, Wang T. Effect of turbulence and devolatilization models on coal gasification simulation in an entrained-

508

flow gasifier. Int J Heat Mass Transf 2010;53:2074–91. doi:10.1016/j.ijheatmasstransfer.2009.12.047.

509

[35] Ren F, Li ZQ, Liu GK, Chen ZC, Zhu QY. Numerical simulation of flow and combustion characteristics in a 300

510

MWe down-fired boiler with different overfire air angles. Energy and Fuels 2011;25. doi:10.1021/ef101664m.

511

[36] H.Kobayashi, J.B.Howard, A.F.Sarofim. Coal devolatilization at high temperatures. Symp Combust 1977;16:411–

512

25. doi:10.1016/S0082-0784(77)80341-X.

513

[37] Sprouse KM, Schuman MD. Predicting Lignite Devolatilization with the Multiple Parallel and Two-Competing

514

Reaction Models. Combust Flame 1981;43:265–71.

515

[38] Wall, T F, Phelan, W J, Bartz S. Doc. F388/a/3. Int Flame Res Found 1976.

516

[39] J.H.Jeans. The equations of radiative transfer of energy. Mon Not R Astron Soc 1917;78:28–36.

517

[40] Bradley D, Lawes M, Park HY, Usta N. Modeling of laminar pulverized coal flames with speciated devolatilization

518

and comparisons with experiments. Combust Flame 2006;144:190–204. doi:10.1016/j.combustflame.2005.07.007.

25

ACCEPTED MANUSCRIPT 519

[41] Patankar S V., Spalding DB. A calculation procedure for heat, mass and momentum transfer in three-dimensional

520

parabolic flows. Int J Heat Mass Transf 1972;15:1787–806. doi:10.1016/0017-9310(72)90054-3.

521

[42] Ahmed S, Hart J, Nikolov J, Solnordal C, Yang W, Naser J. The effect of jet velocity ratio on aerodynamics of a

522

rectangular slot-burner in the presence of cross-flow. Exp Therm Fluid Sci 2007;32:362–74.

523

doi:10.1016/j.expthermflusci.2007.04.011.

524

[43] Yan LB, He BS, Yao F, Yang R, Pei XH, Wang CJ, et al. Numerical simulation of a 600 MW utility boiler with

525

different tangential arrangements of burners. Energy and Fuels 2012;26:5491–502. doi:10.1021/ef300929v.

526

[44] Ahmed S, Hart J, Naser J. The effect of jet velocity ratio on aerodynamics of rectangular slot-burners in

527

tangentially-fired furnaces. Third Int Conf CFD Miner Process Ind CSIRO, Melbourne, Aust 2003:41–6.

528

[45] Al-Abbas AH, Naser J, Hussein EK. Numerical simulation of brown coal combustion in a 550 MW tangentially-

529

fired furnace under different operating conditions. Fuel 2013;107:688–98. doi:10.1016/j.fuel.2012.11.054.

530

[46] Drosatos P, Nikolopoulos N, Agraniotis M, Kakaras E. Numerical investigation of firing concepts for a flexible

531

Greek lignite-fired power plant. Fuel Process Technol 2016;142:370–95. doi:10.1016/j.fuproc.2015.10.033.

532

[47] Reinaldo RF. Use of a CFD based numerical model to calculate heat transfer in boiler superheaters panels. 17th Int

533

Congr Mech Eng 2003.

534

[48] Purbolaksono J, Ahmad J, Beng LC, Rashid AZ, Khinani A, Ali AA. Failure analysis on a primary superheater tube

535

of a power plant. Eng Fail Anal 2010;17:158–67. doi:10.1016/j.engfailanal.2009.04.017.

536

[49] Akiyama K, Pak H, Takubo Y, Tada T, Ueki Y, Yoshiie R, et al. Ash deposition behavior of upgraded brown coal

537

in pulverized coal combustion boiler. Fuel Process Technol 2011;92:1355–61. doi:10.1016/j.fuproc.2011.02.016.

538

[50] Syrodoy S V., Kuznetsov G V., Gutareva NY, Salomatov V V. The efficiency of heat transfer through the ash

539

deposits on the heat exchange surfaces by burning coal and coal-water fuels. J Energy Inst 2017:1–11.

540

doi:10.1016/j.joei.2017.06.014. 26

ACCEPTED MANUSCRIPT 541

[51] Huang Q, Zhang YY, Yao Q, Li SQ. Numerical and experimental study on the deposition of fine particulate matter

542

during the combustion of pulverized lignite coal in a 25 kW combustor. Powder Technol 2017;317:449–57.

