ARID ZONE JOURNAL OF ENGINEERING, TECHNOLOGY & ENVIRONMENT
AZOJETE, June, 2019. Vol. 15(2):418-434

Published by the Faculty of Engineering, University of Maiduguri, Maiduguri, Nigeria.
Print ISSN: 1596-2490, Electronic ISSN: 2545-5818

www.azojete.com.ng

418

ORIGINAL RESEARCH ARTICLE

DETERMINATION OF MAIGANGA LIGNITE COAL COMBUSTION CHARACTERISTICS
FOR APPLICATION IN THERMAL POWER PLANT USING STANDARD MATHEMATICAL

MODELS

I. I. Ozigis* and M. T. Zarmai
(Department of Mechanical Engineering, Faculty of Engineering,University of Abuja, PMB 117 Abuja,

Kilometer 23, Airport Road, Abuja, Nigeria)
*Corresponding author’s e-mail address: idris.ozigi@uniabuja.edu.ng

ARTICLE INFORMATION

Submitted 29 March, 2018
Revised 20 April, 2019
Accepted 23 April, 2019

Keywords:
Coal, combustion
equivalence ratio
mathematical model
thermal power plant

ABSTRACT
This paper presents determination of Maiganga lignite coal
combustion characteristics for application in thermal power plant using
standard mathematical models. The problem statement was that
Nigeria cement plants uses rotary kiln coal burner despite its
associated drawbacks such as sudden explosion and incomplete
combustion. Fluidized bed technology has less of the drawbacks
associated with rotary kiln coal burner. The integration of Maiganga
coal in mathematical models will increase accurate prediction of
operating variables useful in design and sizing the components of
fluidized bed thermal power plant. The methodology of the study
includes utilization of established numerical models based on energy
balance and fuel properties for Maiganga lignite combustion. The coal
was fired in a pilot atmospheric fluidized bed combustor (FBC). The
results obtained include the theoretical air required per kg of
Maiganga lignite was 7.4, at an excess air of 10% and maximum mass
of air supplied per kg of Maiganga lignite of 8.82. The time for burn
out of particle sized 0.4 mm was determined to be 2.64 min, with
burning rate of 0.23 kg/min (3.8 g/s). The ignition temperature of 797 K
and fuel power of 84 kW for Maiganga coal were determined for the
pilot FBC in this study. The Maiganga lignite fuel, air and sorbent flow
rates through the fluidized bed combustor were predicted to be 14.2
kg/hr (0.23 kg/min), 202.4 kg/hr and 1.26 kg/hr respectively. The
combustion performance evaluation of the fluidized bed combustor
had specific firing rate for the lignite at graded particle size of between
0.2-1.12 mm at bed temperature of 1173 K was 2.8 g/m2s, air-fuel ratio
of 23 and equivalence ratio of 0.45. The above results are similar to
coal burnout time of 3 minutes and equivalence ratio of 0.40 in an
atmospheric fluidized bed combustor in the literature. Hence, above
parameters can be used to design and model a safe ignition and good
combustion characteristics in other lignite fired power plants similar to
that of Maiganga lignite coal.

© 2019 Faculty of Engineering, University of Maiduguri, Nigeria. All rights reserved.

1.0 Introduction
Maiganga coal is mined and processed for combustion in rotary kiln coal burner for cement
production by Ashaka cement plant. The combustion of Maiganga coal takes place in the

mailto:idris.ozigi@uniabuja.edu.ng
http://www.azojete.com.ng


Arid Zone Journal of Engineering, Technology and Environment, June, 2019; Vol. 15(2):418-434. ISSN 1596-2490;
e-ISSN 2545-5818; www.azojete.com.ng

Corresponding author’s e-mail address: idris.ozigi@uniabuja.edu.ng

419

presence of high temperature, turbulence and continuous air flow that results in rapid oxidation,
ignition and hot flame in an enclosure like rotary kiln burner and fluidized bed combustor.
Modular coal-fired thermal power plant developments have increased in Nigeria with proposed
Okobo coal-fired power plant at capacity of 1200 MW and others. Exploitation of coal by surface
working method from Maiganga hills, near Kumo in Gombe, commenced in October, 2007. The
combusting of Nigerian coals in rotary kiln coal burner is about a decade in Nigeria and the
technology have spread from Ashaka cement plant to cement plants at Obajana, Ibese, and
Sokoto. The rotary kiln coal burner has drawbacks such as sudden and frequent coal explosion
as well as incomplete combustion. Fluidized bed coal combustion technology has less of the
drawbacks associated with rotary kiln coal burners.

Mathematical models in the form of equations, graphs or tables can be used to represent and
predict phenomena as in fluidization and combustion. Mathematical models contribute to better
understanding of the processes in thermal power plants (Alobaid, et al., 2016). The fuel
properties in the modelling are to advance an established fact that moisture, volatile matter,
oxygen, hydrogen contents among other factors contributes to combustion as reported by
Ngampradit et al. (2004). There are several combustion models that had addressed various parts
of fluidized bed combustion available in literature. An example was computational fluid
dynamics (CFD) combustion model for biomass for different particle sizes in a fluidized bed as
reported by Li et al. (2015a). The integration of Maiganga coal in fluidized bed combustion
models have received little attention. Mathematical models applications have increased accurate
prediction of operating variables such as air flow rate, fuel flow rate among others for complex
fluidization processes in combustor. These operating variables are in turn useful in design and
sizing the components of the fluidized bed thermal power plant.

