Operational and Design Strategies to Improve PFBC Power ... - circe

Operational and Design Strategies to
Improve PFBC Power Plant Efficiency
Luis M. Romeo & Cristóbal Cortés
Centro de Investigación del Rendimiento de Centrales
Eléctricas (CIRCE)
Diego Martínez
Escatrón PFBC Powerplant
ENDESA, S.A.

Operational and Design Strategies to Improve PFBC Power Plant
Efficiency
Luis M. Romeo and Cristóbal Cortés, CIRCE, Spain
Diego Martínez, ENDESA, S.A., Spain
Summary:
This paper presents a semiempirical model of a pressurised fluidised bed combustion power plant. It is well-
know that one of the options to retrofit existing steam plants is to build a PFBC power plant that take
advantage of the existing steam turbine and increase the life of the power plant. The retrofit is based in the
replacement of the conventional old boiler of pulverised fuel by a pressurised fluidised bed boiler. Also, a gas
turbine is incorporated to the system. The steam generated drives the old turbine unit and the combustion
gases drives the gas turbine. Both the original efficiency and the total load improve in the retrofit.
The model has been developed to simulate and predict the Escatrón (Spain) PFBC power plant behaviour
under different operating conditions. Good agreement has been found between the computed results and
actual plant data at different operational regimes for the most important variables of the power plant. The
main aim of this model is to study different strategies to improve the efficiency in the power plant. This paper
describes the model developed, the strategies to improve efficiency, as well as its results, and as
conclusions, point out the improvements and perspectives for future work

1. Abstract
Nowadays the state of the art of PFBC technology lies halfway between the demonstration stage in units of
intermediate size (72-79 MWe) and the commercial availability of larger scale plants. The operation of
existing power stations has demonstrated that several points remain widely open to improvements. Due to
fuel quality effects and the use of retrofitted plants, the PFBC power plant efficiency presently demands
significant improvements. Likewise, the high energy efficiencies offered by the PFBC concept had not been
completely demonstrated. To overcome these difficulties and further develop the technology a semiempirical
model of a pressurised fluidised bed power plant has been developed. The model has been validated with
actual plant data, being able to predict the Escatrón (Spain) PFBC power plant behaviour under different
operating conditions. It has been widely tested to study not only the fluidised bed behaviour, but also the
influence of fluidised bed variables in the rest of the power plant. Good agreement has been found between
the computed results and actual plant data at different operational regimes for the most important variables
of the power plant (i.e. in-bed temperature profiles, fuel feed rate, entrainment rate, heat exchangers and
heaters thermal behaviour, steam and gas mass flow rate, gas and steam turbine power and power plant
efficiency). The main aim of this model is to study different strategies to improve the efficiency in the power
plant. These strategies include: the improvement of sootblowing schedules of external heat exchangers; air
preheating system optimisation; selection of operational set-points that bring the highest efficiency;
evaluation of the efficiency improvements due to design changes (changes in retrofitted steam turbines and
heat exchangers, natural gas reburning, selection of different types of coal). This paper describes the model
developed, the strategies to improve efficiency, as well as its results, and as conclusions, point out the
improvements and perspectives for future work.
2. Introduction
Pressurised fluidised bed combustion (PFBC) is an emerging technology for electricity generation, now being
implanted across Europe. Its main advantages are the capability of handling low rank fuels, an excellent
environmental performance, a high energy efficiency and a moderate specific investment in comparison with
other advanced coal combustion concepts. Presently, two coal PFBC power stations are operating in Europe
(Escatrón, Spain and Vartan, Sweden), and one unit is under construction at Cottbus (Germany). Specific
details on the concept, design and operating experience have been summarised by Menéndez et al (1987),
Anderson and Jansson (1991), Alvarez Cuenca et al. (1995) and Botros (1995).
The operation of existing power stations has demonstrated that several points remain widely open to
improvement. In this respect, the inherently complex behaviour of the fluidised bed is logically the main
concern. Apart from erosion and fouling effects, experience with given coal types has revealed unexpected
modifications of bed density and heat transfer potential, bed temperature unevenness and variations of
sensibility to operating conditions. The consequences of strong changes in the coal supply or combined
combustion with other fuels have not been experienced yet.
The future role of PFBC power plants in the market of electricity generation will depend on their ability to
mach the required load easily and with high efficiency in a scenario of variable demand and high
competitiveness. Therefore, one of the keys of the PFBC technology is to predict and to control how

