14th

IFRF Member’s Conference

Evaluation of Syngas Reburn Technology on a Tangentially p.c. Fired

Boiler with Advanced Chemical Engineering Models

2M. Falcitelli,

1S. Malloggi,

1(∗∗∗∗)N. Rossi,

3L. Tognotti ,

4 S. Merlini

1 ENEL S.p.A. – Generation and Energy Management Division – Area Tecnica Ricerca, Via A. Pisano,

120 - 56122 Pisa – ITALY 2 Consorzio Pisa Ricerche - Piazza D’Ancona, 1 – 56127 Pisa – ITALY

3 Università degli Studi di Pisa - Dipartimento di Ingegneria Chimica, Chimica Industriale e Scienza

dei Materiali – Via Diotisalvi 2, 56100 Pisa – ITALY 4 RJC Soft - Via Contessa Matilde 28 , 56125 Pisa - ITALY

ABSTRACT

This paper presents the outcome of an integrated methodology for the analysis of combustion

technologies applied for controlling NOx emissions and char burnout from full-scale power

plants. The methodology is based on an integrated use of furnace probing measurements

coupled with different simulation tools: CFD for 3D simulation of combustion chambers,

PROATESTM

providing a mono-dimensional model of the convection pass, and Chemical

Engineering Models (RNA). The latter consists of equivalent networks of ideal reactors

automatically extracted from the results of CFD simulations, where detailed reaction

mechanisms are applied and an accurate calculation of the combustion yields and of pollutant

emissions is performed.

In order to explain the potentiality of this analytical approach, a study addressed to evaluate

the best firing configuration for an existing tangentially pulverised coal (p.c.) fired utility

boiler using Syngas (synthetic gas from gasification of biomass or wastes) as reburning fuel is

presented. Reburning is an in furnace combustion modification technology for NOx control.

By staging the introduction of the air and the fuel, an environment is created where NOx

generated by the combustion of the main fuel is subsequently reduced by the hydrocarbon

radicals arising from the reburn fuel under reducing atmosphere conditions.

In the first phase of the study the combustion system supplied with p.c. has been

experimentally characterised. Data from the experiments have been used to tune the numerical

models whose outputs reproduced with good accuracy the experimental results. In the

following, complying with the plant constraints, different feeding options for Syngas have

been evaluated: straight injection below main burner zone, conventional reburning and lean

reburning. Simulations have shown that Syngas, if properly injected, can improve the

operation of conventional boilers, both in terms of NOx emissions and char burnout control.

Besides, the work demonstrates the usefulness of employing comprehensive computational

environment in process studies of industrial combustion systems.

Key Words:

Pulverised Coal, Syngas, Reburning, Detailed Kinetics

(∗)

Corresponding Author

1. INTRODUCTION

In recent years, increasing attention to the use of renewable and sustainable energy resources

has led to consider, as near term option, the possibility of co-firing Syngas (i.e. synthetic gas

produced by gasification of biomass or wastes) with coal in the existing large-scale pulverised

coal (p.c.) power plants. This solution offers several advantages, e.g. the feasibility to utilise a

large quantity of renewable sources in a higher efficiency power generation system coupled to

lower investment costs, compared to systems supplied exclusively with biomass or Refuse

Derived Fuels (RDF). Particularly, although RDF gasification applied in the field of energy

recovery from wastes is still in its early stages as a large-scale commercial industry, it is

claimed that this technology is as environmentally clean as a state-of-the-art waste incinerator,

that the capital cost of systems based on gasification is comparable with (or even cheaper

than) that of conventional Waste-to-Energy plants (incinerators with energy recovery) and

that, because the electric efficiencies of such systems can be more than 50 per cent higher

than conventional WtE plants, the overall cost of treating waste can be significantly lower.

The candidate to be the most effective way to employ Syngas is the Integrated Gasification

Combined Cycle (IGCC). This technology is based on the combination of a gasification

system with a gas turbine and a steam cycle and has the potential to provide thermal energy to

power conversion efficiencies exceeding 40%. Nevertheless critical for the success of the

IGCC is the maintenance of the gas turbine, which requires Syngas especially free from alkali

metals (less than 0.1 ppm). On the other hand the direct use of Syngas in combustion boilers

allows an higher tolerance for tars, alkali, ammonia, particulate and other impurities and, even

if it is less efficient (about 31%) from the point of view of thermal energy conversion, it may

offer the possibility to achieve savings on both capital and maintenance costs. The former

owing to the option to retrofit existing boilers and to avoid dedicated gas cleaning systems,

the latter on condition that Syngas, if properly injected, may improve the normal operation of

conventional boilers, in terms of rise in efficiency of NOx and char burnout control systems.

The concept is to use Syngas as reburning fuel. To this purpose some of its properties are

suitable. It has a large fraction of inert as N2, CO2 and H2O, so unlike natural gas it can be

injected in boiler without flue gas re-circulated. Further it may contain ammonia which, in

particular condition of oxygen and temperature, is effective in reducing NOx. Its oxidizable

species are mainly CO and H2, this assures a faster reaction with oxygen rather than natural

gas or liquid fuels, but it may penalise the direct reduction of NOx because, among the

reaction paths driving NOx reduction, the contribution of CH radicals coming from reburning

fuel will be secondary. For these reasons and others connected with plant characteristics,

crucial for controlling NOx and char burnout by Syngas co-firing is the design of the feeding

system.

