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Cost-effective flexibilisation of an 80 MWe retrofitted biomass power plants: Improved
combustion control dynamics using virtual air flow sensors
J. Blondeau, T. Museur, O. Demaude, P. Allard, F. Turoni, J. Mertens
PII: S2214-157X(20)30242-2
DOI: https://doi.org/10.1016/j.csite.2020.100680
Reference: CSITE 100680
To appear in: Case Studies in Thermal Engineering
Received Date: 24 April 2020
Revised Date: 22 May 2020
Accepted Date: 7 June 2020
Please cite this article as: J. Blondeau, T. Museur, O. Demaude, P. Allard, F. Turoni, J. Mertens, Cost-
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Cost-effective flexibilisation of a retrofitted biomass power plants:
improved combustion control dynamics using virtual air flow sensors
J. Blondeau, T. Museur, O. Demaude, P. Allard, F. Turoni, J. Mertens
AUTHORS CONTRIBUTION
• J. Blondeau: Conceptualization, Data curation, Formal analysis, Writing – original
draft;
• T. Museur: Conceptualization, Investigation, Methodology, Writing – review & editing;
• O. Demaude: Conceptualization, Investigation, Methodology, Writing – review &
editing;
• P. Allard: Conceptualization, Investigation, Methodology, Project administration;
• F. Turoni: Conceptualization, Methodology, Funding, Supervision;
• J. Mertens: Conceptualization, Methodology, Funding, Supervision, Writing – review
& editing.
Cost-effective flexibilisation of an 80 MWeretrofitted
biomass power plants: improved combustion control
dynamics using virtual air flow sensors
J. Blondeaua,b,∗
, T. Museurc, O. Demaudec, P. Allardc, F. Turonid, J.
Mertense,f
aThermo and Fluid dynamics (FLOW), Faculty of Engineering, Vrije Universiteit Brussel
(VUB), Pleinlaan 2, 1050 Brussels, Belgium
bCombustion and robust optimization (BURN), Vrije Universiteit Brussel (VUB) and
Université Libre de Bruxelles (ULB)
cEngie Laborelec, Rodestraat 125, 1630 Linkebeek, Belgium
dEUtech Scientific Engineering, Dennewartstrasse 25-27, 52068 Aachen, Germany
eEngie Research, Place Samuel de Champlain 1, 92930 Paris-la Défense, Paris, France
fDepartment of Electromechanical, system and metal engineering, Ghent University,
Technologiepark Zwijnaarde 131, Zwijnaarde, Belgium
Abstract
As they deliver dispatchable renewable energy, biomass power plants are ex-
pected to play a key role in the stability of the future electricity grids domi-
nated by intermittent renewables. Large-scale, biomass-fired power plants are
often retrofitted from coal-fired plants. Such a fuel modification combined with
decreasing pollutant emission limits and higher requirements in terms of load
flexibility can lead to a decrease of the maximum power delivered by the unit.
The limiting factors are partly related to the control systems of those plants.
In this paper, we present the results of the upgrading of a 80 MWe, retrofitted
biomass power plant that was achieved by improving the dynamic control of
the combustion process. Thanks to the addition of virtual air flow sensors in
the control system and the re-design of the combustion control loops, the unde-
sired effects of a recent 10% power increase on NOxemissions were more than
compensated. The accurate control of the local NOxproduction in the furnace
resulted in a decrease of these emissions by 15% with an increased stability. This
study will help increasing the cost-effectiveness of such conversions, and facili-
∗Corresponding author: julien.blondeau@vub.be
Preprint submitted to Case Studies in Thermal Engineering June 11, 2020
tate the development of dispatchable, renewable power units able to contribute
to the grid stability.