Lee (1997) investigated heat transfer and combustion in advanced swirling fluidized bed
combustor. He formulated the basic governing equations based on continuity, energy equations,
chemical reaction and radiation heat transfer. Ngampradit et al. (2004) simulated a circulating
fluidized bed combustor with shrinking core and emission. Their work was to predict proper
amount of fuel blend and to reduce emission from coal combustion. The researchers attained
improvement in the solid fuel size change during the combustion. The researchers also added
emission models to predict the formation of NO, N2O and SO2, which can be used for
environmental prediction consideration. Similarly, Mikulcic et al. (2014) reported numerical
study of co-firing pulverized coal and biomass inside a cement calciner. The results show that
when combusting biomass in an existing pulverized fuel burner, special attention need to be
given to complex oxidation of char particles to avoid unpredicted emission of hot fly ash. Their
numerical models improve better understanding of particle kinetics in the operation of the
calciner in reduction of pollutant formation. Marra et al. (2014) worked on fluidized bed
combustor coupled with a sterling engine for co-generation purposes, which consisted of heat
transfer, energy balance in fluidized bed and the relationship between power, efficiency and
torque at assigned geometrical parameters and physical properties of sterling engine. More
efficient heat transfer due to multiphase fluidized medium was attainable than heat transfer
tubes immersed in flue gases during their study. The abrasion action of solid particles also
reduces fouling of the heat exchanger surfaces that are associated with coal and biomass
combustion. However, the contribution of diameter and length of heater tubes on performance
prediction without loss of efficiency and power needs further investigation. Johnson (2007)

file:///C:/Users/user/Downloads/azojete143/www.azojete.com.ng


Ozigis and Zarmai: Determination of Maiganga Lignite Coal Combustion Characteristics for Application in Thermal
Power Plant using Standard Mathematical Models. AZOJETE, 15(2):418-434. ISSN 1596-2490; e-ISSN 2545-5818,
www.azojete.com.ng

Corresponding author’s e-mail address: idris.ozigi@uniabuja.edu.ng 420

worked on biomass-fired fluidized bed combustion for clean energy production with advantage
to reduce exhausted SO2, CO2 and particulates from the flue gas in comparable to fossil fuel
combustion under similar circumstances. The researcher essentially reviews the trend of
development of fluidized bed technology and made an outlook into the future without
discussing the challenges associated with combustion of solid and gas in each of the mentioned
fluidized bed technologies. Thapa et al. (2016), centered their work on physics of fluidization and
chemistry of fuel combustion. Their modeling and simulation focused on various flow regimes
enriched with olivine, coal char and their mixture in air fed into fluidized bed combustion reactor.
Their short coming was the proportion of total gas feed rate into bottom and primary were not
included in the modeling process. Sarroza et al. (2017), investigated the ignition characteristics
of pulverized coal, biomass and co-firing by use of a visual drop tube furnace and a high-speed
imaging technique camera. The results indicated effect of volatile matter content in coal and
alkali metal present in biomass on the distance to ignition as captured by the camera. However,
the distance to ignition point measured by the camera is different to ignition temperature
except a correlation was employed.

The process of coal combustion involves heating up, drying, devolatization and char oxidation as
variously reported by researchers such as Basu (2015) and Li et al. (2015b). However, there are
difficulties connected with combustion of coal in thermal power plants. Some of the key
challenges include sudden fire explosion, which are threats to safety in addition to economic
losses. The main causes of undesirable explosion were attributed to contact with hot surfaces by
leakages of coal particles and oil from startup burner, main burner and flue gas cleaning devices
like electrostatic precipitators. In addition, sudden explosion can occur in thermal power plants
due to external factors such as smoking, open flame, welding, among other factors but can be
handled with good working habits. The external factors in explosion have several protection and
prevention techniques reported by Chunmiao et al. (2011). The challenges are inherent factors in
fuel, that aid sudden explosion as reported by Eckhoff (2003). It is desirable to minimize this
challenge to ensure safe combustion and encourage use of coal, instead of idle and unexploited
coal deposit asset, in several places of the world.

Researches on Maiganga coal had mainly be on proximate, ultimate, petrographic, ash,
thermographic and radiological analyses as well as calorific value determination, while
combusting the coal in furnaces and burners are scanty in literature. In this work, Maiganga coal
was analyzed for prediction of combustion characteristics for application in thermal power plants
using standard mathematical models. Maiganga coal has proven reserve of about 760 million
metric tons and is found in Maiganga hills, near Kumo, along Gombe-Yola Road, in Akko Local
Government Area of Gombe State, Northeastern part of Nigeria as reported by Idriss et al.
(2018). The deposit lies within longitude 11°20’E and latitude 10°20'N.

The aim of this research is to study the Maiganga coal combustion characteristics for application
in thermal power plants using standard mathematical models. The objectives are to determine
the Maiganga lignite fuel properties and its combustion stoichiometry; calculate the Maiganga
lignite burning rate and its fuel power; evaluate the fuel, air and sorbent flow rates through the
combustor as well as to conduct performance evaluation of the combustor and validation of the
models.

http://www.azojete.com.ng


Arid Zone Journal of Engineering, Technology and Environment, June, 2019; Vol. 15(2):418-434. ISSN 1596-2490;
e-ISSN 2545-5818; www.azojete.com.ng

Corresponding author’s e-mail address: idris.ozigi@uniabuja.edu.ng

421

2. Methodology
2.1 Determination of Maiganga Lignite Fuel Properties and Combustion Stoichiometry
The Maiganga lignite samples were collected from Maiganga coal mine owned by Ashaka
Cement Plc, and was prepared according to ASTM standard of D2234 (ASTM, 1990) for the
particle size analysis which was carried out at National Metallurgical Development Centre, Jos.
The proximate and ultimate analyses of the Maiganga lignite coal were performed according to
ASTM standards described in codes D3173, D4239, D3174, D5142 and D5373 (ASTM, 1990). The
proximate and ultimate analyses as well as the calorific value had been carried out by several
researchers such as Idriss et al. (2018), Tikpangi (2016) and Ryemshak and Jauro (2013), which
were adopted for this work. The properties of gypsum and particle size distribution were
determined in this work at National Metallurgical Development Centre, Jos. Determination of
particle size distribution of crushed and ground coal and gypsum as well as coal combustion in a
pilot fluidized bed combustor were carried out. Mathematical models for Maiganga lignite
combustion in fluidized bed were selected from established models on energy and mass
balances from literature. The models were used to estimate performance of the Maiganga lignite
fired in a combustor. The theoretical air required per kg of fuel, excess air required and actual
mass of air were obtained by substitution of proximate and ultimate analysis of Maiganga lignite
in the stoichiometry equations (Balleney, 2007; UNEP, 2006). The theoretical air required per kg
of fuel (TA) was determined using equation (1) as given by Balleney (2007):







  SOHCTA )

8
(8

3
8

23
100 2

2

(1)
where:
C is carbon content in the ultimate analysis of Maiganga lignite
H2 is hydrogen content in the ultimate analysis of Maiganga lignite
O2 is oxygen content in the ultimate analysis of Maiganga lignite
S is sulphur content in the ultimate analysis of Maiganga lignite

The amount of excess air required (EA) calculated using equation (2) as given by UNEP (2006):

2

2

21
100
O

OEA 



(2)

where:
O2 is oxygen content in the ultimate analysis of Maiganga lignite
The actual mass of air supplied per kg of fuel ( ) was calculated using equation (3) as given by
UNEP (2006):

A
A TE

 )
100

1(
(3)

where:
EA is excess air required for the Maiganga lignite combustion (%)
TA is the theoretical air requirement per kg of Maiganga lignite fuel.