Although many variants of the gas reburn principle have been demonstrated in laboratory or

pilot plants, in practical applications gas reburning, as secondary fuel, can be fed with two

main options: conventional reburning and lean reburning. Conventional reburning involves

firing gaseous fuel (up to 25% of the total heat input) above the primary combustion zone in a

coal-fired boiler. This upper-level firing creates a slightly fuel-rich zone. NOx produced in the

lower region of the boiler is reduced in this “reburning zone” and converted to molecular

nitrogen (N2). Successively overall lean conditions are re-established by the injection of

overfire air in order to complete the combustion.

Lean reburning has been more recently proposed, motivated by process economics, to achieve

comparatively moderate NOx reductions, but at much lower gas input than in conventional

reburn and without the need for an overfire air system to achieve CO and char burnout. In this

technology, natural gas is injected into the furnace at sufficiently low flow rates to maintain

overall fuel-lean conditions. The NOx reburning reactions then occur within the locally fuel-

rich regions formed by the gas injection and mixing process. Mixing between the injected gas

and furnace gas is key to effective NOx removal. CO and char burnout is achieved by the

excess O2 available in the overall fuel-lean furnace gas, without the need for a separate

overfire air system. This overall fuel-lean approach to gas reburning offers the potential to

meet the NOx emissions targets applicable to many installations at lower capital costs and

lower operating costs than are typically associated with conventional gas reburn.

In the present study both the option have been evaluated considering Syngas as reburn fuel of

a tangentially p.c. fired utility boiler. The methodology adopted is based on an integrated use

of furnace probing measurements coupled with different simulation tools: CFD code (IPSE)

for 3D simulation of combustion chambers, PROATESTM

providing a mono-dimensional

model of the convection pass, and chemical engineering model called Reactor Network

Analysis (RNA). The latter consists of an equivalent network of ideal, perfectly stirred,

reactors extracted from the results of CFD simulation by an automatic zoning algorithm.

Detailed reaction mechanisms are then applied over the reactor network and a more accurate

calculation of the combustion yields is performed. RNA is based on a mechanistic approach

to the combustion chemistry. Until now it was applied for the prediction of pollutant emission

of gaseous species (NOx, SOx, CO, H2S, HCl) using detailed reaction schemes; recently it

was extended to include the calculation of char oxidation and ash properties. The whole

methodology represents a powerful comprehensive computational environment that allows

applying the most assessed combustion models to a full-scale simulation of industrial power

plants. The advantage respect conventional modeling consists in the possibility of employing

detailed kinetics, qualified with laboratory research without any simplification, besides CFD

simulations, whose sub-models have been calibrated with pilot facilities testing together with

prior field experience.

Previously literature has been published on coupling CFD modeling of combustion processes

to ideal chemical reactor networks [1, 2, 3, 4]. The present work would bring a further

contribution in this field with the aim to demonstrate that CFD+RNA modeling methodology

is mature for process studies of industrial combustion systems.

2. THE MODELLING APPROACH

A scheme of the modelling approach employed in the process studies of industrial combustion

systems is the following:

• As starting point, some baseline furnace probing measurements are conducted at several

boiler operating conditions to determine in-furnace oxygen, NOx and CO concentrations

as well as temperature distributions. Data derived from the measurement campaign

include daily bulletin from the plant control room showing flow rate and temperature of

the feeds, chemical analysis of gaseous emissions and ashes at the boiler economizer

outlet, fuel composition and fineness, temperature of gas and metal surface at certain

locations in the convection pass. All the data are employed for setting the inlet and the

boundary conditions of the numerical simulations, for tuning the empirical parameters and

for qualifying the predictions.

• A three-dimensional model of the combustion chamber is performed to predict local

temperatures, heat fluxes, flow rates, and concentrations of main species. This is achieved

employing a CFD code (IPSE) over a grid typically including between 50000 and 300000

cells.

• The convection pass is schematised with a mono-dimensional model which utilises

PROATES TM

code for calculating all the heat exchanges between the gas and boiler

fluids [5].

• A chemical engineering model of the boiler is provided. For the combustion chamber it

consists of an equivalent network of idealised reactor elements (up to 600) extracted from

the results of CFD simulation by an automatic zoning algorithm [2]. For the convection

pass the chemical reactor model is designed following the same schematisation adopted

by PROATES TM

.

• Detailed reaction mechanisms including (NOx, SOx, Char Burnout) is applied over the

reactor network (RNA) and a more accurate calculation of the combustion yields is

performed. The kinetic mechanisms typically include some hundreds of chemical species

or radicals and some thousands of chemical reactions for the gaseous phase. The solid

phase includes heterogeneous NO reduction by char and heterogeneous char oxidation

with a detailed population balance (800 size and burnout classes) keeping track of size,

density change and burnout.

3. CFD MODEL DESCRIPTION

For the 3D CFD calculation, the IPSE code is used. It is a finite-volume code in-house

developed by ENEL for the numerical modelling of reacting flows, with special emphasis on

3D simulation of combustion systems. The code solves the Favre-averaged Navier–Stokes

equations for a dilatable fluid, together with mass and enthalpy conservation equations,

transport equations for chemical species and equations of state for ideal gases in the well

established form. The source term due to the heat transferred by radiation is calculated using

the discrete ordinates method in the S4-approximation. For the turbulence, although k-ε

model has been implemented, a simple zero equation turbulence model is usually used in

order to leave greater computational resources to the representation of combustion chemistry.