Keywords: biomass, power plant, flexibilisation, NOx, virtual sensors
1. Introduction
Hydropower and bioelectricity are the two main dispatchable sources of re-
newable energy. In 2016, they provided 12% and 6% of the gross electricity gen-
eration in Europe, respectively. The two main intermittent renewable sources,
sun and wind power, accounted for 9% and 3% of this gross generation, re-
spectively [1, 2]. In addition to energy storage and demand side management,
the concomitant development of dispatchable and non-dispatchable renewable
energy sources is a key factor to ensure the stability of the electricity grids in
the future [3]. The further development of bioelectricity can be achieved in a
cost-effective manner by taking advantage of the existing assets currently fed
with fossil solid fuels [3, 4, 5, 6]. Over 250 coal-fired, large scale power plants are
currently operated in Europe [3]. Although in decline, the coal power capacity
in construction worldwide still reached 235 GWein 2018 [7]. Retrofitting coal-
fired boilers to biomass combustion is not always straightforward, but can be
most of times achieved through limited adaptations of the existing equipment.
In Europe, large coal power plants were successfully converted to wood pellet
combustion in several countries (Denmark, UK, Netherlands, France, Belgium,
among others) [3, 8]. Although the retrofitted large-scale power plants currently
in operation are fed with conventional wood pellets, the thermal pretreatment
of biomass can improve the physical and chemical characteristics of the fuel
and facilitate such conversions, leading to even more limited retrofitting and
operational costs. It could also broaden the types of biomass resources used
in large-scale power plants (e.g. agricultural residues and energy crops from
marginal lands) by limiting the impact of their less favorable chemical and
physical characteristics [9, 8].
Coal and biomass are both carbonaceous solid fuels: they can be burned
2
in the same types of boilers, the most common ones being grate-fired boilers,
fluidised bed boilers and pulverised-fuel boilers. The latter type largely domi-
nates the existing fleet of large-scale power plants worldwide [10], and it is used
in approximately 50% of the biomass-fired power plants [8]. Coal and biomass
however present some important differences in their physical and chemical char-
acteristics. The first one is the lower heating value of biomass (18 to 22 MJ/kg,
dry ash free basis) compared to coal (26 to 31 MJ/kg) [10]. Injecting the same
thermal power in the furnace of a power plant therefore requires significantly
larger fuel mass flow rates. Some handling or preparation equipment (e.g. the
mills of pulverised-fuel boilers) can therefore limit the thermal input if they
reach their maximum capacity in terms of mass or volume flow rate.
Due its fibrous structure, biomass also presents a lower grindability than
coal. Roller mills are generally used in pulverised-coal boilers to crush the raw
pieces of coal to µm-sized particles (typically 90 wt%<300 µm). When they
are fed with biomass pellets, roller mills can deliver 80 to 90 wt%of particles
smaller than 1mm [8], hence significantly larger than coal particles. The pro-
duced biomass particles also present a large aspect ratio than coal particles.
The settings of roller mills can be adapted to optimise their performances with
biomass, sometimes at the expense of their capacity. Hammer mills generally
show better performances than roller mills with biomass [8]. Their rotating ham-
mers literally cut the biomass fibres, leading to lower particle sizes, although
still significantly larger than coal particles: the largest biomass particles can still
reach 1−3mm [11, 8]. Their aspect ratio is also reduced compared to roller
mills [8]. Whether they are produced in roller mills or in hammer mills, the
larger size and the anisotropy of biomass particles can lead to burnout issues
if their residence time in the furnace is not sufficient [12, 13, 8]. When 100%
biomass firing is applied, it is therefore recommended to reduce the maximum
particle size down to 3mm and to reduce the portion of large particles (e.g.,
<10−15 wt%particles in the size range of 1−3mm) [8]. Even then, ensuring a
complete burnout of biomass particles in a furnace designed for coal combustion
might require a power derating: it decreases the volumetric flow of flue gas in
3
the furnace and hence increases the residence time of the particles [14]. It should
be noted that the thermal pre-treatment of biomass can however make this re-
newable feedstock more suitable for roller mills, leading to limited adaptation
of the equipment [9, 8]. Mild pyrolysis of raw biomass can modify its structure
in such a way that it becomes more brittle. The lower investment required to
retrofit the power plant and the less frequent operational issues can justify the
additional pre-treatment step, although further efforts must be carried out to
reduce the related costs in the future [9, 8].