2.2 Maiganga Lignite Fuel Burning Rate and Fuel Power
2.2.1 Burning rate constant and time for burn out of lignite
The burning rate constant (Kb) was obtained using equation (4) as given by Turns (2000):

file:///C:/Users/user/Downloads/azojete143/www.azojete.com.ng


Ozigis and Zarmai: Determination of Maiganga Lignite Coal Combustion Characteristics for Application in Thermal
Power Plant using Standard Mathematical Models. AZOJETE, 15(2):418-434. ISSN 1596-2490; e-ISSN 2545-5818,
www.azojete.com.ng

Corresponding author’s e-mail address: idris.ozigi@uniabuja.edu.ng 422

c
b

BDK


 )1ln(8 2 


(4)
where:

2 is approximately gas-particle density (kg/m3)
D is diffusion coefficient for lignite coals (m2/s)
B is transfer number in combustion of lignite coal for O2 and CO2 diffusion = constant
c is bulk density of Maiganga lignite coal at graded size (kg/m3)

The lignite particle burn-out time was determined using equation (5) as given by Turns (2000):

b

c
c k

dt
2


(5)

where:
dc is initial lignite particle size (mm)
Kb is burning rate constant (m2/s)

2.2.2 Lignite burning rate (Ff)
The burning rate (kg/hr) was calculated using equation (6) as follows (Turns, 2000):

)1ln(4 2 BDrF cf   (6)
where:
rc is maximum lignite coal particle radius (mm)

2.2.3 Energy balance in lignite coal combustion
The chemical heat of Maiganga lignite coal in combustion was obtained as the product of
burning rate and the lignite lower calorific value (LCV) as expressed in equation (7). Thus:

LCVFQ f (7)
where:
Ff is lignite coal burning rate or lignite flow rate (kg/hr) (Ozigis and Arudi, 2013)
LCV is lignite coal calorific value (kJ/kg)
Q is energy capacity (KJ/hr) or (W)
Therefore, bed temperature in the combustor was determined using equation (8) as follows:

ff

fb

Cm
LCVF

dt
dT


(8)

where:
mf is mass of the lignite coal in combustor (kg)
Cf is specific heat capacity of the lignite coal (kJ/kgK)

2.3 Maiganga Lignite Fuel, Air and Sorbent Flow rates in the Combustor
2.3.1 The quantity of air supplied into fluidized bed combustor

http://www.azojete.com.ng


Arid Zone Journal of Engineering, Technology and Environment, June, 2019; Vol. 15(2):418-434. ISSN 1596-2490;
e-ISSN 2545-5818; www.azojete.com.ng

Corresponding author’s e-mail address: idris.ozigi@uniabuja.edu.ng

423

The quantity of dry air at atmospheric pressure supplied by centrifugal fan for combustion was
determined using equation (9) as follows (Highley and Kaye, 1983; Ozigis, et al. 2015):

)1)(( AAfa ETFF  (9)
where:
Fa is the air flow rate from the centrifugal fan (kg/hr)
Ff is fuel flow rate (kg/hr)
TA is theoretical air (kg of air/kg of fuel)
EA is excess air (%)

The volumetric flow rate (Qa) of air was found using equation (10) as given below:


a

a
FQ 

(10)
where:
 is density of air (kg/m3)
Qa is volumetric flow rate (m3/s)

2.3.2 Particle surface temperature
The surface temperature attained by lignite coal particle was determined from coal particles rate
of heat transfer (Q) to bed materials using equation (11) as given by Broughton and Howard
(1983):

 bfcc TTAhQ  (11)
where:
Ac is surface area of the particles (m2)
Tf is particle surface temperature (K)
Tb is bed temperature (K)
hc is heat transfer coefficient of coal particle (W/m2K) as using equation (12) obtained from
Broughton and Howard (1983):

pc
c dd

kh 016.02


(12)
where:
dp is sorbent gypsum particle size (mm)
K is thermal conductivity of the combustion gas (W/m.K)
Therefore, the surface temperature of lignite in combustor was determined using equation (13)
as follows:

ff

bfccf

Cm
TTAh

dt
dT )( 


(13)

where:
mf is mass of the lignite coal in combustor (kg)
Cf is specific heat capacity of the lignite coal (kJ/kgK)

file:///C:/Users/user/Downloads/azojete143/www.azojete.com.ng


Ozigis and Zarmai: Determination of Maiganga Lignite Coal Combustion Characteristics for Application in Thermal
Power Plant using Standard Mathematical Models. AZOJETE, 15(2):418-434. ISSN 1596-2490; e-ISSN 2545-5818,
www.azojete.com.ng

Corresponding author’s e-mail address: idris.ozigi@uniabuja.edu.ng 424

2.3.3 Sulphur Removal by Sorbent in Maiganga Lignite Coal Combustion
The mole flow rate of sulphur (Fsm) in gypsum was calculated using equation (14) given by Nag
(2009):

mws

f
sm M

SF
F




(14)
where:
Ff is burning rate of Maiganga lignite coal or flow rate (kg/hr)
S is percentage of sulphur content in Maiganga lignite (%).
Mmws is molecular mass of sulphur (kg/kmol) (obtained from periodic table).
However, the flow rate of calcium at calcium to sulphur ratio of 3:1 (molar basis), is to limit
emissions of SO2 adequately and was calculated using equation (15) as given by Nag (2009):

ratiomolarFF smc  (15)
where:
Fc is flow rate of calcium (Kmol/hr)
Mass flow rate of CaSO4 (Fcs) was determined using equation (16) as given by Nag (2009):

cmwgcs FMF  (16)
where:
Mmwg is molecular mass of CaSO4 (kg/kmol)
Fcs is mass flow rate (kg/hr)
The percentage of CaSO4 in gypsum was determined using equation (17) as follows:

100% 4 
gypsummw

gmw

M
M

CaSO
(17)

where:
Mmw gypsum is the molecular mass of gypsum (CaSO4.2H2O) (kg/kmol)
Therefore, mass flow rate of gypsum (Fg) was calculated using equation (18) as follows:

4%CaSO
FF cs

g 
(18)

where:
Fg is sorbent flow rate (kg/hr)
Comparing fuel flow rate to sorbent flow rate, the sorbent gypsum constitutes

100
f

g

F
F

.
Heat lost for sulphur removal by sorbent gypsum reaction during combustion was calculated
using equation (19) as given by Kataja and Majanne (2007):

)()( gbpgggfgc
gpgg TTCFTTxh

dt
dTCm

 
(19)

where:

http://www.azojete.com.ng


Arid Zone Journal of Engineering, Technology and Environment, June, 2019; Vol. 15(2):418-434. ISSN 1596-2490;
e-ISSN 2545-5818; www.azojete.com.ng

Corresponding author’s e-mail address: idris.ozigi@uniabuja.edu.ng

425

x is total exposed surface area of ejected sorbent gypsum (m2)
g is residence time of sorbent gypsum in the combustor (s)

Cpg is gypsum specific heat capacity (kJ/kgK)
Tg is gypsum temperature in bed (K)
mg is mass of sorbent gypsum fed into the combustor (kg)
Therefore, temperature of sorbent gypsum in the combustor was calculated using equation (20)
as follows:

pgg

gbedpgggfgcg

Cm
TTCFTTxh

dt
dT )()( 




(20)

2.4 The Combustion Performance Evaluation of the Fluidized Bed Combustor
The performance parameters include specific firing rate, air-fuel ration and equivalence ratio.

Specific Firing Rate
The specific firing rate (SFR) was estimated using equation (21) as given by Broughton and
Howard (1983):

bc
f

FR PDm
At
m

S 
(21)

where:
mf is mass of fuel burnt (kg)
A is the area of air distributor based on total area of orifice diameter (m2)
t is time for combustion (s)
mc is molecular mass of Maiganga lignite coal

bP is the bed pressure
D is reaction rate coefficient for coal at 1173 K

2.4.2 Determination of air fuel ratio
Air fuel ratio (AF) was determined using equation (22) as given by Crawford (1980):

mc

a

nm
nAF





97.28 (22)

where:
an is number of moles of oxygen plus number of moles of nitrogen.
cm is molecular weight of Maiganga lignite coal = 12
mn is number of moles of Maiganga lignite coal = 1.

2.4.3 Equivalence ratio of fuel combustion in the combustor
Equivalence ratio was defined and calculated using equation (23) as given by Ramirez, et al.
(2007):

AF
RE L

(23)

file:///C:/Users/user/Downloads/azojete143/www.azojete.com.ng


Ozigis and Zarmai: Determination of Maiganga Lignite Coal Combustion Characteristics for Application in Thermal
Power Plant using Standard Mathematical Models. AZOJETE, 15(2):418-434. ISSN 1596-2490; e-ISSN 2545-5818,
www.azojete.com.ng

Corresponding author’s e-mail address: idris.ozigi@uniabuja.edu.ng 426

where:
LR is air-fuel ratio minimum and specific to the combustor

AF is air fuel ratio

LR is air-fuel ratio minimum and specific to the combustor was calculated using equation (24) as
given by Ramirez, et al. (2007):

f

a
L F

F
R




292.1 (24)
where:
Fa is air-fuel ratio in the combustor
Ff is air fuel ratio

The combustor’s equivalence ratio was determined in terms of flow rates and air-fuel ratio using
equation (25) as follows:

AFF
F

E
f

a




292.1 (25)
where:
AF is air fuel ratio
Fa is the air flow rate from the centrifugal fan (kg/hr)
Ff is fuel flow rate (kg/hr)

2.5 Computing Procedure
The data from proximate and ultimate analysis, pilot fluidized bed combustor (FBC) were used
to validate the models, which were computed as design data shown in Table 2. The developed
ordinary differential equations were numerically integrated over time, bearing in mind the
assigned initial values of bed, sorbent gypsum and particle surface temperatures. M-file and
programme base on combustion parameters were developed for ODE 45 and were run on
MATLAB. The programme was used to determine temperatures at various parts of the
combustor as well as the burning rate, specific firing rate and equivalence ratio of coal
combustion. The results were presented in the form of Tables and Figures.

3. Results and Discussion
3.1 Maiganga Lignite Fuel Properties and Combustion Stoichiometry
The proximate and ultimate analysis of Maiganga lignite and Tongo gypsum are as shown in
Table 1. A high volatile matter indicates long flame and more smoke from the fuel when fired.
Volatiles ignite first and sustain the process of combustion. Maiganga coal with 30.5% volatiles
and average calorific value of 22 MJ/kg, implies it is a lignite but close to sub bituminous coal as
with description in ASTM (Oka, 2004). Tongo gypsum indicates that it could react with coal
during combustion because of its high calcium content (36.01%); hence, useful as sorbent
material. Thus, sulphur presence in solid fuel can be removed with addition of gypsum. Calcium
is among materials that can cause reduction of SO2 emission in co-firing of coal in combustor as

http://www.azojete.com.ng


Arid Zone Journal of Engineering, Technology and Environment, June, 2019; Vol. 15(2):418-434. ISSN 1596-2490;
e-ISSN 2545-5818; www.azojete.com.ng