The coal particles are described by either an Eulerian or stochastic Lagrangian procedure to

integrate the equation of motion and the energy balance, together with the consideration of

physical models. The coal conversion is described in sequence by pyrolysis and char

combustion, considering the particle diameter and density to be constant. For the volatile

release the reaction scheme of Ubhayakar et al. [6] is used. For char combustion a first order

kinetic rate combined with a diffusion resistance is used. The volatile composition is

determined from parallel devolatilization models [7], which indicate the yield composition in

terms of H2, CO, CO2, H2O, O2, CH4 and tars. The combustion of gaseous pyrolysis yields is

modelled with a “quasi-global”’ scheme [8], combining a single irreversible reaction between

each hydrocarbon species (CH4 and tars) and oxygen to form CO and H2, together with a

detailed CO-H2 oxidation mechanism with 8 species and 9 elementary reactions. The

numerical model is based on the solution of transport equations for all chemical species (CH4,

tars, O2, CO2, CO, H2, H2O, OH, O, H), char size classes, enthalpy and the three flow

momentum components. The time discretisation is formulated as explicit for all transport

equations, with the exception of species transport equations, where the convective and

diffusive terms of transport over the cells are treated explicitly, while the source term inside

each cell, due to the finite rate reaction chemistry, is solved implicitly after being linearised

with respect to the mass fraction increments. The solution scheme is transient SIMPLE like,

with the difference that at each time step, the use of a direct matrix inversion algorithm yields

the exact solution of pressure equation. A more detailed description of the CFD model can be

found in [9].

4. RNA MODEL DESCRIPTION

RNA is a computational environment that accommodates realistic chemical reaction

mechanisms, both homogeneous and heterogeneous. Indeed, mechanisms with a few thousand

elementary chemical reactions can be simulated on ordinary personal computers, provided

that the flow structures are restricted to the idealised case of plug flow or perfectly stirred

tanks. Reactor network models significantly reduce the amount of computational time for

chemical kinetics with respect the direct implementation into a three-dimensional CFD code;

however, to represent a helpful tool in dealing with industrial problems these models should

be generated from CFD outputs in an automatic and objective way that does not depend on

the specific case to be modelled. To this purpose a specific algorithm has been developed.

The current algorithm, starting from flow, temperature and chemical species concentration

CFD fields, in relation to a discretized three-dimensional enclosure, performs a regrouping of

the finite volume elements to obtain a desired number of zones, each one geometrically

connected and having homogeneous chemical-physical properties. This task is achieved by

refining the classification of all the cells belonging to the computational domain into several

steps. General and simple criteria for turbulent non-premixed combustion flames have been

fixed to control the ‘‘growth ’’of cell clusters and to evaluate the degree of homogeneity for

the resulting zones. As result, the entire domain is classified in homogeneous connected zones

and each zone is modelled as an isothermal completely stirred reactor (CSTR). The operating

conditions (temperature, volume, flow exchanges) are assigned straight from balance on CFD

fields. The composition of the inlet feeds is specified with realistic species for both the gas

and solid phase. The solution is obtained by reiterative calculation, looping up to

convergence, as the Reactor Networks are fully recycling. A detailed description of the

algorithm is presented in [2] and the information flow is sketched in figure 1. Obviously the

reliability of the simplification depends mainly on the number of reactors required, larger is

the number more computational time is needed. Nevertheless the computational efficiency

can still be increased by wide margin if the code will be ported on PC cluster platform.

3D-CFD Reactor Network

Generation Algorithm

Detailed

Reaction

Chemistry

Calculation

(DSMOKE,

CHEMKIN)

Clustering of Mesh Cells

by ∆∆∆∆T, ∆λ∆λ∆λ∆λ ranges

Further subdivision by

connected zones

Reclassification by

MIXING INDEX

Result: Best Mixed RN for

requested # of connected

zones

Operating Conditions of Reactors

• typology = isothermal CSTR

• volume, temperature, composition of feeds

• flow rates of exchanging streams

Minor Chem.

Species

Concentration

(CO, NOx SOx

H2S, Char

Burnout, etc.)

Local

Stoichiometry

field λ(x,y,z)

Major Chem.

Species

Concentration

Flow field

Temperature

field T(x,y,z)

Figure 1. Scheme of the information flow in Reactor Network Analysis.

5. KINETIC MODEL DESCRIPTION

The gas phase reaction mechanism, like all mechanistic kinetic schemes of some complexity,

is basically formed on a strongly modular and hierarchical structure in which the simplest

reaction sub-mechanisms are necessary to investigate the more complex ones [8]. Since the

description of the comprehensive kinetic mechanisms can not be addressed here, only a brief

list of the encompassed modules is reported below. The core hydrocarbon combustion

module, containing up to twelve carbon atoms, has been elaborated by Ranzi, et al. [10]. The

nitrogen sub-mechanism has been derived by Milan Polytechnic researchers [4] from the

work of Miller and Bowman [11] (1989), Kilpinen et al. [12] and from the developments

proposed by Glarborg et al. [13]. The mechanism describing sulphur chemistry in post

combustion condition has been proposed by University of Leeds researchers [14] and it is

mainly based on the study presented in [15]. The mechanism of the reactions involving Cl-

containing species has been taken from Roesler et al. [16].

The heterogeneous chemistry is coupled with homogeneous gas chemistry with a fundamental

formulation of the mass balance in a CSTR where two phases are present. RNA is based on a

number CSTRs and PFRs interconnected, but a single PFR can be represented in turn with a

series of CSTRs, so efforts have been addressed to develop an efficient numerical solution for

a single CSTR. The heterogeneous CSTR solver developed, accounting for a huge number of

size/burnout classes for char particles, is based on the work of Pedersen et al. [17], but some

of its characteristics are novel: char particle includes its ash forming matter, an integral (rather

than differential) population balance is adopted which is naturally predisposed to include

fragmentation models, a slip between gaseous and solid time contact can be assigned for each

size/burnout class, the system of equations in both gaseous and solid phases are solved at the

same time. A complete description of the model will be shown in a next paper.