In addition to their lower heating value and their larger size, biomass par-
ticles also differ from coal in their combustion behaviour and their inorganic
composition. While coal particles emit 5-40% of volatile compounds during
pyrolysis (the first step of combustion), biomass releases 70 to 90% of volatiles
[10]. This strongly modifies the heat release distribution in the flame. This large
volatile content is also the cause for the higher propensity of biomass particles
to create explosive atmospheres, which lead to additional safety requirements
during handling and storage compared to coal [15].
The inorganic composition of biomass also differs from that of coal: although
the ash content of biomass is significantly lower than for coal ( 0.4-3% vs. 1-30%
[10]), which leads to lower particulate matter emissions, the higher concentra-
tions of some inorganic elements, in particular potassium and/or chlorine, is a
major source of operational issues [16, 17, 8]. Lower ash melting temperatures
and higher concentrations of condensable inorganic volatiles are generally ob-
served. They lead to a deposit build-up on the boiler’s heat exchangers in both
the radiative and convective parts (called slagging and fouling, respectively).
In grate-fired and fluidised bed boilers, other mechanisms can also cause bed
agglomeration issues. The main measure that can be taken to avoid such ash-
related issues is to make sure that the flue gas temperatures close to the boiler
wall, in the fuel bed and at the outlet of the furnace (Furnace Exit Gas Temper-
ature, FEGT) are compatible with the characteristics of the fuel. In furnaces
designed for coal combustion, this might also require a power derating. Alter-
natively, fuel blends or additives can be used to improve the ash characteristics
4
and keep a higher FEGT [16, 17, 8]. Thermal pre-treatment can also modify
these characteristics and reduce the needed power derating [9, 8].
Biomass contains less nitrogen and much less sulfur than coal [10]. Hence,
NOxand SOxemissions are expected to decrease after a retrofit, even though
NOxemissions are not only caused by the oxidation of the nitrogen from the
fuel (fuel NOx) but also by the oxidation of nitrogen from combustion air under
high temperature and high O2-concentration conditions (thermal NOx) [10].
Due to the redistribution of the heat release in the flame and in the furnace,
the NOxemission reached after the retrofit of a boiler from coal to biomass are
very difficult to predict [17, 18]. When the retrofit to biomass is accompanied
by a decrease of the legal Emission Limit Values (ELV’s) applied to the power
plant, the production of NOxin the furnace can also become a limiting factor100
and therefore lead to a power derating.
Furthermore, if the duty of the power plant is changed from ensuring base
load to backing-up intermittent renewables, as expected in the future, more
frequent load variations will also cause higher NOxemissions [19]. During fast
transients, the adequacy of the combustion air flow rate compared to the fuel
flow rate is indeed not always guaranteed on the short-term: locally in the
furnace, a temporary higher excess of oxygen can be observed, which results in
a NOxemission peak that will disappear as soon as the new regime is reached for
both the air and the fuel flow rates, with the desired air-fuel ratio. The impact
of such fast transients can be limited by an accurate control of the combustion
process. When both the air and the fuel flow rates are measured and controlled
at the level of the burners, rather than for the whole furnace, the local air excess
can be directly monitored and controlled, in order to limit NOxemission peaks
and other operational issues [20]. This is however rarely the case in pulverised
fuel boilers. An even distribution of air and/or fuel between the burners is often
considered instead, which can lead to large uncertainties on the local air-fuel
ratios [21].
When available, flue gas treatment systems such as Selective Catalytic or
Non-Catalytic Reduction installations (SCR/SNCR) of course limit the impact
5
of a retrofit on the NOxemissions at the stack.