Corresponding author’s e-mail address: idris.ozigi@uniabuja.edu.ng

427

reported by Rokni, et al. (2017). The Maiganga coal proximate and ultimate analysis as shown in
Table 1, were adopted for the modelling to predict the combustion characteristics. The
proximate analysis for Maiganga lignite in this work are within the mean values of moisture
(11.03%), volatile (36.10%), carbon (45.96%) and ash (6.91%), respectively, as reported by
Tikpangi (2016). The oxygen content (11.38%) and calorific value (22 MJ/kg (4982 Cal/g))
reported by Ryemshak and Jauro (2013), were similar to the results of oxygen content and
calorific values reported in this work. Maiganga lignite fuel properties differences from one
location to the other locations, according to Ikwuagwu and Uzoegbu (2017), which were due to
environmental and temperature effects on lignite at different depths and locations within an
area, similarly, reported by researchers on this Maiganga lignite deposit. However, the
percentages of moisture and ash of Maiganga coal in this work differ to results reported by
Ikwuagwu and Uzoegbu (2017), due to variation in air-dried or oven dried of the feedstock. The
particle size distribution for the Maiganga lignite ranges from 0.2 mm to 1.12 mm was an
effective specific surface area for an efficient combustion in the pilot fluidized bed combustor,
after removal of foreign matters by using appropriate sieves. However, particle size can be less
than 75 m for coal burner in cement rotary kiln as reported by Song et al. (2018). Particle size
distribution range for burners helps to minimize oversize and under size that can cause large
particle breakages and coal hang-up. Coal hang-up occurs due to coal moisture in thermal
power plant, which can cause sudden explosion. During coal combustion, hot flashes and fly
ashes from finer particles can ignite other material that can lead to sudden explosion in
combustors such as in rotary kiln burner for cement production.

Table 1: Proximate and Ultimate Analysis of Maiganga Lignite and Gypsum
S/N % Composition Maiganga Lignite Coal* Tongo Gypsum
1 Moisture 13.7 20.93
2 Volatile Matter 30.5
3 Ash 10
4 S 0.56 18.62
5 C 56
6 N2 0.91
7 H2 3.86 2.34
8 O2 10.05 55.76
9 CaO 32.57
10 SO3 46.5
11 Ca 23.28
12 Calorific Value (MJ/kg) 21-23
13 %CaSO4 79
*Adopted from Idriss, et al. (2018), Tikpangi (2016) and Ryemshak and Jauro (2013)

Combustion stoichiometry is aimed to determine exactly the quantity of air needed to oxidize
fuel that results in stable flame and safe products. The presences of CO2, SO2, CO, among others,
will require monitoring to prevent concentration beyond approved limit and to take decision on
type of explosion venting devices to minimize fire explosion. In addition, prevention of CO in
flue gas cleaning devices like electrostatic precipitator will minimize fire explosion. Table 2 has

file:///C:/Users/user/Downloads/azojete143/www.azojete.com.ng


Ozigis and Zarmai: Determination of Maiganga Lignite Coal Combustion Characteristics for Application in Thermal
Power Plant using Standard Mathematical Models. AZOJETE, 15(2):418-434. ISSN 1596-2490; e-ISSN 2545-5818,
www.azojete.com.ng

Corresponding author’s e-mail address: idris.ozigi@uniabuja.edu.ng 428

stoichiometric quantity of air per kg of Maiganga coal, which took into account the moisture
content. Above stoichiometric quantity of air per kg of 7.423 kg, will result in warm flue gases
while below will result in fuel rich mixture as reported in Turns (2000). Complete combustion of a
rich mixture that results in fuel built up at burner can lead to sudden explosion; hence avoidance
of fuel rich in thermal plant is desirable. The excess air in this work varies between 10-20% but
with preference for 10% depending on particle size. According to Gupta (2007), coal requires
about 50% excess air to completely burn, depending on fuel particle sizes, which differ from
excess air in this work. Sufficient excess air has tremendous influence in minimization of sudden
explosion in fuel combustion. Conversely, when minimum amount of air was supplied, part of
the fuel will not burn due to lack of intimate contact between air and coal.

Table 2: Computed Design Data for the Combustion
S/N Description Unit value
1 Theoretical air required per kg of fuel 7.4
2 Excess air (%) 10
3 Maximum mass of air supplied per kg of fuel 8.82
4 Burning rate constant (m2/s) 81032.6 
5 Time for burnt out at 0.4-10mm particle size (min) 2.64
6 Burning (Fuel flow) rate (kg/min) 0.23
7 Power in fuel (kW) 84
8 Air flow rate (kg/hr) 202.4
9 Sorbent (gypsum) flow rate (kg/hr) 1.26
10 Specific firing rate (SFR) (kg/m2.min) 0.168
11 Air-fuel ratio 23
12 Equivalence ratio of the Maiganga lignite fuel combustion 0.45

3.2 Maiganga Lignite Burning Rate and Fuel Power
Coal particle burning rate was determined by computation of burning rate constant and time for
burnt out with values as shown in Table 2. The time for burn out of particle sized 0.4 mm was
determined to be 1.74 minutes, with burning rate of 0.23 kg/min (3.8 g/s). Burn out time
depends on particle size, bed temperature and coal characteristics as reported by Broughton
and Howard (1983). Similarly, burning rate in fluidized bed was reported in one instance as 6.0
g/s for particle sized 3.0-10 mm at bed temperature of 985-1110 K by Oka (2004) as against 3.8
g/s (0.23 kg/min) in this work. The coal burning time can last up to 33 minutes and
devolalization takes up to 10-100 seconds, depending on the type of coal and particle size as
reported by Oka (2004). The optimum burning rate at particle size of 0.4 mm was 0.23 kg/min
(0.0038 kg/s), similar to burning rate of palm kernel-sawdust briquettes determined to be 0.002-
0.006 kg/s for boiling water test as reported by Kuti (2009). Therefore, burning rate depends on
intensity of O2 diffusion towards the coal particle surface, rate of chemical reaction and
increases with char particle size. The ignition temperature of 797 K for Maiganga coal was
determined in this pilot fluidized bed combustor as previously reported by Ozigis, et al. (2013).
Ignition temperature and burning rate are useful for safety issues due to explosiveness of coal
dust when fired in a combustor.