For char combustion a 0.5 order kinetic rate combined with a diffusion resistance is used. The

kinetic rate for char combustion has been considered as a function of burnout. Also NOx

reduction on char surface has been included. The values assigned to the model parameters are

exactly those reported in [17]. Of course the initial char reactivity depends on coal properties,

for that reason correlation between standard coal analysis and kinetic constants have been

produced (as shown in figure 2) based on Hurt and Mitchell measurements [18]. Nevertheless

it has been experienced by the authors that if the correlation are adopted to assign kinetic

constants for coals typically used in Italian plants, often it is not possible predicting char

burnout with useful tolerances. At now, the initial char reactivity is specified from calibration

procedures, whereby activation energy parameter is adjusted to match the predicted UBC

emission to reported values for a single set of operating conditions.

Kinetics for the devolatization process were not included in the CSTR solver yet. The volatile

yields are implemented as discrete injections into all CSTRs of the near-burner zones whose

mass balance from CFD coal/char fields gives net release. The nitrogen, the sulphur and the

chlorine contained in coal are released respectively as HCN, H2S and HCl.

2030

4050

6070

80

60

70

80

90

100

110

120

130

65

70

7580

8590

E [kJ/m

ole

]

Carbon co

ntent (%

daf)

Volatile matter (% daf)

2030

4050

6070

80

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

65

70

75

8085

90

A [kgC

/ (m

2 s

Pa

0.5)]

Carbon co

ntent (

% daf)

Volatile matter (% daf)

Figure 2. Correlation for the kinetic constants of the initial reactivity of char-O2 reaction. The

experimental values (■) for a suit of American coals are taken from [18].

6. CASE STUDIED

Fusina Power Station: Plant Description

In order to explain the potentiality of the analytical approach previously described, a study

addressed to evaluate the best firing configuration for an existing utility boiler using Syngas

as reburning fuel is presented. Fusina Unit 3 was chosen for the study. Fusina Power Station

(sited near Venice, north-eastern Italy), consists of four tangentially fired, coal units, for a

total installed capacity of 960 MWe. The 320 MWe Fusina unit 3 is equipped with a low NOx

Concentric Firing System (LNCFS) designed by Alstom Combustion Engineering (formerly

ABB), a Selective Catalytic Reactor (SCR) for final NOx reduction, a flue gas

desulphurisation (FGD) system and an electrostatic precipitator. Coal is fed to five levels,

each supplied by one mill. The secondary air is injected via an arrangements of ports, which

can determine different degrees of staging in the main burner zone. The Concentric Firing

System (CFS) is realised by auxiliary air ports positioned between the coal and oil/gas

nozzles. These ports can be moved horizontally up to a maximum angular displacement of

22° from the alignment with the burner jets to increase the oxygen concentration in the

regions near the boiler walls, in order to protect the furnace tube surface from fireside

corrosion in the reducing atmosphere environment. The overall furnace stoichiometry is

controlled by using multiple levels of Separated Overfire Air (SOFA). Further air staging in

the burner zone can be achieved by opening the Close Coupled Overfire Air ports (CCOFA).

Both SOFA and main windbox injectors have independent vertical tilting capability. The

combustion chamber is 12.8m deep by 10.3m wide, and 42.7m high. In the upper furnace

platens and division panels for intermediate temperature steam superheating are installed. In

figures 3 and 4 schematics of the combustion system and respectively the main windbox

arrangement are reported [19].

COAL NOZZLES

SEPARATED OFA3 levels

CCOFA

CFSConcentric Firing System

Tangential combustion system with coal

nozzles positioned on 5 levels

Concentric Firing System

Figure 3. Schematic of Fusina Unit 3 Combustion System

OFA SEPARATA

CFS

OFA

AUX SUP

OIL/GAS

CFS

COAL

COAL

COAL

COAL

COAL

CFS

CFS

CFS

CFS

CFS

CFS

CFS

CFS

OIL/GAS

OIL/GAS

OIL/GAS

OIL/GAS

AUX INF

OFA

OFA

OFA

SEPARATED OFA

Figure 4. Coal nozzles and air registers in the Low-NOx Concentric Firing System (LNCFS)

with Close-Coupled Overfire Air (CCOFA) used at Fusina Unit 3.

Tuning of the 3D-CFD Model

Gas temperature measurements, carried out by mean of a suction pyrometer at the boiler nose

elevation, were used in order to tune the 3D-CFD model. The combustion configuration

recorded during the temperature measurements was reproduced and the wall fouling factors

were adjusted to reproduce the measured values. The main operating parameters during the

tests, corrected to take into account experimental errors, are given in table 1. Figure 5 shows

the good agreement between the experimental points and the model predictions, confirming

that the model well reproduces the heat transfer inside the combustion chamber.

Coal flow rate 31.4 kg/s

Total air flow rate 316 kg/s

OFA flow rate 57 kg/s

Transport air flow rate 69.4 kg/s

Oxygen at the ECO outlet 3 %, wet

Thermal Input 787 MWt

Primary air/Coal temperature 71°C

Secondary air temperature 295°C

Table 1. Operating parameters during temperature measurements

Figure 5. Comparison between calculated and measured gas temperatures at the boiler nose

elevation.