In summary, the retrofit of a coal-fired power plant to biomass combustion
can lead to a power derating when one or several of the following limitations
are faced:
•Limited fuel handling or milling capacity;
•Longer residence time required to ensure particle burnout;
•Lower Furnace Exit Gas Temperature required to avoid ash-related issues;
•Too high NOxemissions in steady state, and/or too high NOxemission
peaks due to larger and/or more frequent load variations.
In this paper, we present the results of the recent upgrading that was carried
out on the boiler of a 80 MWepower plant converted from coal to biomass 10
years earlier, after its average power output was reincreased by 10%. The cost-
effective implementation of virtual air flow sensors in the combustion control
system allowed to do more than compensate the undesired effect of this recent
power reincrease on NOxemissions. Section 2 describes the power plant, the
applied measures, as well as the measurements and data analysis that was car-
ried out. Section 3 compares the performances of the power plant before and
after the upgrade was applied.
2. Methodology
2.1. Les Awirs power plant
Les Awirs power plant, located in Belgium, was entirely converted from
coal- to biomass-firing in 2005 [22]. The boiler is a pulverised-fuel boiler with
tangential firing: the injection of fuel and combustion air occurs at the four
corners of the furnace, at 4different levels, which creates a rotating flow in
the center of the boiler, as illustrated in Fig. 1. Wood pellets are delivered at
the power plant and directly sent to two storage silos equipped with the safety
features needed to fulfil the requirements of the European ATEX legislation
6
(explosive atmospheres). Two hammer mills are then fed by gravity from the
silos. Wood particles smaller than 2mm are entrained by primary air from the
bottom of the mills to the 16 burners. The burners are also fed with secondary
air. The boiler was originally not equipped with a Over Fire Air system (OFA)
for NOxemission reduction through global air staging in the furnace, but the
highest row of burners were put out of service to play the same role, following
the Burner Out Of Service (BOOS) principle [10]. No secondary NOxemission
reduction system is installed (no SCR, nor SNCR). Natural gas is fired during
start-up and allows for the ignition of the biomass particles once the furnace
reached hot conditions. Natural gas also provides a support at low load and/or
during maintenance on one of the two mills, for instance for the replacement of
the hammers.
Figure 1: Tangential firing in a pulverised-fuel boiler [23].
As the boiler was originally designed for fuel oil combustion, and then
retrofitted to coal combustion, the furnace volume is rather limited, even for
coal. The conversion to biomass therefore let some limitations appear: stud-
ies showed that a too short residence time of the largest particles and a high
7
FEGT would have resulted in a large unburnt content in the fly ash and fouling
issues on the first superheaters at high load. The high thermal power density
in the furnace would also have lead to NOxemissions exceeding the new legal
ELV’s, that evolved to the current value of 250 mg/Nm3at 6% O2(monthly
average). A power derating was therefore applied: from the original maximum
gross power of 125 MWeto approximately 80 MWe. In order to reach higher
shares of dispatchable, renewable power, the average power output of the plant
was however increased by 10% ten years after the initial retrofit (from 70 to 77
MWe). This let some limitations appear in terms of NOxemissions: their level
as well as their variations became problematic, as will be showed further. These
issues were very much related to the way the combustion air was controlled.
The total air flow rate injected of the furnace was a function of the total fuel
flow rate, and therefore of the total power output. The combustion air was
supposed to be equally distributed among the burners in service by opening the
primary and secondary air dampers homogeneously. As already stated, such a
global regulation of the air-fuel ratio leads to high NOxproduction zones in the
furnace due to unavoidable unbalances between the burners, even temporarily
[21].
2.2. Virtual sensor implementation
In order to move to a more accurate control of the combustion process and
limit the production of NOxin the furnace, especially during load variations, it
is necessary to monitor and control the air-fuel ratio at the level of the burners,
instead of the whole furnace [21]. This requires that both the fuel flow rate and
the air flow rate are measured for each of the 16 burners. At Les Awirs power
plant, the fuel flow rate per burner was already monitored using pressure drop
measurements in primary air pipes. The relative difference in the pressure drops
is correlated to the total amount of injected fuel to derive individual fuel flow
rates per burners. Alternatively, microwave systems such as the EUCoal flow
system described in [24, 21] can also be implemented. In this case, the main
challenge was therefore to provide the control system with an accurate feedback
8
on the air flow rates per burner in a cost-effective manner to complement the
available fuel flow rates. Rather than installing hardware flow measurements on
every primary and secondary air ducts, virtual sensors were implemented.