proposed changes in process variables, in the power plant design or in the selection of fuels, would affect
the performance and efficiency of the overall power plant.
Unfortunately, the modelling of pressurised fluidised bed combustors has achieved up to now only a limited
success. As a consequence, fluidised bed models of practical application are based on experiment. The high
demand of empirical information has been traditionally satisfied by means of experimental, small scale
facilities. Among the great variety of reported studies, the papers of Chen and Saxena (1977), Chakraborty
and Howard (1981), Selçuk and Ozkan (1984), Horio et al. (1985), Azevedo et al. (1989) and Bellgardt et al.
(1987) are excellent contributions in the field of atmospheric fluidised bed combustion. Pressurised
laboratory beds have been used by Rajan and Wen (1980), Saxena (1988) and Mingyao et al. (1987),
references which constitute the basic wealth of fundamental data specifically concerning PFBC technology.
The empirical character of these developments raises logically the question of the actual applicability of the
results and correlations to full scale equipment. Based on Grimethorpe PFBC experimental facilities, Hoy et
al. (1987) have found a diagram for gas and steam turbine loads as a function of several process variables
(bed height, bed temperature and air by-pass). They also concluded that a detailed analysis of part-load
characteristic con be made only for a particular plant. This paper present the analysis and results for a large
scale plant, the 80 Mwe Escatrón power station in Zaragoza (Spain).
This paper presents the results of an comprehensive survey of empirical correlations, most of them one-
dimensional, applicable to PFBC. The model is adjusted in order to reproduce process and in-bed data taken
at Escatrón PFBC power station (Spain) under a wide range of operating conditions. This represents the
novelty of using full scale information to validate empirical correlations, the objective being to draw specific
conclusions on the reliability of empirical PFBC modelling. As we will discuss in detail, the overall agreement
is good and the limitations can be adequately identified.
3. Model Description
In order to have a realistic power plant simulation, the input variables have been chosen to be the ambient
conditions, the characteristic of the fuel, the main control set-points and the cycles deterioration of equipment
performance (i.e. fouling in heat exchangers). The model is composed of three modules, describing steam
and gas turbines and the pressurised fluidised bed.
3.1 STEAM CYCLE.
The simulation and behaviour of steam cycles is a well-know subject, having been previously studied in
detail (Stodola and Loewenstein, 1945; Spencer et al., 1963). However, the cycle arrangement in a PFBC
power plant possesses special features demanding a particular treatment. For the heat-exchangers, a
standard simulation have been chosen, taking into account the fouling thermal resistance in condenser
(cooled by water from a river) an economiser (fouled by flying ash). Fouling is considered as an external
input, due to the difficulty in its accurate prediction.
In the steam turbine, stage temperatures and pressures are calculated as linear function of the main steam
flow rate; the flow rate to the heaters are calculated with the steam turbine flow coefficients (Cotton and

Schofield, 1971; Cooke, 1985). Figure 1 compares measured and calculated steam turbine loads. Negligible
deviations are observed with maximum differences of 1% for the whole operating range.
3.2. GAS CYCLE.
Concerning the gas turbine, a common characteristic of many component-based simulation studies is the
lack of information about the component maps. Consequently, techniques have been proposed to overcome
this difficulty (Saravanamutto and McIsaac, 1983). In this work, the simulation is based on experimental data
correlated thought dimensionless numbers (Shepherd, 1956). In spite of the difficulties in modelling gas
turbines, the results show good agreement. The gas cycle is composed by a two-spool gas turbine with the
high-pressure turbine connected to the high pressure compressor and the alternator. In addition to the
general lack of design information (non-availability of gas turbine characteristics) with the PFBC lay-out,
simulation is even more involved. For these reasons, the use of well-know methods (Cohen et al, 1983;
Bathie, 1983) are unsuitable. One of the best solution is to combine dimensional analysis with experimental
data. Dimensionless analysis has been previously used to build universal compressor characteristics
(Saravanamuttoo and MacIsaac, 1983; Muir et al., 1983). The theoretical basis of dimensional analysis for
gas turbines is well-know (Shepherd, 1956), although some modifications have been made in this case. The
fouling of the low-pressure compressor (LPC) makes their coefficients decrease with time. Since the fouling
evolution is complex, it has been taken as an external output modifying the corresponding compressor
characteristic. Moreover the control by variable guide vanes makes the turbine coefficients inappropriately
variable under constant operating conditions. A new and more stable coefficient has been found and is used
to calculate the gas output temperature (Romeo et al., 1997). A comparison between the measured and
calculated gas output temperature is show in figure 2. Small differences of 5 ºC are observed.
3.3. PRESSURISED FLUIDISED BED COMBUSTOR.
The simulation of the pressurised fluidised bed combustor is based on a previous work (Romeo et al., 1994)
but some modifications have been made to enlarge the operational load range simulated and to take into
account a bed height larger than design. The model is composed of five submodels describing fluid
dynamics, elutriation, sulphur retention, coal combustion (char and volatile matter) and heat transfer. One-
dimensional behaviour is assumed, i.e. all the predicted values are interpreted as the average of different
heights. The combustor has been divided in six cells. Five of them model the bed and the last represent the
freeboard zone. This scheme result from an equilibrium between accuracy, data available to validate the
results at different heights, and calculation time. The division also reflects the differences in density of steam
tubes along the bed.
Fluid dynamics is evaluated with correlations taken from different contributions. Minimum fluidisation velocity
is evaluated after Chitester et al. (1984); bubble diameter as the average of Darton et al. (1977) and Rowe
(1976) correlations; bubble velocity is evaluated with the equation of Kunni and Levenspiel (1977); finally the
bubble and void fraction is calculated according with Kunni and Levenspiel (1990). Average bed and single
cell density are calculated using the estimated void fraction and the average particle density.
Char combustion is evaluated as the oxidation of carbon, whereas the combustion of volatile is calculated by
subtracting the char energy content from the coal heating value. Given the data available on Escatrón coals,

