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EXERGY ANALYSIS AND OPTIMISATION OF A DECENTRALISED WOODCHIP-FIRED COGENERATION PLANT

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In this study, comprehensive exergy analysis of a woodchips fired cogeneration system based on organic Rankine cycle (ORC) is presented. The analysis is conducted to an existing cogeneration plant located in Scharnhauser Park, Stuttgart-Ostfildern, Germany that has been in operation since 2003. This study starts with discussing the exergetic analysis methodology, and then defining the most important performance evaluation indicators based on the exergetic analysis (e.g. exergetic efficiency, exergy destruction ratio, relative exergy destruction ratio, and exergy loss ratio). In the first section of the study, the input parameters for a simulation-based analysis is defined. In following sections, a mathematic model of the energy generation process was established. The structure of the model is explained, and the mass and exergy balances of the major system components are discussed in detail. The study shows that the Fixed Bed Combustion Boiler (FBCB) and the ORC evaporator are the main sources of exergy destruction. The FBCB contributes to 58% of the total destructed exergy while the ORC evaporator contributes to 30% of the total destructed exergy. Finally, some recommendations are suggested to optimize the plant’s energy conversion process through reducing the exergy destruction within the FBCB. To achieve higher conversion efficiencies continuous development of the bioenergy systems is needed. The presented study, which is based on experience from a full-scale system, aims to increase the knowledge about the influence of process parameters on the conversion efficiency. The primary and secondary air-flow rates are employed as major controlling parameters to maintain the stability of the combustion and achieve high conversion efficiencies. Simulation results showed that the energy efficiency of the biomass furnace can be increased by more than 2% when an optimized combustion air management system is applied. The study also examines the influence of the fuel moisture on the exergetic efficiency of biomass conversion. Simulation results showed a considerable influence of the fuel moisture on the process efficiency. The evaporation process of the moisture in the combustion chamber absorbs a considerable fraction of the fuel energy, which had an important effect on decreasing the process temperature levels. Finally, clear recommendations were suggested to optimize the plant’s energy conversion process through reducing the exergy destruction within the boiler. The main two factors that seem to improve the exergetic efficiency of the FBCB and consequently of the overall exergetic efficiency of the plant are obtaining woodchips with lower moisture content and decreasing the excess air ratio. Keywords: cogeneration, optimisation, efficiency enhancement, ORC, combustion.
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EXERGY ANALYSIS AND OPTIMISATION OF A DECENTRALISED WOODCHIP-FIRED COGENERATION
PLANT
Rafal Strzalka, Ahmed Aly, Dietrich Schneider, Ursula Eicker
Stuttgart University of Applied Sciences, Schellingstrasse 24, D-70174 Stuttgart, Germany
Tel.: +49/77/8926-2889, Fax: +49/711/8926-5698, Email: rafal.strzalka@hft-stuttgart.de
ABSTRACT: In this study, comprehensive exergy analysis of a woodchips fired cogeneration system based on organic
Rankine cycle (ORC) is presented. The analysis is conducted to an existing cogeneration plant located in Scharnhauser Park,
Stuttgart-Ostfildern, Germany that has been in operation since 2003. This study starts with discussing the exergetic analysis
methodology, and then defining the most important performance evaluation indicators based on the exergetic analysis (e.g.
exergetic efficiency, exergy destruction ratio, relative exergy destruction ratio, and exergy loss ratio).
In the first section of the study, the input parameters for a simulation-based analysis is defined. In following sections, a
mathematic model of the energy generation process was established. The structure of the model is explained, and the mass
and exergy balances of the major system components are discussed in detail. The study shows that the Fixed Bed Combustion
Boiler (FBCB) and the ORC evaporator are the main sources of exergy destruction. The FBCB contributes to 58% of the
total destructed exergy while the ORC evaporator contributes to 30% of the total destructed exergy. Finally, some
recommendations are suggested to optimize the plant’s energy conversion process through reducing the exergy destruction
within the FBCB.
To achieve higher conversion efficiencies continuous development of the bioenergy systems is needed. The presented study,
which is based on experience from a full-scale system, aims to increase the knowledge about the influence of process
parameters on the conversion efficiency. The primary and secondary air-flow rates are employed as major controlling
parameters to maintain the stability of the combustion and achieve high conversion efficiencies. Simulation results showed
that the energy efficiency of the biomass furnace can be increased by more than 2% when an optimized combustion air
management system is applied. The study also examines the influence of the fuel moisture on the exergetic efficiency of
biomass conversion. Simulation results showed a considerable influence of the fuel moisture on the process efficiency. The
evaporation process of the moisture in the combustion chamber absorbs a considerable fraction of the fuel energy, which had