http://www.azojete.com.ng


Arid Zone Journal of Engineering, Technology and Environment, June, 2019; Vol. 15(2):418-434. ISSN 1596-2490;
e-ISSN 2545-5818; www.azojete.com.ng

Corresponding author’s e-mail address: idris.ozigi@uniabuja.edu.ng

429

3.3 Maiganga Lignite Fuel, Air and Sorbent Flow rates through the Combustor
The fuel, air and sorbent flow rates were 0.23 kg/min, 202 kg/hr and 1.26 kg/hr respectively, as
shown in Table 2. The fuel and airflow rates promote turbulence, sustenance of combustion and
flame front and collectively affect particle surface temperature. Burning rate is equated to fuel
flow rate in coal-fired fluidized bed combustor, because no fuel is allowed to hang and build up
in combustor to minimize explosion as reported by Broughton and Howard (1983). Fuel build up
and burner flame stabilization were managed with controls to minimize sudden explosion, often
with smoke and heat detectors as well as elimination of leaks from oil guns, oil burner light up
operations and finer particles from fuel ducts as reported in Broughton and Howard (1983). The
profiles for particle surface, bed and sorbent temperatures against Maiganga lignite burning
time in a pilot FBC are as shown in Figure 1. Some of the predictable factors to minimize
frequency of fire explosion in coal burner include particle size, fuel moisture level, sorbent, bed
and particle surface temperatures. In addition, first in and first out policy for coal storage and
usage will minimize spontaneous combustion as well as avoidance of wet and dry coal particles
that can cause clogging in fuel feed line and in screw feeder. The particle surface temperature of
1800K obtained for Maiganga lignite in this work was close to flame temperature when
compared to particle surface temperature of bituminous coal of 2445 K reported by Sarroza, et
al. (2017). The main reason for sluggish increase of sorbent gypsum temperature that was
predicted by the models was due to its high calcium content in the Tongo gypsum. The practice
of blending coal with gypsum to remove sulphur in coal is not wide spread in thermal power
plants in developing countries. The mass flow rate of gypsum at 1.26 kg/hr will remove sulphur
in coal, and will also minimize sudden and undesirable explosion in combustor. In this work,
Tongo gypsum had flow rate at 9% in Maiganga coal with sulphur content of 0.56%, similar to a
coal-fired fluidized bed boiler that had flow rate of limestone at 40% in a coal with sulphur
content of 3.6% as reported by Nag (2009).

Figure 1: Maiganga Lignite Particle Surface, Bed and Gypsum Temperature against Time

3.4 Combustion Performance Evaluation of the Fluidized Bed Combustor
The Maiganga lignite particle sizes relationship with burning rate, specific firing rate (SFR) and
equivalence ratio are as shown in Figure 2. The lower the SFR, the more economical the fuel
burnt. Hence, Maiganga lignite is suited for combustion in particle sizes more than 0.4 mm to
achieve high equivalence ratio that approaches 0.45, whereas less than particle sizes of 0.4 mm,
the equivalence ratio decreases from 0.15 to 0.05. It has been recognized that the performance

file:///C:/Users/user/Downloads/azojete143/www.azojete.com.ng


Ozigis and Zarmai: Determination of Maiganga Lignite Coal Combustion Characteristics for Application in Thermal
Power Plant using Standard Mathematical Models. AZOJETE, 15(2):418-434. ISSN 1596-2490; e-ISSN 2545-5818,
www.azojete.com.ng

Corresponding author’s e-mail address: idris.ozigi@uniabuja.edu.ng 430

of combustor depends mainly on equivalence ratio range used. The lower limit of equivalence
ratio range was determined by the minimal amount of air required to oxidize fuel and generate
enough heat to maintain combustion process. Low values of equivalence ratio would reduce bed
temperature and the energy liberation necessary to maintain the combustion processes. On the
other hand, high equivalence ratio would cause increases in bed temperature due to increase in
oxygen diffusion as reported by Ramirez et al. (2007).

Figure 2: Effects of Maiganga Lignite Particle Sizes on Performance of the Combustor

3.5 Validation of Mathematical Models
Presented in Table 3 is the comparison of model results with other results in literature. The
modelled fluidized bed combustor had fuel and airflow rates of 14.2 kg/hr and 202.4 kg/hr
respectively, obtained in this work at a bed temperature of 1173 K. The burning (flow) rate of
14.2 kg/hr and airflow rate of 202.4 kg/hr can be employed in design of screw feeder for
metering of ground coal and centrifugal fan for supply of air to the combustor, respectively. The
FBC had fuel to airflow rates ratio of 0.071, due to excess air of 10%. The ratio of fuel to airflow
rates in standard fluidized bed combustor is within 0.15 as reported by Alobaid, et al. (2016). Tri-
Tordai, et al. (2010), reported co-combustion of coal and biomass with power output of 45-90
kW in that work. Optimizing airflow and fuel flow can result in uniform and efficient combustion
as reported by Wiatrus-Motyka (2016). Also, another modelled coal combustion resulted in a
particle burn out time of 3 minutes at specific firing rate of 3.83 g/m2s at a bed temperature of
1173 K as reported by Broughton and Howard (1983). On the other hand, Maiganga lignite coal
had burn out time of 2.64 minutes with corresponding specific firing rate (SFR) of 2.8g/m2s
(0.168 kg/m2min) at bed temperature of 1193 K obtained in this work. SFR is a measure of
intensity of combustor operation, control of flame lift and as an estimate for comparing various
coal-fired burners. SFR will guide sizing of air distributor, orifice diameter and estimation of coal
flow rate into combustor for efficient firing devoid of fuel rich combustion. Furthermore,
Maiganga lignite coal combustion at equivalence ratio of 0.45 obtained in this work is similar to
an equivalence ratio of 0.40 for rice-husk-fired fluidized bed gasifier reactor as reported by
Ramirez et al. (2007). The bed temperature obtained for Maiganga coal during burning ranges
from 1103 to 1223 K. This is similar to bed temperature of 1273 K for coal-fired furnace reported
by Li, et al. (2010). All the Maiganga coal models results were compared with other results in
literature with good agreement. Therefore, the selected mathematical models have been

http://www.azojete.com.ng


Arid Zone Journal of Engineering, Technology and Environment, June, 2019; Vol. 15(2):418-434. ISSN 1596-2490;
e-ISSN 2545-5818; www.azojete.com.ng

Corresponding author’s e-mail address: idris.ozigi@uniabuja.edu.ng

431

validated and can be used appropriately in limiting sudden explosion and raise more interest in
fluidized bed burners for cement production and for modular coal-fired thermal power plants.