this is the only option in our case, if only a first approximation to the physical reality, and has been used
previously under the same circumstances of lack of experimental data (Hyppänen et al, 1991). Since char
combustion can be considered to be uniform, the evolution of volatile matter becomes a controlling factor,
specially when firing low rank coals. A special treatment has been given to this question, having developed a
new scheme for the spatial calculation of the heat release (Romeo et al., 1997)
Heat transfer from the fluidised bed to the surface of internals is due to three contributions: particle
conduction, gas convection and thermal radiation. Particle conduction is commonly divided into two different
contributions, which are the limits of the correlation formulae for “small” and “large” particles (Botterill, 1989).
In fluidised beds with small particles (up to approx. 800 µm), this is the main contribution, whereas gas
convection dominates with large particles and in pressurised beds. The Chekansky correlation (Botterill,
1989), is adopted for conduction mechanisms due to small particles. The contribution of large particles is
calculated with the correlation of Denloye and Botterill (1978), tested under pressures up to 10 bar. Gas
convection heat transfer is calculated by the Nusselt type equation of Baskakov et al. (1973) which has been
widely tested (George and Welty, 1984; Gomar and Renz, 1991). Radiation in fluidised beds begins to be
significant at approximately 600 °C and its effect increases with particle size and decreases with tube pitch.
The radiation heat transfer coefficient is evaluated with the effective emissivity ε e of Baskakov et al. (1973).
In accordance with this use of heat transfer correlations, overall heat transfer coefficients are estimated as
the sum of the three contributions. Since the area of non-immersed tubes is small for the operating
conditions of the Escatrón bed, freeboard heat transfer is calculated as the result of gas convection and
thermal radiation, neglecting the contribution of entrained particles (Clark et al, 1989; Golan et al, 1980).
Figure 3 shows a comparison between the steam mass flow rate data and the computed results. With a wide
range of operating conditions (75-95% maximum load), only small deviations, about 4% of the value, are
observed. Fig. 4 shows the results for the average bed density, also exhibiting the same level of agreement
for a large variation of this variable. The integrated model consists in the coupling of the three modules
above described, intended to predict the most important plant variables. The simulation exhibits a good
agreement with experimental data. As an example, figure 5 shows a comparison between computed results
and measurements for the overall plant load in performance test. Although, in two cases, deviations are
around 3 MW, in most cases deviations up to 2 MW are observed and can be reasonably accepted in such a
wide operational range.
4. Strategies to Improve Efficiency.
The practical importance of the model stems from it uses as a tool in evaluating design and operational
changes. Many details of the PFBC plant technology still demand a dedicated study, specially those that
concerns the efficiency and availability improvements. The following list gives some examples of studies that
have been or are being undertaken with the aid of the plant simulator:
(i) Optimisation of the on-load cleaning schedule of the economiser, which affects plant efficiency
and steam turbine load.
turbine load.
(ii) Possibility of increasing cyclone cooling, quantification of their influence in reduction of gas