an important effect on decreasing the process temperature levels.
Finally, clear recommendations were suggested to optimize the plant’s energy conversion process through reducing the
exergy destruction within the boiler. The main two factors that seem to improve the exergetic efficiency of the FBCB and
consequently of the overall exergetic efficiency of the plant are obtaining woodchips with lower moisture content and
decreasing the excess air ratio.
Keywords: cogeneration, optimisation, efficiency enhancement, ORC, combustion.
1 INTRODUCTION
The world’s energy demand is steadily increasing and
there are serious concerns regarding the depletion of
fossil fuels and how long fossil fuels can remain
sufficient to meet the world´s increasing energy needs.
On the other hand, climate change is believed to have
several negative consequences on the environment and
human health, which are mainly linked to the increase of
greenhouse gas emissions. Advancing and more efficient
renewable energy conversion systems are one of the most
important prerequisites for the reduction of
anthropogenic climate change.
Among the regenerative energy sources, biomass is
the most important and widely used energy carrier. Today
biomass is most efficiently used in decentralised
cogeneration plants, as they combine high efficiency with
reasonable fuel transport distances. The technologies for
decentralised cogeneration have the unique advantages of
reducing the environmental impact of power generation
and increasing the effectiveness of biomass utilisation
00[2].
The most mature and proven technology for biomass-
based decentralised cogeneration is the ORC process.
Historically, the efficient use of solar energy, geothermal
energy as well as energy from biomass was the main
driver for the development of the ORC technology. The
principle of the ORC process is quite similar to
conventional Rankine Cycle, with the major difference,
that an organic medium (hydrocarbons: such as
isopentane, iso-octane, toluene or silicone oil) is used as
the working fluid. These organic fluids have more
desirable thermodynamic properties at lower pressures
and temperatures, which makes them more suitable for
application in decentralised plants. Considering the
framework conditions given for biomass CHP
applications, silicone oil is the most appropriate working
fluid [3]. The use of silicone oil has the advantage, that
electricity can be produced at lower levels of pressure
and temperature, which leads to significant reduction of
both investment and operation costs [4].
More than 150 biomass cogeneration plants based on
the ORC technology have been installed in Europe, most
of them (about 140 plants) are based on biomass
combustion, of which more than 50 plants feed their
produced heat into district heating networks [4][6]. The
majority (about 85 plants) of the ORC modules have a
power output between 0.2 and 3.1 MWel and are installed
in Germany [7][8].
A practical example for the utilisation of the ORC
technology is the cogeneration plant in Scharnhauser
Park, which covers the main part of the energy demand of
a modern urban settlement located near Stuttgart,
Germany. The 140 ha area comprises residential
buildings with a living space of 130,000 m2 in addition to
48,000 m2 of mixed commercial area [4]. The main share
(80%) of the heat demand of the area is covered by the
cogeneration plant, which works in heat driven mode.
The ORC plant covers also about 50% of the electricity
demand of the settlement with 10,000 inhabitants.
In this paper a comprehensive exergy analysis of a
woodchip-fired cogeneration system is presented. The
exergetic analysis is an efficient tool for optimisation of
energy generation systems. Several examples of exergy
analysis application for a comprehensive optimisation of
power generation units can be found in the literature.
Abusoglu and Kanoglu [9] introduced a very good brief
historical overview on the exergetic analysis and
optimisation. They generally discussed the concept of
exergies of fuels and exergies of products and applied
this concept on the components of diesel engine powered
generation. Yildrim and Gungor [10] conducted exergetic
and exergoeconomic analysis for CHP system with two
diesel engines. Each of the diesel engines set in the
analysed plant produced 5.76 MW of electrical power,
with the steam capacity of each diesel engine in the range
of about 4.5 tons/h. The exergetic performance results
indicate that the diesel engine is by far the most exergy
destructive equipment in the plant. Colpan and Yesin [11]
conducted exergetic analysis for an existing gas/steam
combined cycle cogeneration system (Bilkent plant,
Turkey). They calculated the exergy destructions within
the plant and exergy losses to the environment. Through
the paper’s conclusion, it was stated that thermoeconomic
efficiency can be improved if separate forms of total
exergy of streams (e.g. physical and chemical exergies)
are used. It is worth mentioning that the current study is
based on the total exergy of streams including both
physical and chemical exergies. Al-Sulaiman et al. [12]
performed energy and exergy analyses of a biomass
trigeneration system using an organic Rankine cycle
(ORC). They concluded that the two main sources of the
exergy destruction are the biomass burner (~55%) and
the ORC evaporator (~38%). They finally recommended
that when designing a similar trigeneration system, the
most important components that need considerable care
in their design and selection are the biomass burner and
ORC evaporator.
2 EXERGY ANALYSIS METHODOLOGY
It is notable that the performance of most of the
power plants are discussed from the energy viewpoint