Evaluation of the kinetic model prediction capabilities

The kinetic model prediction capabilities were evaluated on the basis of the results of a testing

campaign previously undertaken at Fusina unit 3 in order to optimise the performance of the

low-NOx combustion system: SOFA and CCOFA registers were opened in various

combinations, while adjusting the secondary air ports to maintain the windbox pressure at the

reference value of about 180 mm wg. During the testing period a South African coal from a

constant supply was fed to the boiler. For more details on the experimental campaign see

reference [20]. Some combustion configurations experimentally tested were reproduced by

using the CFD+RNA model and the UBC and NOx vs. primary stoichiometry trends were

evaluated. Finally trends obtained by using the model were compared with those

experimentally found. In tables 2 and 3 respectively the coal proximate and ultimate analyses

and the fineness used for modelling are reported. They were derived from measurements

carried out during the testing period from a composite pulverised coal sample from all the

mills.

Ultimate Analysis

Hydrogen % 3.95

Carbon % 65.32

Nitrogen % 1.56

Oxygen % 6.35

Sulfur % 0.47

Proximate Analysis

Ash % 14.65

Moisture % 7.70

Volatile Matter % 22.53

LHV MJ/kg 25.1

HHV MJ/kg 27

Table 2. Coal composition and heating value

1100

1150

1200

1250

1300

1350

1400

0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5

Distance from the boiler front wall [m]

Ga

s t

em

pe

ratu

re [

°C]

Measured

Calculated

Particles remaining on 50 mesh sieve % wt. 0.31

Particles between 50 and 100 mesh sieve % wt. 3.10

Particles between 100 and 200 mesh sieve % wt. 16.30

Particles through 200 mesh sieve % wt. 80.29

Table 3. Coal fineness

In figure 6 the UBC and NOx at the furnace exit predicted by the model in different

combustion configurations are compared with the corresponding experimental values. The

model reproduced with good accuracy the experimental UBC and NOx trends vs. furnace

stoichiometry. In the following the tuned model has been used as predictive tool to evaluate

different feeding options for syngas.

0.75 0.80 0.85 0.90 0.95 1.00 1.050

100

200

300

400

500

600

700

800

900

1000

1100

0

1

2

3

4

5

6

7

8

9

10

11

NO

2 m

g/N

m3@

6%

O2 d

ry

Burner Zone Stoichiometry

NOx measured

NOx calculated

C in ash measured

C in ash calculated

C in

ash

%

Figure 6. Calculated and measured UBC and NOx

7. SYNGAS CO-FIRING CONFIGURATIONS

Complying with the plant constraints, the following syngas injection configurations have been

considered:

1. straight injection below main burner zone: syngas is fed to two separate burners

positioned on the side walls in the lower part of the combustion chamber, below the main

burners (see figure 7).

2. conventional reburning: syngas is injected trought the existing CCOFA ports without flue

gas recirculation. Post combustion air is fed to the SOFA ports.

3. lean reburning: syngas is fed to the existing SOFA nozzles without gas recirculation. No

post combustion air is injected.

A fraction of syngas corresponding to 10% (19 kg/s) of the total thermal input has been

considered. For configurations 2 and 3 two different air feeding options to the main burner

nozzles have been studied. A scheme of the feeding configurations is presented in figure 7.

The main operating parameters used for calculations are given in table 4. Coal fineness and

composition are unchanged from baseline simulations. The composition of syngas is given in

table 5. The simulated configurations are schetched in figure 8.