(iii) Reutilization of a low-pressure heater, in order to improve steam cycle efficiency
(iv) Evaluation of plant performance and efficiency at partial load operation
4.1. ECONOMISER
Depending on the ash and sulphur content of the coal and the behaviour of the cyclones, small particles (<
10 μm) are no collected by cyclones and, after passing thought the gas turbine are slowing down at the
economiser, where are stuck between the fins of the heat exchanger tubes. These ashes need to be
removed and cleaned from the economiser by means of an on-load cleaning schedule due to the heat
transfer from hot gases to water decrease with economiser fouling. The simulation has allowed to optimise
the cleaning schedule and to quantify the improvements in both, load and power plant efficiency.
The most important conclusions of a detailed study show that a non-effective cleaning may means important
losses of load and efficiency. A long or inefficient on-load cleaning schedules or even the non-cleaning
suppose a lost up to 0.9 % in efficiency and 1.4 MW in the steam turbine due to a increase in gases
temperature of 50 ºC in chimney, table 1.
UA (kW/ºC) Steam Turbine
Power (MW)
Gases Temp.
Chimney (ºC)
Power Plant
Efficiency (%)
Clean Economiser 340 63.0 196.0 34.12
Foul Economiser 140 61.6 245.5 33.20
Table 1. Comparison between the power plant behaviour with a clean or foul economiser. Simulation results.
For this reason a detailed analysis of the economiser and the sootblowing design are needed to take
advantage of the hot flue gases from the gas turbine (400 ºC). The economiser must be carefully designed to
be capable of reducing the gas temperature up to 170 ºC or near the acid point of the gases and be easily
cleaned by compressed air of steam. That means not to have fins or at least, not very close each other to
minimise the ash stuck between them which reduce the efficiency and the power produced by the steam
turbine. The lost of efficiency due to a “bad” design join with a inefficient on-load cleaning schedule is around
1.1% in power plant efficiency and 1.6 MW, table 2.
UA (kW/ºC) Steam Turbine
Power (MW)
Gases Temp.
Chimney (ºC)
Power Plant
Efficiency (%)
Clean Economiser 500 63.3 185.0 34.32
Foul Economiser 140 61.6 245.5 33.20
Table 2. Comparison between the power plant behaviour with a clean and good designed and a foul and bad designed
4.2. CYCLONE COOLING
economiser. Simulation results.
Another study that has been undertaken with the simulatior is the possibility of increasing cyclone cooling in
order to reduce cyclone ash sintering and its associated plant unavailability. The temperature has a
important influence in the sintering of the ash in cyclones so, a decrease in temperature is believed to reduce

the possibility of sintering formation in cyclones, that means a reduction of problems of unavailability.
Important aspects are the quantification of the subsequent reduction in gas turbine load and efficiency of the
plant. Depending of the temperature reduction by cyclone cooling the lost in gas turbine load is around 0.6
MW each 10 ºC of temperature reduction. The efficiency decrease is approximately 0.15 % with the same
temperature reduction. The reduction in unavailability can not be estimated, although is clear that a bigger
temperature reduction a bigger availability obtained. A reduction of 10 – 20 ºC is believed to be enough to
notice the effects in sintering reduction, but in this case a practical study should be needed to take any
conclusion.
4.3. OPERATING PARAMETERS
Partial load and changes in operating conditions have also influence in efficiency. There are some variables
to match a required load: mean bed temperature and bed height can be modified, and also the air flow from
the gas turbine compressor. In the particular case of PFBC mean bed temperature changes have more
influence that bed height or air flow changes, both in efficiency and load. Approximately, in the whole
operating range a variation of 10 ºC in the mean bed temperature means a variation of 1.8 MW in load (1.1
MW in the steam turbine and 0.7 MW in gas turbine). The efficiency changes are from 0.16 up to 0.2 % with
the same temperature variation, with more influence at reduced loads, table 3. Changes in bed height has a
smaller influence in load, 0.7 MW each 10 cm of height changes up to a bed height of 3.5 m., and above the
tube bundle (3.55 m) just 0.3 MW with the same height variation. Variations in efficiency are also smaller.
Mean Fluidised
Bed Temp (ºC)
Steam Turbine
Power (MW)
Steam Turbine
Power (MW)
Steam Turbine
Power (MW)
Power Plant
Efficiency (%)
825 58.1 11.9 70.0 33.37
835 59.2 12.6 71.8 33.57
845 60.4 13.2 73.6 33.75
855 61.5 13.8 75.3 33.91
Table 3. Influence of the mean bed temperature in the behaviour of the PFBC power plant. Simulation results.
With the help of the model an important conclusion has been addressed respecting the air flow rate. The
best operating strategy to reduce losses of efficiency is to use the minimum air needed for a uniform and
complete coal combustion (around 2.0 – 2.5 % oxygen content in the gases to gas turbine). In spite of it is
believed that an increase in air flow rate would improve gas turbine load and power plant efficiency due to an
increase in gas flow to gas turbine, the results of the simulator conclude the opposite. An increase of 2.0 kg/s
of air compressed has not a effect in the power plant load, just a small increase in steam turbine and a
decrease in gas turbine, with a efficiency reduction of 0.2 %. This is because the power needed to compress
air depends on the r.p.m. of the gas turbine compressor to the power of three, while the power produced in
the gas turbine is linear with the gases flow. Moreover, if the control variables of the pressurised fluidised
bed remains constant, a bigger air flow means a lower gases temperature, which influences to the gas
turbine to reduce load. So, it is concluded that a variation in air flow must be followed by a variation (in the
same direction) of the fluidised bed control variables.