(either during the plant’s designing phase or during its
operation). So the energy efficiency of the plant -and
sometimes of its components- would be introduced as an
indicator for the plant performance, and hence any
suggested optimization would be based on energy
standpoint. While the energy balance mainly consider the
quantity of energy, it ignores the quality of energy. To
elaborate it is clear that there are some forms of energy
(e.g. potential, kinetic, mechanical, and electrical energy)
which are considered as superior energy forms as they
could be fully converted in an ideal process to any other
form of energy. On the other hand, the quality of thermal
and chemical energy depends on various parameters (e.g.
temperature, pressure and chemical composition) of the
energy carrier and of the surrounding environment.
Referring to the previous point, it is obvious that
electricity has a greater quality than low-pressure steam
or a cooling water stream in a power plant. In
thermodynamics, the quality of a given quantity of
energy is characterized by its exergy.
Exergy could be defined as the maximum theoretical
useful work obtainable from an energy conversion system
as this is brought into thermodynamic equilibrium with
the thermodynamic environment while interacting only
with this environment [13][14]. The second law of
thermodynamics tackles a new dimension in addition to
the energy balance by accounting for the real
thermodynamic inefficiencies in processes or systems,
and the exergy concept is really useful to investigate this
aspect. From the exergetic viewpoint, the exergy
destruction (occurring within the system’s boundaries)
and exergy losses (exergy transfers out of the system
which is no longer used in the overall system) accounts
for the real inefficiencies of the considered system.
Among the major causes of exergy destruction are
chemical reaction, heat transfer across a finite
temperature difference, fluid friction, flow’s throttling,
and dissimilar fluids’ mixing [15]. Exergy analysis
identifies the magnitude of thermodynamic inefficiencies
and locates the components that are responsible for such
inefficiencies.
To proceed with any thermodynamic analysis, it is
crucial to appropriately define the system (e.g. system’s
boundaries). System definition is one of the most
important prerequisites for exergy analysis because the
choice of boundaries can determine whether to consider
the effect of heat transfer as an exergy destruction or as
an exergy loss. It is also of great importance to
appropriately define the thermodynamic reference
environment which could be considered (in the context of
exergy analysis) as a large thermodynamic system in
equilibrium, in which the state variables (T0 and p0) and
the chemical potential of the chemical components -
contained in it- remain unchanged when heat and
materials are exchanged between another system and this
reference environment. It is worth mentioning that the
thermodynamic environment is irreversibility-free and
could be assigned with zero exergy value. Throughout
this study the term environment refers to the
thermodynamic reference environment with temperature
(T0) and pressure (p0).
For the performance evaluation of the installed
system, the incoming and outgoing energies are defined
on the basis of the energy of the fuel and energy of
product. It is worth mentioning that the term fuel is used
here in a general sense and is not necessarily restricted to
being an actual physical fuel such as woodchips, coal,
natural gas or oil (e.g. the fuel of an electric motor is the
electric energy stream that drives the motor, and the fuel
of a pump is the mechanical shaft work that drive the
pump). Hence appropriate definition of fuel and product
is crucial for the evaluation of a certain component and of
the overall system. The rules mention in [14] have been
used to define fuel and product (for each component and
for the overall system) in order to evaluate the
performance of the analysed biomass-fired cogeneration
plant.
The thermodynamic properties (shown in Table I)
could be used to define the enthalpy and entropy of each
stream (by using corresponding tables and graphs), which
are used to calculate each stream’s physical exergy
through the equation below:
 = (-) - (-) (1)
Where:
: Physical exergy of  stream, and are the
enthalpy and entropy of the corresponding stream
respectively.
: Reference temperature (taken to be the average
reference environment temperature of 15 °C).
:Enthalpy of the corresponding stream at reference
condition (temperature 15 °C and pressure 1.104 bar).
: Entropy of the corresponding stream at reference
condition (temperature 15 °C and pressure 1.104 bar).
It is well known that all thermodynamic processes are
governed by the laws of mass and energy conservation.
These conservation laws state that mass and energy can
neither be created nor destroyed in a process. On the
other hand, exergy is not conserved but it could be
destroyed by irreversibility within a system [15].
Consequently, an exergy balance must contain a
destruction term that vanishes only in a reversible
process. Furthermore, exergy could be lost when a
material or energy stream is rejected to the environment.
So exergy destruction () and exergy loss ()
indicate the inefficiencies associated with the irreversible
processes at the  system component. By choosing the
components’ boundaries at reference temperature (,
the value of () will be always zero, as all the
thermodynamic inefficiencies within the component will
be charged to the component’s exergy destruction (),
and consequently for  component of an energy
conversion system.