The basic idea of a virtual sensor is to take advantage of existing, reliable
measurements such as pressure drops and damper openings and to combine
them with a physical model of the air distribution system to compute the air
flow rates in all ducts. The physical relevance of the model allows for a ro-
bust process control with high dynamic capabilities that are essential during200
load variations.The EUSoft Air system already described in [25, 26, 20, 21] was
implemented at Les Awirs power plant. Each element of the air distribution
system is modelled as an equivalent resistance to the air flow. The non-linearity
of the air flow through the dampers is taken into account by considering sig-
moidal damper flow curves. The system then uses the available physical inputs
(pressure measurements, damper positions and total air flow measurements)
to provide the main control system with the estimated air flow rates to each
burner. Equivalent flow resistances ϕiare then determined, as illustrated in
Fig. 2. Eq. 1 gives the general relationship between a pressure drop ∆p, the
associated equivalent resistance ϕeq and the mass flow rate Q.
Figure 2: Working principle of the EUSoft Air virtual sensors.
∆p=ϕeq Qn(1)
Figure 3 compares the original and the new combustion process control sys-
tem. In the original system, the total thermal load and the total fuel flow rates
were the only parameters used to determine the total air flow and the opening
of the burner air dampers. The Forced Draft Fan was used to deliver the total
air flow required to burn the total amount of fuel injected in the furnace, as
9
a function of the total load. The air dampers were controlled based on preset
openings depending on the total load, in an open loop. If needed, the operators
could adjust the individual damper openings to reduce the NOxemissions by
balancing the combustion air flow rates, without any feedback. During transient
phases, a cross-limiting control ensured that the air excess was always sufficient:
the air flow rate increased first during load increase, and the fuel flow rate de-
creased first during load decrease. In the new control system, the virtual sensors
play the same role as physical air flow measurements and bring additional infor-
mation that can be combined with the fuel flow rates to control the local air-fuel
ratios. The individual burner air flow rates are therefore controlled by the air
damper in a closed loop, in order to obtain the desired local air-fuel ratios, based
on the individual fuel flow rates to the burners. The Force Draft fan controls
the total air flow during start-up only and uses the wind box pressure as set
point in normal operation. The cross-limiting control during transient phases is
now applied at the burner level. Although a significant extension of the number
of inputs and outputs of the control system was required to implement this new
control philosophy, the required investment was of course much more limited
than its hardware alternative.
2.3. Measurements and data analysis
The results showed in Section 3 are based on the continuous monitoring
of the gross power output and the NOxemissions of the power plant. The
power output was measured at the transformer with an accuracy of 0.2%. The
NOxemissions were retrieved from the Continuous Emission Monitoring System
(CEMS) of the power plant, based on extractive Automated Monitoring System
(AMS): the flue gas is sampled and dried, before NOxand O2concentrations are
determined using UltraViolet Resonance Absorption Spectroscopy (UV-RAS)
and paramagnetic devices, respectively. The O2measurement is used to correct
the NOxemissions to the reference oxygen level (6%). The global accuracy on
NOxconcentration taken into account for legal reporting is 20%, taking into
account the flue gas sampling process. The analysers themselves show a much
10
Burner air flows
Total air flow
Total fuel flow
Burner fuel flows
Total thermal load
Air dampers
Forced Draft Fan
Total thermal load
Air dampers
(a) (b)
Forced Draft Fan
Wind box pressure
Air dampers !
openings
Total air flow
Burner air flows
Wind box pressure
Set Point
Equipment
Measurement
Soft sensor
Figure 3: Original (a) and new (b) principles of the combustion process control. The virtual
sensors are used to provide the feedback on the individual air flows sent to the burners.
better accuracy [27].