Conclusions
The overall simulation of a PFBC power plant has been developed. The model is capable to predict the most
important variables of the power plant, i.e. bed temperature profiles, steam and mass flow rate, steam and
gas turbine power, power plant efficiency. All of them have been compared with experimental data under
different operational conditions and good agreement has been found. For Escatrón design data and in the
best conditions, the model predicts a efficiency of 35 % and a maximum load of 78.2 MW which are very
close to the real design data, although the model has been build with operation data. These results also
depends on the coal used and the fouling of different equipment.
With the aid of the simulator, plant studies and analysis to improve efficiency continue, aimed to the
improvement of plant efficiency and availability, through the precise evaluation of proposed operational and
design changes. Further developments of the model are required to solve problems related to the practical
needing of optimising power plant performance. And nowadays in an scenario of variable demand the
optimisation is specially important at reduced loads.
Acknowledgements
This research has been fully supported by Endesa, S. A. Mr Alfonso Ruiz, director of Escatrón PFBC power
station, Dr. Emilio Menéndez, head of the R&D department of Endesa, S.A., and Mr. Diego Martínez, head
of the R&D department at Escatrón are gratefully acknowledged for making possible the project and for all
the facilities provided. Escatrón power plant personnel is also acknowledged for their useful assistance.
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Calculated steam turbine power (MW)
62
60
58
56
54
52
50
48
48 50 52 54 56 58 60 62
Measured steam turbine power (MW)
Figure 1. Comparison between steam turbine power measured and calculated

390
385
380
375
370
365
360
355
350
350 355 360 365
370 375 380 385 390
Measured gas output temperature (ºC)
Figure 2. Comparison between measured and calculated gas output temperatures
60
58
56
54
52
50
48
Calculated steam mass flow rate (kg/s)
- 5 %
+ 5 %
48 50 52 54 56 58 60
Measured steam mass flow rate (kg/s)
Figure 3. Comparison between steam mass flow rate data and computed results

Calculated average bed density (kg/m 3 )
800
780
760
740
720
700
680
660
640
- 5 %
640 660 680 700 720
740
+ 5 %
760 780 800
Measured average bed density (kg/m 3 )
Figure 4. Comparison between average bed density and computed results
Calculated gross load (MW)
74
72
70
68
66
64
62
+ 2 MW
- 2 MW
62 64 66 68 70 72 74
Measured gross load (MW)
Figure 5. Comparison between predicted and actual plant load

Biographical Information
Speaker : Luis M. Romeo
Company : CIRCE (Center for Power Plant Efficiency Research)
Country : Spain
Luis M. Romeo (Ph. D. Eng.), is Project Manager of the Center for Power Plant Efficiency Research, and
teach Thermodynamics in the Department of Mechanical Engineering, University of Zaragoza.
He gained his professional experiences developing and managing several projects in different power plants
such as the Pressurised Fluidised Bed Combustion Power Plant at Escatrón (Spain) and Teruel Power Plant
(Spain). He worked on R&D projects at Escatrón PFBC power plant (ENDESA, S.A.) since January 1993, in
activities related with efficiency improvements and power plant modelisation, specially in the pressurised
fluidised bed combustor. He solved energy problems for the R+D department of the ENDESA,S.A.´s power
plant, searching and writing more than 40 technical reports about combustion, heat exchange, and steam
and gas turbines in PFBC power plants.
CIRCE (Center for Powerplant Efficiency Research) is a joint Research Foundation sponsored by (ENDESA,
S.A.) (Spain´s largest public utility), ERZSA (Zaragoza Electric Company), the University of Zaragoza and
the regional government of Aragón. It was formally established in 1993, although activities of CIRCE´s
university researcher began in 1981. General objectives of CIRCE are the support of R&D activities in
thermal power stations and energy systems.