  

(2)
Where:

: exergy of the  component’s fuel

: exergy of the  component’s product
The exergy balance for an overall energy conversion
system could be expressed as

  

 
(3)
Where:

: exergy of the overall system’s fuel

: exergy of the overall system’s product

: exergy destruction throughout the overall system

: exergy loss of the overall system (includes the
exergy flow rates of all streams rejected by this
system to the surroundings)
The chemical exergy of the working fluids’ streams
have been calculated using GATEX software, which was
developed by Frank Cziesla in 2002 at the Institute for
Energy Engineering (TU Berlin) and is based on the
THESIS calculation package. It uses the CODATA-
Values (programmed by Andreas Krause, 1994) for the
material properties of ideal gases and the new
formulation of the IAPWS-IF97 for water/steam data. As
the composition of the thermal oil is constant, then its
chemical exergy can be neglected during the exergy
analysis.
Exergetic efficiency () is one of the most important
indicators used for performance evaluation based on
exergetic analysis. An appropriately defined exergetic
efficiency precisely characterizes the performance of a
system or a system’s component from the thermodynamic
viewpoint. The exergetic efficiency is defined as the ratio
between exergy of product and exergy of fuel, so for the
 component
= 

= 1 - 

(4)
And for the overall system
 = 

= 1 - 


(5)
There are a couple of other important exergy related
performance indicators that could be introduced as
outcomes of proper exergy analysis, such as the exergy
destruction ratio ( ), the relative exergy destruction
ratio (
) and the exergy loss ratio ( ). Improving an
energy conversion system according to exergetic
analysis’s results means improving components with the
highest values of the exergy destruction 
or the
exergy destruction ratio ()
 = 