Table 3: Comparison of Model Results with Literatures
S/N Parameters Model Results for

Maiganga Lignite
Results Obtained From Literature

1 Maiganga fuel flow rate
(kg/hr)

14.20 40-80 Tri-Tordai et al. (2010)

2 Air flow rate (kg/hr) 202.4 297 Tri-Tordai et al. (2010)
3 Particle burn out time (min) 2.64 3.0 Broughton and Howard,

(1983).
4 Bed Temperature (K) 1103-1223 1275 Li et al. (2010)

5 Equivalence ratio 0.45 0.4 Ramirez et al. (2007)
6 Thermal energy output (kW) 84 45-90 Tri-Tordai et al. (2010)

4. Conclusion
This work presents determination of Maiganga lignite coal combustion characteristics for
application in thermal power plant using standard mathematical models. The conclusions drawn
were that particle size distribution can minimize sudden explosion from fly ash particles and
moisture in coal fired in combustor needs to be minimized to avoid clogging that can lead to
explosion while sorbent gypsum will minimize bed temperature. The ignition temperature of
Maiganga lignite coal was determined to be 797 K. The models were used to determined
Maiganga lignite fuel to have air-fuel ratio of 23 and equivalence ratio of 0.45. The airflow rate of
202.4 kg/hr will form the basis for design of centrifugal fan for forced air supply into the
combustor. The Maiganga lignite-burning rate of 14.2 kg/hr with burn out time of 2.64 minutes
for particle size graded at 0.4 mm was determined. The burning rate of 14.2 kg/hr will aid the
design of screw feeder for supply and metering of ground Maiganga lignite fuel into the
combustor. The specific firing rate for Maiganga lignite at 0.4 mm particle size and at 1173 K bed
temperature was 2.8 g/m2s. The specific firing rate of 2.8 g/m2s, will guide the design of surface
area of air distributor, orifice diameter and for estimation of rate of coal into the combustor for
efficient firing devoid of fuel rich combustion.

Acknowledgement
The authors wish to thank all the Staff that assisted in carrying out the experiments at the
combustion bay in the Faculty of Engineering, Abubakar Tafawa Balewa University, Bauchi,
Nigeria. In particular, the authors appreciate the contributions of Prof. A. A. Asere and Prof.
Habou Dandakouta for all their guidance and encouragement.

References
Alobaid, F., Mertens, N., Starkloff, R., Lanz, T., Heinze, C. and Epple B. 2016. Progress in dynamic
simulation of thermal power plants. Progress in Energy and Combustion Science, 59:129-136.

file:///C:/Users/user/Downloads/azojete143/www.azojete.com.ng


Ozigis and Zarmai: Determination of Maiganga Lignite Coal Combustion Characteristics for Application in Thermal
Power Plant using Standard Mathematical Models. AZOJETE, 15(2):418-434. ISSN 1596-2490; e-ISSN 2545-5818,
www.azojete.com.ng

Corresponding author’s e-mail address: idris.ozigi@uniabuja.edu.ng 432

ASTM-1990. American Society for Testing and Materials. Gaseous Fuel, Coal, Coke and Firewood.
Annual book of ASTM standards. New York 05,05; 04, 07.
Balleney, PL. 2007. Thermal Engineering. Delhi: Khanna Publishers Ltd: 618-684.
Basu, P. 2015. Combustion, circulating fluidized bed boilers: Design, operation and maintenance,
Canada: Springer: 89-119.
Broughton, J. and Howard, JR. 1983. Combustion of coal in fluidized bed. In: Howard J.R. (Ed.)
fluidized beds combustions and applications. Ripple road, Barking Essex, England: Applied
Science Publishers ltd; 1983: pp. 37-48, 66-72.
Chunmiao, Y., Chang, L. and Gang, L. 2011. Coal dust explosion prevention and protection based
on inherent Safety. First International Symposium on Mine Safety and Engineering, Procedia
Engineering, 26: 1517-1525.
Crawford, M. 1980. Air pollution control theory. New Delhi: McGraw; 259-574.
Eckhoff, RK. 2003. Dust explosions in the process industries. 3rd ed, Gulf Professional Publishing,
an Imprint of Elsevier; 1-156.
Gupta, OP. 2007. Elements of fuels, furnaces and refractories, 5th edition. 2 –B Nath market, Nai
sarak, New Delhi: Khanna Publishers; 174 – 176, 506- 509.

Highley, J. and Kaye, WG. 1983. Fluidized bed industrial boilers and furnaces in: Howard, JR.
editor. fluidized beds combustions and applications, Ripple road, Barking Essex, England: 77 –82,
86 –110.
Idriss, IM., Grema, AS., Musa, MA. and Ej-jummah, M. 2018. Maiaganga coal analysis and
gasification simulation for power generation. International Journal of Science, Environment and
Technology, 7.6:1933-1942.
Ikwuagwu, C. and Uzoegbu, MU. 2017. The Maiganga coal deposit: bituminous, sub-bituminous
or lignite. IOSR Journal of Applied Geology and Geophysics, 5.1: 67-74.
Johnson, F. 2007. Fluidized bed combustion for clean energy. The 12th International Conference
on fluidization-new horizons in fluidized Engineering, held at Chalmers University of Technology,
at SE-41296, Goteborg, Sweden, May 13-18, art 5, 47-61.
Kataja, M., and Majanne, Y. 2007. Dynamic model of a bubbling fluidized bed boiler, Tampere
Univ. of Tech., Institute of Automation and control, Box 692, Fi-33101, Tampere:140-148.
Kuti, AO. 2009. Performances of composite sawdust briquette fuel in a biomass stove under
simulation condition. Assumption University Journal of Technology, 12.4: 284-288.
Lee, SW. 1997. Investigation of heat transfer and combustion in the advanced fluidized bed
combustor. Tech. Report No.16. Pittsburgh: US Depart of Energy:1-13
Li, J, Manasosh, CP., Younger, PL., Watson, I., Hossain, M., and Welch, S. 2015a. Characterization
of biomass combustion at high temperatures based on an upgraded single particle model.
Applied Energy, 156: 749-755.
Li, J., Manasosh, CP., Younger, PL., Watson, I., Hossain, M., and Welch, S. 2015b. Prediction of
High Temperature Rapid Combustion Behaviour of Woody Biomass Particles. Fuel, 105:205-214.