Figure 7. Schematic of Syngas injection configurations

Coal flow rate 27,5 kg/s

Syngas flow rate 19 kg/s

Oxygen at the ECO outlet 3 % vol., wet

Primary air/Coal temperature 71 °C

Secondary air temperature 295 °C

Syngas temperature 800 °C

Table 4. Operating parameters used for simulations

CO (% vol, dry) 7.7

CO2 (% vol, dry) 13.7

CH4 (% vol, dry) 3.5

H2 (% vol, dry) 14.5

N2 (% vol, dry) 55.6

C3H8 (% vol, dry) 0.2

C2H4 (% vol, dry) 3.0

C4Hy (% vol, dry) 0.02

C5Hy (% vol, dry) 0.01

O2 (% vol, dry) 1.88

H2O (%, wet) 16.5

CHAR (g /Nm3, wet) 52

TAR (g / Nm3, dry) 15.3

NH3 (g / Nm3, dry) 6.60

HCl (g / Nm3,dry) 2.30

H2S (g / Nm3,dry) 1.80

LHV (kJ/kg) 4400

Table 5. Syngas composition and Heating Value

AIR

AIR

AIR + COAL

AIR + SYNGAS

AIR

SYNGAS

AIR + COAL

SYNGAS

AIR + COAL

AIR SOFA PORTS

CCOFA

MB

AIR

AIR

AIR + COAL

AIR + SYNGAS

AIR

SYNGAS

AIR + COAL

SYNGAS

AIR + COAL

AIR

INJECTION BELOW MAIN BURNERS STD. REBURNING LEAN REBURNING

SOFA PORTS

CCOFA

MB

G01

Baseline

OFA

S00

Injection

below MB

zone

RS0

Conventional

Reburning

RS1

Conventional

Reburning

LR0

Lean

Reburning

LR1

Lean

Reburning

AIR 80 kg/s

SYN 0 kg/s

SR 1.21

τ 0.78

AIR 58 kg/s

SYN 0 kg/s

SR 1.21

τ 0.78

AIR 75 kg/s

SYN 0 kg/s

SR 1.21

τ 0.78

AIR 75 kg/s

SYN 0 kg/s

SR 1.21

τ 0.78

AIR 0 kg/s

SYN 18 kg/s

SR 1.21

τ 0.78

AIR 0 kg/s

SYN 18 kg/s

SR 1.21

τ 0.78

AIR 32 kg/s

SYN 0 kg/s

SR 0.91

τ 0.30

AIR 23 kg/s

SYN 0 kg/s

SR 0.99

τ 0.28

AIR 0 kg/s

SYN 18 kg/s

SR 0.92

τ 0.29

AIR 0 kg/s

SYN 18 kg/s

SR 0.92

τ 0.29

AIR 37 kg/s

SYN 0 kg/s

SR 1.32

τ 0.24

AIR 0 kg/s

SYN 0 kg/s

SR 1.32

τ 0.24

Opened Opened Opened Close Opened Close

COAL

31 kg/s

AIR

210 kg/s

SR

0.79

τ

2.2 s

COAL

27.5 kg/s

AIR

203 kg/s

SR

0.90

τ

1.9 s

COAL

27.5 kg/s

AIR

237 kg/s

SR

1.00

τ

2.0 s

COAL

27.5 kg/s

AIR

237 kg/s

SR

1.00

τ

2.0 s

COAL

27.5 kg/s

AIR

275 kg/s

SR

1.16

τ

1.8 s

COAL

27.5 kg/s

AIR

312 kg/s

SR

1.32

τ

1.5 s

SYNGAS

BURNERS Not present

SYN 18 kg/s

AIR 28 kg/s Not present Not present Not present Not present

Figure 8. Simulated configurations

It is worth to stress that in all simulated configurations Syngas is fed to the boiler almost at

the exiting temperature from gasification plant (800 °C). Indeed, if it is possible to avoid an

heat exchanger down to the gasification plant, the energy efficiencies will be increased.

Nevertheless a deeper evaluation of this option would be required.

8. RESULTS AND DISCUSSION

For all the considered cases, the reactor networks generated from CFD simulations consist of

550 CSTRs for the combustion chamber. This number resulted the best compromise between

a quite satisfactory simplification of flow and computational demand. As example, in order to

qualify the accuracy of the schematisation, a comparison between O2 fields calculated by

CFD and by RNA with detailed mechanisms is shown in figure 9.

Figure 9. Contour plot of O2 for two sections of the boiler calculated by CFD with 100000

cells (left side) and by a RNA with 550 CSTRs (right side).

As each CSTR of the network corresponds to a volume inside the boiler, the results of the

kinetic calculations can be represented with contour maps of specific sections. This is shown

in figures 10 and 11, where NOx and UBC simulated by RNA for some configurations are

compared. Nevertheless to achieve an easier understanding of the results, it is more helpful to

show the average values of nitrogen species, C in ash and other key process parameters along

the boiler height (figures 12-17).

G01 S00 RS0 LR1

Figure 10. Contour plot of NO (mass fraction) for a section of the boiler calculated by RNA

for meaningfull configurations.

G01 S00 RS0 LR1

Figure 11. Contour plot of C in ash for a section of the boiler calculated by RNA for

meaningfull configurations.

0 10 20 30

0

50

100

150

200

250

300

350Hopper Main Burner Zone CCOFA OFA

pp

mw

(kg

/kg

)

Height Z (m)

N-fuel

N-NOx

0 10 20 300.00

0.01

0.02

0.03

0.04

0.05

0.06

0.07

0.08

0.09

0.10

0.11

0

10

20

30

40

50

60

70

80

90

100

Hopper Main Burner Zone CCOFA OFA

O2 m

ass f

raction

(kg

/kg

)

Height Z (m)

O2

UBC

UB

C %

0 10 20 300.7

0.8

0.9

1.0

1.1

1.2

1.3

1.4

1.5

1.6

1.7

1.8

1.9

700

800

900

1000

1100

1200

1300

1400

1500

1600

1700Hopper Main Burner Zone CCOFA OFA

SR

(O

x /

Ox s

tec)

Height Z (m)

SR

Temperature

Tem

pe

ratu

re (°C

)

0 10 20 30

0

50

100

150

200

250

300

350Hopper Main Burner Zone CCOFA OFA

pp

mw

(kg

/kg

)

Height Z (m)

N-fuel

N-NOx

0 10 20 300.00

0.01

0.02

0.03

0.04

0.05

0.06

0.07

0.08

0.09

0.10

0.11

0

10

20

30

40

50

60

70

80

90

100

Hopper Main Burner Zone CCOFA OFA

O2 m

ass f

raction

(kg

/kg

)

Height Z (m)

O2

UBC

UB

C %

0 10 20 300.7

0.8

0.9

1.0

1.1

1.2

1.3

1.4

1.5

1.6

1.7

1.8

1.9

700

800

900

1000

1100

1200

1300

1400

1500

1600

1700Hopper Main Burner Zone CCOFA OFA

SR

(O

x /

Ox s

tec)

Height Z (m)

SR

Temperature

Tem

pe

ratu

re (°C

)

Figure 12. Case G01: simulated average

values along the boiler. N-fuel is the sum of

N contained in NH3, HCN, HCNO, CN.

N-NOx is the sum of N contained in NO,

NO2, N2O. UBC is the fraction of C in ash.

SR is the stoichiometric ratio, ie. sum of O

contained in all the species ratio total mass

of O required for the complete oxidation of

HC species.

Figure 13. Case S00: simulated average

values along the boiler. N-fuel is the sum of

N contained in NH3, HCN, HCNO, CN.

N-NOx is the sum of N contained in NO,

NO2, N2O. UBC is the fraction of C in ash.

SR is the stoichiometric ratio, ie. sum of O

contained in all the species ratio total mass

of O required for the complete oxidation of

HC species.