(6)
Alternatively, the component exergy destruction rate
can be compared to the total exergy destruction rate
within the system (
) leading to the relative exergy
destruction ratio (
)

= 

(7)
Where:

: exergy destruction throughout the overall system
(summation of exergy destruction within all system’s
components, 
  
)
The exergy loss ratio ( ) can be defined similarly,
by comparing the overall exergy loss to the exergy of the
fuel provided to the overall system
= 

(8)
3 MODEL DEVELOPMENT
3.1 Input data
As the exergy analysis is conducted to analyse an
existing plant, some of the input data are directly
measured during the plant’s operating conditions and
some other values are provided from plant simulation
conducted at the Centre of Applied Research (zafh.net),
Stuttgart University of Applied Science [16]. There are
two main parameter categories that should be identified,
namely thermodynamic properties of each working
fluid’s streams (including temperature, pressure and mass
flow rate) and chemical composition (e.g. of woodchips,
air and flue gases).
Table I: Streams’ properties (mass flow rate, temperature and pressure) and exergies (physical, chemical and total)
Stream
M
[kg/s]
T
[°C]
p
[kPa]
Eph
[MW]
Ech
[MW]
Etotal
[MW]
Woochips
1
0.91
15.0
101.4
0.00
9.10
9.10
Air
2
3.66
15.0
101.4
0.00
0.01
0.01
3
18.0
104.0
0.01
0.01
0.01
4
140.0
102.7
0.08
0.01
0.09
Flue gases
5
4.57
436.0
100.0
0.69
0.12
0.80
6
291.0
99.0
0.38
0.12
0.50
7
202.7
98.0
0.29
0.12
0.41
8
211.7
104.0
0.30
0.12
0.42
Thermal oil
9
36.6
300.0
115.0
17.13
0.00
17.13
10
240.0
113.0
12.79
0.00
12.79
11
240.1
135.1
12.80
0.00
12.80
12
250.0
135.0
13.02
0.00
13.02
Silicone oil
13
17.00
257.4
660.0
3.19
0.04
3.23
14
222.0
15.1
2.20
0.04
2.24
15
121.0
11.2
1.07
0.04
1.11
16
75.6
10.2
0.18
0.04
0.22
17
76.1
781.0
0.20
0.04
0.24
18
168.5
731.0
1.05
0.04
1.10
District heating water
19
61.86
56.0
360.0
0.70
0.16
0.86
20
72.0
350.0
1.30
0.16
1.46
The current study was conducted under the
assumptions that the CHP system operates in a steady-
state condition, ideal gas principles are applied to air and
flue gases, the combustion reaction is complete, the
kinetic and potential exergies are neglected, and the
temperature and pressure of the reference thermodynamic
environment are taken as =288 K and = 101.4 kPa.
The main molar (mass fraction) compositions of
woodchips has been set 50.00% carbon, 43.00% oxygen,
6.20% hydrogen, 0.30% nitrogen and 0.05% sulphur
(chemical exergy of dry ash free woodchips is 18.6
MJ/kg). The main molar compositions of air is 75.04%
nitrogen, 22.99% oxygen, 1.28% argon, 0.63% water
vapour and 0.05% carbon dioxide. The main molar
compositions of flue gases has been considered 65.53%
nitrogen, 14.00% water vapour, 12.10% carbon dioxide,
7.50% oxygen and 0.87% argon. The physical and
chemical exergy of each stream will be calculated
according to the method described in the methodology
section. Table I shows the physical, chemical and total
exergy of each stream in MW.
3.2 Model structure description
A mathematical model of the cogeneration plant was
developed in order to analyse the exergetic system
performance. For the exergetic analysis of the plant
performance, the mathematical description of the plant
could be simplified into 16 components, namely: Intake
Air Fan (IAF), Exhaust Fan (EXF), Thermal Oil Pump
(TOP), Silicone oil Pump (SOP), Generator (GEN), Air
Preheater (APH), Fixed Bed Combustion Boiler (FBCB),
Thermal Oil Economizer (TOECO), Evaporator (EVA),
Turbine (TUR), Recuperator (REC), Condenser (CON)
and four Motors (Motor 1 to Motor 4). Besides the
woodchips (stream 1), there are 5 other working fluids
namely air (stream 2 to 4), flue gases (stream 5 to 8),
thermal oil (stream 9 to 12), silicone oil (stream 13 to 18)
and district heating’s water (stream 19 and 20).
The structure of the mathematical model was based
on the principle of operation of the cogeneration plant,
where the energy produced through woodchip
combustion is transferred via thermal oil cycle to the
ORC process. Thermal oil is used as a heat transfer fluid
because the temperature required for driving the ORC
process (thermal oil feed temperature around 300°C) can
be achieved while operating the thermal oil boiler
practically at atmospheric pressure, this means that no
constant boiler supervision is needed. Just after the ORC
evaporator, the silicone oil is expanded through the
turbine which is directly connected to the generator.
Subsequently, the expanded silicone oil passes through a
recuperator before it enters the condenser. The
condensation of the working fluid takes place at
temperature level which allows the heat recovered to be
utilised for district heating. The liquid working fluid then
is pressurized through the feed pump, passes the
recuperator and returns to the evaporator.
Figure 1: Wood-fired ORC cogeneration plant
According to the structure and mode of operation of
the cogeneration plant shown in Figure 1, 20
thermodynamic streams (their exergies are labelled as
through
) and 11 electromechanical streams (their
exergies are labelled as