http://www.azojete.com.ng


Arid Zone Journal of Engineering, Technology and Environment, June, 2019; Vol. 15(2):418-434. ISSN 1596-2490;
e-ISSN 2545-5818; www.azojete.com.ng

Corresponding author’s e-mail address: idris.ozigi@uniabuja.edu.ng

433

Li, S., Xu, T., Zhou, Q., Tan, H., and Hui, S. 2010. Effect of coal-over-coal reburns on furnace
temperature and heat flux distribution in 1MW tangentially fired furnace. International Journal of
Thermal Sciences, 49: 225-233.
Marra, FS., Miccio, F., Solimene, R., Urciuolo, M., Chirone, R., Continillo, G., Lombardi, S. and
Fussco, G. 2014. Stepup of an integrated stirling engine-fluidized bed experimental system, 16th
International Stirling Engine Conference, 24-26, September, Bilbao, Spain: 399-409.
Mikulcic, H., Berg, VE., Vujanovic, M., and Duic, N. 2014. Numerical study of co-firing pulverized
coal and biomass inside a cement calciner. Waste Management and Research, 32.7: 661-669.
Nag, PK. 2009. Power Plant Engineering. 3rd ed. 15th Reprint. New Delhi: Tata McGraw Hill
publishing Co. Ltd: 343-379.
Ngampradit, N., Piumsomboon, P. and Sajjakulnukit, B. 2004. Simulation of a circulating fluidized
bed combustor with shrinking core and emission model. Science Asia; 30: 365-374.
Oka, SO. 2004. Fundamental processes during coal combustion in fluidized beds. Fluidized Bed
Combustion, Marcel Dekker, basel, New York, USA; 211-355.
Ozigis, II. and Arudi, IS. 2013. Design, construction and performance of a screw feeder for
fluidized bed combustor. Nigerian Journal of Engineering; 20.1:54-63.
Ozigis, II., Dandakouta, H. and Egbo, G. 2013. Design and performance characteristics of heating
element in ignition of Maiganga lignite coal in a fluidized bed combustor. Journal of Engineering
and Technology; 8. 2: 47-52.
Ozigis, II, Dandakouta, H, and Egbo, G. 2015. Design and construction of centrifugal fan for a
fluidized bed combustor. Nigerian Journal of Tropic Engineering; 8. 2: 41-49.

Ramirez, JJ., Martinez, JD. and Petro, SL. 2007. Basic design of a fluidized bed gasifier for rice
husk on a pilot scale. Latin American Applied Research, :37 .4: 299-306.
Rokni, E., Chi, HH. and Levendis, YA. 2017. In-Furnace Sulphur Capture by Co-Firing Coal with
Alkali Based Sorbents. Journal of Energy Resources Technology, 139. July: 042204-2-042204-6.
Ryemshak, SA. and Jauro, A. 2013. Proximate analysis, rheological properties and technological
application of some Nigerian coals. International Journal of Industrial Chemistry, 4.7: 1-7.
Sarroza, CA., Bennet, TD., Eastwick, C. and Liu, H. 2017. Characterizing pulverizing fuel ignition in
a visual drop tube furnace by use of a high-speed imaging technique. Fuel Processing
Technology, 157: 1-11.
Song, CZ., Wen, JH., Li, YY., Dan, H., Shi, XY. and Xin, S. 2018. Thermogravimetric assessment of
combustion characteristics of blends of lignite coals with coal gangue. 3rd Annual International
Conference on Mechanics and Mechanical Engineering, Advances in Engineering Research,
Hothot, China: 105: 490-495.
Thapa, RK., Pfeifer, C. and Halvorsen, BM. 2016. Flow regime identification in a fluidized bed
combustor reactor. International Journal of Modelling and Optimization, 6.3:188-193.
Tikpangi, KM. 2016. Radiological, Trace Elemental and Petrographic Characteristics of Maiganga
Coal Deposits of Northern Benue Trough, North-Eastern, Nigeria. PhD thesis, Department of
Physics, University of Malaya, Kuala Lumpur: 97-99.

file:///C:/Users/user/Downloads/azojete143/www.azojete.com.ng


Ozigis and Zarmai: Determination of Maiganga Lignite Coal Combustion Characteristics for Application in Thermal
Power Plant using Standard Mathematical Models. AZOJETE, 15(2):418-434. ISSN 1596-2490; e-ISSN 2545-5818,
www.azojete.com.ng

Corresponding author’s e-mail address: idris.ozigi@uniabuja.edu.ng 434

Trif-Tordal, G., Ionel, I., Popescu, F., Dungan, LI. and Varga, L. 2010. Waste biomass & coal co-
combustion in stationary fluidized bed as promising RES based technology. WSEAS Transactions
on Environment and Development, 6(7):561-562.
Turns, SR. 2000. An Introduction to Combustion: Concepts and Applications. 2nd Ed London:
McGraw-Hill: 542-545.
UNEP-2006. United Nations Environment Programme, Thermal energy equipment: Boilers and
thermic-fluid heaters. United Nations Environment Programme, New Delhi, India: 13-17.
Wiatros-Motyka, M. 2016. Optimizing fuel flow in pulverized coal and biomass fired boilers.
International Energy Agency, Clean Coal Centre, London, UK: 1-61

http://www.azojete.com.ng

	ORIGINAL RESEARCH ARTICLE
	DETERMINATION OF MAIGANGA LIGNITE COAL COMBUSTION 
	I. I. Ozigis* and M. T. Zarmai
	OLE_LINK5
	OLE_LINK6
	OLE_LINK4
	OLE_LINK3