543

doi:10.1016/j.powtec.2017.03.009.

27

ACCEPTED MANUSCRIPT 544

Table 1. Physical properties of brown coal used in this simulation work. Proximate analysis (wt%, ar) Volatile

Ash

Moisture

C

H

O

N

S

(KJ/kg)

24.77

20.37

16.86

38.00

75.17

5.45

16.64

0.95

1.79

12120

ar, on a received basis, daf, on a dry ash-free basis, LHV represents the lower heating value

Table 2. Detailed information of velocity inlet boundary condition. Case

1

2

3

4

5

6

7

8

9

10

PAR

0.325

0.350

0.375

0.400

0.425

0.450

0.475

0.500

0.525

0.550

VPA (m/s)

25.9

27.9

29.9

31.9

33.8

35.8

37.8

39.8

41.8

43.8

VSA (m/s)

50.8

48.1

45.4

42.7

40.1

37.4

34.7

32.1

29.4

26.7

𝑄𝑎𝑖𝑟(x105kJ)

2.423

2.356

2.290

2.224

2.157

2.091

2.024

1.958

1.891

1.825

0.451

0.581

0.747

0.955

1.231

𝑃𝑃𝐴

555

LHVar

Fixed carbon

545 546 547 548 549 550 551 552 553

554

Ultimate analysis (wt%, daf)

0.349

𝑃𝑆𝐴

1.592

2.066

3.609

𝑄𝑎𝑖𝑟 represents the total air energy input, 𝑃𝑃𝐴 represents the momentum of primary air, 𝑃𝑆𝐴 represents the momentum of secondary air.

𝑃𝑃𝐴

𝑃𝑆𝐴 represents the momentum ratio between primary air and secondary air flow

556 557 558 559 560 561 562 563

2.714

Table 3. Specific meaning of 𝜙, Γ and 𝑆 in different governing equations. 𝜙

Γ

𝑆

Continuity equation

1

0

0

Momentum equation

𝑢𝑖

𝜇

Energy equation

𝑇

Turbulence kinetic energy

𝑘

𝑘𝑓 μ+

28

‒

𝑐𝑝

𝜇𝑡

𝜎𝑘

∂𝑝

∂𝑥𝑖 + 𝑆𝑖 𝑆𝑇

𝐺𝑘 ‒ 𝜌𝜀

ACCEPTED MANUSCRIPT Turbulence dissipation rate

μ+

𝜀

564

29

𝜇𝑡

𝜎𝑠

𝐶1𝜀𝐺 ε 𝑘 ‒ 𝐶 𝜌𝜀2 𝑘 2𝜀 𝑘

ACCEPTED MANUSCRIPT 565

566 567 568 569 570 571 572 573 574

Table 4. Comparison of CFD results and reference data. velocity (m/s)

temperature (K)

O2 mass fraction

H2O mass fraction

CO2 mass fraction

CFD results

10.7 a

1212 a

0.0492b

0.0895b

0.1885 b

Reference data

11.2a

1237a

0.0470b

0.0929b

0.1872 b

Relative discrepancy

4.46%

2.02%

4.68%

3.68%

0.69%

a.

represents the real-life data of actual unfavorable firing case 10, b. denotes the theoretical calculations of design

case 1, on a wet basis.

Table 5. Parameters at the furnace exit and the overall heat flux under different PA/PC temperature. PA/PC temperature (K)

328

335

343

flue gas temperature (K)

1216.8

1218.6

1220.7

0.539

0.537

0.535

609.4

611.2

613.5

UCPs’ concentration

(x10-2 kg/m3)

overall radiative heat flux (MW)

575 576 577 578 579 580 581 582

Table 6. Area-weighted temperature difference between design case 1 and other cases. Case

1

2

3

4

5

6

7

8

9

10

Temperature difference (K)

0

12.2

33.6

51.6

52.1

59.1

53.0

52.9

49.3

49.1

583

30

ACCEPTED MANUSCRIPT

(a) Geometric configuration of boiler

(b) Detailed installation information of burners and air nozzles

Fig.1. Schematic of the furnace and the arrangements of main burners and air nozzles

584

31

ACCEPTED MANUSCRIPT

Fig.2. Devolatilization model and product compositions for brown coal used (as received basis).