through

, as the
electromechanical work is just pure exergy) were
defined. MATLAB was used to solve the equations of the
mathematical model.
The system boundaries should be well defined to the
model, it is clear from the schematic that the system has
three main inlet streams (woodchips, air and the
incoming district heating water), and three outlet streams
(net electrical power, exhaust flue gases and the outgoing
district heating water). Therefore, the inlet streams are
mathematically defined as:

  
 
 
(9)
and the outlet streams are mathematically defined as:

  
  
 
(10)
consequently, the overall system exergy of the fuel is:


 
(11)
the overall system exergy of the product is:

 

 
(12)
the overall system exergy loss is:


(13)
3.3 Main components of the mathematical model
The two main elements of the mathematical model
are mass balance equations and energy balance equations.
The mass balance for individual components is given by
(
=
). Simply, the mass flow of the incoming
stream(s) is equal to the mass flow of the outgoing
stream(s). Exergy balances were defined by identifying
the exergy of fuel (
) and exergy of product (
) of
each component.
3.3.1 Fixed bed combustion boiler
The mass balance equation (14) for the fixed bed
combustion is written below. The mass flow rate of the
bottom ash was neglected, as it is absolutely insignificant
compared to mass flow rates of other streams.
Figure 2: Inlet and outlet streams of the boiler

+
+ 
= 
+ 
(14)
Referring to the stream numbers in Figure 2, the mass
balance equation could be written as follows:
+
+ 
=
+
(15)
Bearing in mind, that the exergy rate of the bottom
ash is neglected and its exergy loss is considered as a part
of the exergy destruction within the component, the
exergy balance of the boiler could be introduced as
follows:

= 
+ 
 
=
+ 
 
(16)
Referring to stream numbers in Figure 2, the exergy
balance equation could be written as follows:
=   =  (17)
3.3.2 Evaporator, turbine and condenser
The mass balance equation for the evaporator could
be written as follows:
Figure 3: Inlet and outlet streams of the evaporator

+ 
= 
+ 
(18)
The equation assumes that the mass flow rate of the
evaporator´s inlet streams (incoming thermal oil and
silicone oil) are equal to the mass flow rates of the outlet
streams from the boiler and the turbine (outgoing oil and
silicone oil). The exergy balance equation for the
evaporator can be established as follows:

= 
 
=
 
(19)
referring to the symbols in Fiqure 3, the equation could
be written as follows:

= 

= 

(20)
The silicone oil vapour streams to the turbine after
the evaporator. The streams of the turbine are presented
in Figure 4.
Figure 4: Inlet and outlet streams of the turbine
The mass balance equation for the turbine can be
written as follows:

= 
(21)
The mass balance equation was established in order
to verify if the mass flow rate of the turbine’s inlet stream
(incoming silicone oil) is equal to the mass flow rates of
the turbine’s outlet stream (outgoing silicone oil). The
exergy balance of the turbine could be introduced as
follows (refer to Figure 4)

= 
 
= 
 
(22)

= 
= 
(23)
The inlet and outlet streams of the condenser are
presented in Figure 5.
The mass balance equation for the condensation of the
working medium was established as follows:

+ 
= 
+ 
(24)
Figure 5: Inlet and outlet streams of the condenser
This equation verifies, within the mathematical model, if
the flow rate of the inlet streams of the condenser
(incoming silicone oil and incoming district heating
water) are equal to the mass flow rates of the outlet
streams (outgoing silicone oil and outgoing district
heating water). The exergy balance of the condenser
could be introduced as follows (based on stream labels in
Figure 5):

= 
 
= 
 
(25)

= 

= 

(26)
4 RESULTS AND DISCUSSION
The results of the exergy analysis are presented in
Table II. For each component of the system the
calculation results describe the exergy of fuel (
),
exergy destruction (), the exergy of product (
),
exergy destruction ratio ( , relative exergy
destruction ratio (
) and efficiency ().
Table II: Exergetic analysis results for each component of the cogeneration plant.
Compo-
nent



[MW]

[MW]

[MW]

[%]

[%]
[%]
FBCB
 
 
 
8.384
4.276
4.108
46.96
58.00
49.00
EVA
 

 
4.340
2.204
2.136
24.20
29.90
49.21
TOECO
 

 
0.306
0.089
0.217
0.97
1.20
71.03
CON

 

 
0.890
0.289
0.601
3.17
3.92
67.55
APH
 
 
0.090
0.016
0.075
0.17
0.21
82.52
REC

 

 
1.131
0.273
0.859
2.99
3.70
75.90
TUR

 