In order to determine the impact of the virtual sensor control on the overall
performances of the plant, 5years of minute-average data were analysed: 1year
before the 10% power increase, 1year at higher load with the original control
system, and 3years after the implementation of the new control system. In
Section 3, the considered years are therefore referred to as Y−1, Y0, and then
Y1, Y2and Y3.
3. Results and discussions
Figure 4 illustrates the typical evolution of the gross power output and the
NOxemissions before and after the upgrade of the control system (month (a)
and month (b), respectively). While the power fluctuates between 50 and 90
MWein both cases, the NOxemissions are much higher for month (a). They are
11
also much less stable, i.e. much more sensitive to load variations. The monthly
and the daily averaged emission limits were almost reached, which called for
a cost-effective improvement of the system stability. This stability is obviously
reached for month (b), where almost no minute-average NOxconcentration goes
beyond 250 mg/Nm3, even though the load and its variation are comparable to
month (a).
Figure 4: Evolution of the power output [MWe] and NOxemissions [mg/Nm3@ 6% O2]
during a typical month of year Y0(a) and year Y3(b).
The distribution of the minute-averaged power outputs, NOxemissions and
O2concentrations are given in Fig. 5, together with their yearly averages, for
the 5years of data that were retrieved.
A clear shift towards higher power outputs can be seen between Y−1and
Y0(70 to 77 MWe) although with lower load variations, together with a slight
increase of the yearly average NOxemissions (175 to 179 mg/Nm3) and a large
increase of their variations. The lower load variations are correlated with a lower
12
oxygen excess: the O2concentration decreases from 5.7to 4.7vol%in average.
After the implementation of the virtual air flow measurements (year Y1),
the average power output further increased (81 MWe), while the average NOx
emissions decreased drastically (down to 133 mg/Nm3), despite an increased O2
excess in the flue gas (5.3vol%). During years Y2and Y3, the load variations
were gradually brought back to the same intensity as for year Y0, which resulted
in a slight increase of the NOxemissions (up to 160 and 159 mg/Nm3, respec-
tively), due to the higher number of transient phases and the related reincrease
of the average oxygen excess (up to 6.6and 6.2vol%, respectively). In aver-
age, the power output increased by 4% after the implementation of the virtual
sensors, while the NOxemissions decreased by 15%.
4. Conclusions
In this paper, we showed the results of the cost-effective flexibilisation of a 80
MWe, retrofitted biomass-fired power plants that was achieved by implementing
virtual air flow sensors for the accurate control of the combustion process. This
modification of the control system lead to a limitation of the production of
NOxin the furnace during both steady state and transient phases. This was
required by the increase of the NOxemissions observed after a recent 10% power
reincrease, that was also accompanied by larger emission fluctuations. These
undesired effects were more than compensated after the upgrade of the control
system: the power output further increased by 4%, while the NOxemissions
decreased by 15% and exhibited a much more stable behaviour.
These results illustrate that the conversion of existing coal-fired power plants
design for base-load operation into load-flexible biomass-fired power plants can
be partially achieved thanks to smart, ad hoc modifications of the control sys-
tems that can contribute to limit power derating. This will help increasing
the cost-effectiveness of such conversions, and facilitate the development of dis-
patchable, renewable power units able to contribute to the grid stability.
13
NOx
[mg/Nm3]
Power
[MWe]
50
100
100
200
400
0
0
Y-1 Y0Y1Y2Y3
300
O2
[vol%]
12
10
8
6
4
2
0
Figure 5: Yearly distributions (box-plots) and average values (dots) of the minute-averaged
power output [MWe], NOxemissions [mg/Nm3@ 6% O2] and O2concentration in the flue
gas [vol%dry]: 1year before the 10% power increase, 1year at higher load with the original
control system, and 3years after the implementation of the new control system.
14
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