0 10 20 30

0

50

100

150

200

250

300

350Hopper Main Burner Zone Reburn OFA

ppm

w (

kg

/kg

)

Height Z (m)

N-fuel

N-NOx

0 10 20 300.00

0.01

0.02

0.03

0.04

0.05

0.06

0.07

0.08

0.09

0.10

0.11

0

10

20

30

40

50

60

70

80

90

100

Hopper Main Burner Zone Reburn OFA

O2 m

ass f

raction

(kg

/kg

)

Height Z (m)

O2

UBC

UB

C %

0 10 20 300.7

0.8

0.9

1.0

1.1

1.2

1.3

1.4

1.5

1.6

1.7

1.8

1.9

700

800

900

1000

1100

1200

1300

1400

1500

1600

1700Hopper Main Burner Zone Reburn OFA

SR

(O

x /

Ox s

tec)

Height Z (m)

SR

Temperature

Te

mpe

ratu

re (°C

)

0 10 20 30

0

50

100

150

200

250

300

350Hopper Main Burner Zone Reburn OFA

ppm

w (

kg

/kg

)

Height Z (m)

N-fuel

N-NOx

0 10 20 300.00

0.01

0.02

0.03

0.04

0.05

0.06

0.07

0.08

0.09

0.10

0.11

0

10

20

30

40

50

60

70

80

90

100

Hopper Main Burner Zone Reburn OFA

O2 m

ass f

ractio

n (

kg

/kg

)

Height Z (m)

O2

UBC

UB

C %

0 10 20 300.7

0.8

0.9

1.0

1.1

1.2

1.3

1.4

1.5

1.6

1.7

1.8

1.9

700

800

900

1000

1100

1200

1300

1400

1500

1600

1700Hopper Main Burner Zone Reburn OFA

SR

(O

x /

Ox s

tec)

Height Z (m)

SR

Temperature

Te

mpe

ratu

re (°C

)

Figure 14. Case RS0: simulated average

values along the boiler. N-fuel is the sum of

N contained in NH3, HCN, HCNO, CN.

N-NOx is the sum of N contained in NO,

NO2, N2O. UBC is the fraction of C in ash.

SR is the stoichiometric ratio, ie. sum of O

contained in all the species ratio total mass

of O required for the complete oxidation of

HC species.

Figure 15. Case RS1: simulated average

values along the boiler. N-fuel is the sum of

N contained in NH3, HCN, HCNO, CN.

N-NOx is the sum of N contained in NO,

NO2, N2O. UBC is the fraction of C in ash.

SR is the stoichiometric ratio, ie. sum of O

contained in all the species ratio total mass

of O required for the complete oxidation of

HC species.

0 10 20 30

0

50

100

150

200

250

300

350Hopper Main Burner Zone CCOFA Lean Reburn

pp

mw

(kg

/kg

)

Height Z (m)

N-fuel

N-NOx

0 10 20 300.00

0.01

0.02

0.03

0.04

0.05

0.06

0.07

0.08

0.09

0.10

0.11

0

10

20

30

40

50

60

70

80

90

100

Hopper Main Burner Zone CCOFA Lean Reburn

O2 m

ass f

ractio

n (

kg

/kg

)

Height Z (m)

O2

UBC

UB

C %

0 10 20 300.7

0.8

0.9

1.0

1.1

1.2

1.3

1.4

1.5

1.6

1.7

1.8

1.9

700

800

900

1000

1100

1200

1300

1400

1500

1600

1700Hopper Main Burner Zone CCOFA Lean Reburn

SR

(O

x /

Ox s

tec)

Height Z (m)

SR

Temperature

Te

mp

era

ture

(°C)

0 10 20 30

0

50

100

150

200

250

300

350Hopper Main Burner Zone Lean Reburn

pp

mw

(kg

/kg

)

Height Z (m)

N-fuel

N-NOx

0 10 20 300.00

0.01

0.02

0.03

0.04

0.05

0.06

0.07

0.08

0.09

0.10

0.11

0

10

20

30

40

50

60

70

80

90

100

Hopper Main Burner Zone Lean Reburn

O2 m

ass f

raction

(kg

/kg

)

Height Z (m)

O2

UBC

UB

C %

0 10 20 300.7

0.8

0.9

1.0

1.1

1.2

1.3

1.4

1.5

1.6

1.7

1.8

1.9

700

800

900

1000

1100

1200

1300

1400

1500

1600

1700Hopper Main Burner Zone Lean Reburn

SR

(O

x /

Ox s

tec)

Height Z (m)

SR

Temperature

Te

mp

era

ture

(°C)

Figure 16. Case LR0: simulated average

values along the boiler. N-fuel is the sum of

N contained in NH3, HCN, HCNO, CN.

N-NOx is the sum of N contained in NO,

NO2, N2O. UBC is the fraction of C in ash.

SR is the stoichiometric ratio, ie. sum of O

contained in all the species ratio total mass

of O required for the complete oxidation of

HC species.

Figure 17. Case LR1: simulated average

values along the boiler. N-fuel is the sum of

N contained in NH3, HCN, HCNO, CN.

N-NOx is the sum of N contained in NO,

NO2, N2O. UBC is the fraction of C in ash.

SR is the stoichiometric ratio, ie. sum of O

contained in all the species ratio total mass

of O required for the complete oxidation of

HC species.