585

32

ACCEPTED MANUSCRIPT

Velocity Magnitude (m/s)

22

3.27M 3.92M 4.53M 5.09M

20

18

16 LMB region

IMB region

UMB region

14 0.0

2.5

5.0

7.5

10.0

12.5

15.0

Distance from the reference plane (m)

17.5

Fig.3. Velocity profile along the furnace height under different mesh systems

586

33

ACCEPTED MANUSCRIPT

Case 1

Case 3

Case 5

Case 6

Case 8

Case 10

Fig.4. Temperature distribution contour on the vertical cut at Z=0.

587

34

ACCEPTED MANUSCRIPT

Case 1

Case 3

Case 6

Case 8

Case 5

Case 10

Fig.5. Temperature distribution contour on the horizontal cut at fourth layer of burners at Y=8.93m.

588

35

Mass-weighted average temperature (K)

Mass-weighted average temperature (K)

ACCEPTED MANUSCRIPT

0.325 0.350 0.375 0.400 0.425

1650 1600 1550 1500 1450 1400 1350

SOFA region

MBs' region

1300

0

5

10

15

20

25

arch zone

30

35

40

Dsitance from the reference plane (m)

45

(a) PAR in the range from 0.325 to 0.425

0.450 0.475 0.500 0.525 0.550

1650 1600 1550 1500 1450 1400 1350 1300 0

SOFA region

MBs' region

5

10

15

20

25

arch zone

30

35

40

Dsitance from the reference plane (m)

(b) PAR in the range from 0.450 to 0.550

Fig.6. Mass-weighted average temperature distribution profile of horizontal cross-section along the furnace height.

589

36

45

ACCEPTED MANUSCRIPT

Case 1

Case 3

Case 5

Case 6

Case 8

Case 10

Fig.7. Contour of heat flux spatial distribution on furnace wall.

590

37

ACCEPTED MANUSCRIPT

Radiative Heat Flux (MW)

592 FW ALL PSH 100 RSH 90

600 585 570

80 50

465 450

45

435 0.35

0.40

0.45

0.50

0.55

40

Primary air ratio Fig.8. Variation of radiative heat flux on different heating surfaces.

593

38

ACCEPTED MANUSCRIPT

7

O2 mass fraction (%)

O2 mass fraction (%)

7

6

6

5

5

4

4 3 2 SOFA region

MBs' region

1 5

10

15

20

25

0.325 0.350 0.375 0.400 0.425

3 2

5

30

SOFA region

MBs' region

1

10

15

20

25

0.450 0.475 0.500 0.525 0.550 30

Dsitance from the reference plane (m)

Dsitance from the reference plane (m) (a) PAR in the range from 0.325 to 0.425

(b) PAR in the range from 0.450 to 0.550

Fig.9. Area-weighted average O2 distribution profile of horizontal cross-section along the furnace height.

594

39

ACCEPTED MANUSCRIPT

0.325 0.350 0.375 0.400 0.425

1.2

1.8

CO mass fraction (%)

CO mass fraction (%)

1.8

0.6

0.0

0

5

10

15

20

25

30

35

40

Dsitance from the reference plane (m)

0.450 0.475 0.500 0.525 0.550

1.2

0.6

0.0

45

0

5

10

15

20

25

30

35

40

45

Dsitance from the reference plane (m)

(a) PAR in the range from 0.325 to 0.425

(b) PAR in the range from 0.450 to 0.550

Fig.10. Area-weighted average CO mass fraction distribution profile of horizontal cross-section along the furnace height

595

40

ACCEPTED MANUSCRIPT

Case 1

Case 3

Case 5

Case 6

Case 8

Case 10

Fig.11. Distribution of UCPs’ concentration in the very middle of main burners’ region (Y=8.93m).

596

41

UCPs' concentration (x10-2kg/m3)

ACCEPTED MANUSCRIPT

0.568

0.560

0.552

0.544

0.536 0.30

0.35

0.40

0.45

0.50

0.55

Primary air ratio Fig.12. Variation of UCPs’ concentration at the hypothetical furnace exit under different PAR.

597

42

ACCEPTED MANUSCRIPT Highlights 

Effects of increased primary air ratio in a 660MW pulverized boiler were simulated.



Primary air ratio has great influence on coal combustion and boiler efficiency.



Mechanisms of how primary air ratio affects the boiler performance was discussed.



Situation where momentum of primary and secondary air is close should be avoided.



Suggestion is given to avoid the bad effects caused by increased primary air ratio.