Case G01 has been taken like baseline, because it represents a typical plant operating

configuration for which experimental characterisation data are available. The boiler is fired

with only p.c. and NOx are controlled by air staging. Simulations show that in the main

burner zone the globally rich atmosphere produces the lowest average concentration of NOx

and the highest UBC level than all the other simulated cases. As shown in figure 12, the

average values of N contained in oxidised species (N-NOx) and N contained in reducing

species (N-fuel) demonstrate that reducing reaction paths are working efficiently, because N-

fuel level is very low. Successively in the CCOFA and OFA zones NOx level diminishes due

to the dilution and the shape became suddenly flat after air injection, demonstrating that,

excepting a slight tendency in producing thermal NOx in the OFA zone, the NO/N2 inter-

conversion chemistry works mainly in the main burner zone. On the other hand C in ash level

at the exit of the main burner zone is the highest owing to poor presence of oxygen.

Chemistry driving char burnout continues in the CCOFA and OFA zones and in the first

banks of the convection pass (simulated but not described here): change in UBC slope denote

the transit from diffusion to chemical regime in char-O2 reactions.

In the case S00 the effect of straight injection of Syngas below the main burner zone is

simulated. That configuration would demand the opening of new nozzles in the combustion

chamber, but it would present the benefit of requiring shorter duct for Syngas feeding. Plots

of figure 13 show the effect on NOx and UBC is the worst among co-fired configurations.

NOx level present in the main zone is enhanced by the higher temperature reached. UBC

emissions are higher because char oxidation is delayed. Both phenomena depend on the way

Syngas oxidation behaves: burning faster than coal, Syngas releases chemical heat more

quickly and, at the same time, it withdraws oxygen demanded by char that reaches the

CCOFA zone with more C in ash.

Cases simulating conventional reburning (RS0 and RS1) differ for the way in which part of

the air is fed in the burner zone: in case RS0 upper offset air nozzles are opened, in case RS1

they are closed and the lacked contribution is addressed to the lower offset air nozzles. The

final effect on NOx and UBC emission is similar, but the shapes of N-NOx and N-fuel plots

show as chemistry acts in a different way. In both cases the reactions of reduction of the NOx

in the main zone are slowed down regarding G01 case, because stoichiometry is greater: that

is shown by the N-fuel peaks enhanced. The difference between RS0 ad RS1 reveals in

reburning zone. Indeed in RS1 case, descending N-NOx shape indicates a reducing chemical

effect, while in RS0 case the shape becomes suddenly flat.

Also lean reburning cases LR0 and LR1 differ for air sharing out: in case LR0 upper offset air

nozzles and CCOFA are opened, while in LR1 they are closed. The shapes of the average

NOx values show as in both cases the injection of Syngas does not globally produce any

conversion to N2. NOx emission values are on top level, nevertheless for that configuration

UBC levels at the exit are the lowest. This suggests there is a wide margin to control NOx

emissions reducing the final excess of oxygen in flue gas. To this purpose further simulations

have been performed for case LR0 uniformly reducing the air flow rate until arriving to a final

oxygen excess of approximately 1%. The results of all simulations are summarised in figure

15: the straight injection below the main burner zone seems to be the lesser advisable use of

Syngas. On the contrary important reductions of NOx can be achieved using Syngas as

reburning fuel respect to the basic configuration (only coal with stoichiometric air in burner

zone). The reductions are of the same level showed by the air staging configuration (OFA)

with only p.c. feed, but the advantage offered by Syngas may consist in keeping UBC level

lower. Particularly lean reburning configurations seem to offer the possibility to control both

NOx and UBC reducing the overall air excess to values of about 1 % of O2 in flue gas without

negatively impacting CO and with fair benefit of energy efficiency.

0 1 2 3 4 5 6 7 8 9 10400

450

500

550

600

650

700

750

800

850

900

OFA exp

(O2 3.9%)

Base exp (O2 3.5%)

S00 (O2 3.4%)

LR0 (O2 3.4%)

LR1 (O2 3.4%)

LR0 (O2 2.7%)

LR0 (O2 1.5%)

LR0 (O2 1%)

RS1 (O2 3.4%)

RS0 (O2 3.4%)

G01 OFA

(O2 3.9%)

NO

x [

mg

/Nm

3 @

6%

O2 d

ry]

UBC %

Figure 18. NOx and UBC predicted by all simulations. Beside case name the O2 % dry vol in

flue gas is reported. The measured value are represented by .

9. CONCLUSION

An integrated methodology for the analysis of industrial combustion processes has been

presented. It consists of an integrated use of furnace probing measurements coupled with

different simulation tools: CFD code (IPSE) for 3D simulation of combustion chambers,

PROATESTM

for the convection pass, and RNA for pollutant emissions and burnout

predictions. The advantage respect to conventional modeling consists in the possibility of

employing detailed kinetics, qualified with laboratory research, without any simplification,

besides CFD simulations, whose sub-models have been calibrated with pilot scale testing

together with prior field experience.

In order to explain the features of this analytical approach, a study, addressed to evaluate the

best co-firing configuration for an existing p.c. fired boiler using Syngas as secondary fuel,

was presented. On the first the prediction capability of CFD+RNA model was qualified

against data from a measurement campaign. Then numerical simulations have been performed

for new feeding configurations.

The numerical analysis suggests Syngas injected by conventional or lean reburning

configurations may result effective in controlling NOx and UBC emission from p.c. fired

boilers. Prediction of NOx level for both the configurations are aligned with those produced

by the boiler fired with only p.c. and OFA, but UBC are definitely lower. That may offer

margin for reducing the air excess. Especially lean reburn configuration seems more suitable

to obtain the lowest air excess with the advantage to increase the combustion efficiency and to

reduce the operating costs of flue gas cleaning systems.

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