0.991
0.203
0.788
2.23
2.75
79.52
SOP


 
0.021
0.003
0.019
0.03
0.03
87.78
TOP


 
0.017
0.002
0.015
0.02
0.03
87.88
EXF

 
0.009
0.001
0.008
0.01
0.01
92.95
IAF

 
0.009
0.001
0.008
0.01
0.02
86.07
GEN


0.788
0.016
0.773
0.17
0.21
98.00
Where: FBCB fixed bed combustor, EVA evaporator, TOECO thermal oil economiser, CON condenser, APH air
preheater, REC recuperator, TUR turbine, EXF exhaust fumes, IAF intake air fan, GEN generator.
According to the results obtained by mathematical
modelling of the plant operation, the overall exergy of the
fuel is 13.040 MW, and the overall exergy destruction
throughout the system’s components is 11.227 MW, the
overall exergy loss is 0.504 MW, and the overall
system’s exergy of product is 1.309 MW. Consequently,
the overall exergetic efficiency of the CHP plant is
10.04%. A graphical representation of the exergetic
efficiency of each component is illustrated in Fig. 6, and
the relative exergy destruction ratio of each component is
shown in Fig. 7.
Figure 6: Relative exergy destruction ratios of
cogeneration plant components (water content 50%,
=1.8)
Figure 7: Exergetic efficiency of cogeneration plant
components (water content 50%, =1.8)
The results presented in Figures 6 and 7 show clearly
that the boiler and the evaporator are the components
with the lowest exergy efficiency of 49%. Together the
both cogeneration plant components are responsible for
about 88% of the total exergy destruction within the
whole system. The boiler contributes to about 58% of the
total destructed exergy, while the ORC evaporator
contributes to about 30% of the total destructed exergy.
According to the results of the exergy analysis, the
boiler and the evaporator are the two most important
plant components to be optimised in order to reduce the
overall exergy destruction within the system. Therefore, a
simulation based plant optimisation was carried out in
order to improve the overall exergetic efficiency of the
conversion system.
4.1 Optimisation analysis
Based on the results of the exergy analysis, the
biomass boiler was defined as the plant component with
the highest exergy destruction ratio. Therefore, the
exergy efficiency enhancement of the furnace was set as
the main goal of the optimization measures at the
analysed cogeneration plant. A mathematical model for
biomass combustion systems in medium power range,
which was developed at the University of Applied
Sciences Stuttgart [17], was applied in order to define the
optimisation potential of the analysed plant. The
combustion model is based on the mathematical
description of each step of the burning process and allows
a precise determination of the system parameters, which
are required for improvement of the plant operation. The
influence of the fuel moisture and combustion air
management settings on the plant performance were
investigated within the scope of the optimisation analysis.
Because fresh cut wood chips are used as
combustible at the plant, the relatively high water content
of the fuel can negatively influence the plant
performance. Drying of the combustible is a widely
applied optimisation measure in order to enhance the
burning system performance. Therefore, the lowering of
the fuel moisture and its impact on the exergetic
efficiency was investigated in the course of the
optimisation analysis.
Three fuel water content levels (50%, 35%, 20%) and
their influence on the plant performance were analysed.
The Figure 8 shows the exergetic efficiency of the plant
components when wood chips with a water content of
20% were used as combustible. If compared with the
results presented in Figure 7, it can be seen that the
exergetic efficiency of the furnace increases by 5% if
woodchips with a water content of 20% are used as
combustible.
Figure 8: Exergetic efficiency of cogeneration plant
components (water content 20%, =1.8)
Another important optimisation possibility for
performance enhancement of biomass combustion
appliances is the exact adjustment of the combustion air
supply to the specific requirements of each step of the
combustion process. Generally speaking, if too much air
is fed to the combustion chamber, the efficiency of the
process will decrease, because high quantities of the
atmospheric nitrogen must be heated up in the
combustion chamber. If not enough combustion air is fed
to the furnace, than the combustion will be incomplete
and the result will be an increase of the pollutant
emissions as well as a drop in the plant efficiency.
In order to determine the influence of the combustion
air supply on the exergetical efficiency of the plant, three
air to fuel ratios (2.2, 1.8, 1.4) and their influence on the
plant performance were analysed. The Figure 9 shows the
exergetic efficiencies of the plants components if the
combustion system operates with an air to fuel ratio of
1.4. In comparison to the results presented in Figure 7, it
FBCB; 58,0%
EVA; 29,9%
CON; 3,9%
REC; 3,7% TUR; 2,8%
TOECO; 1,2% Others; 0,3%
APH; 0,2%
98
93
88
88
86
83
80
76
71
68
49
49
010 20 30 40 50 60 70 80 90 100
GEN
EXF
TOP
SOP
IAF
APH
TUR
REC
TOECO
CON
EVA
FBCB
Exergetic Efficiency (_ ) in [%]
98
89
88
88
87
87
80
76
77
68
49
54
010 20 30 40 50 60 70 80 90 100
GEN
EXF
TOP
SOP
IAF
APH
TUR
REC
TOECO
CON
EVA
FBCB
Exergetic Efficiency (_ ) in [%]
can be seen, that the plant efficiency increases to 50.5%
if an air to fuel ratio of 1.4 is achieved.
Figure 9: Exergetic efficiency of cogeneration plant
components (water content 20%, =1.4)
5 CONCLUSION
The study presents a comprehensive analysis of a
CHP system along with its essential components. The
methodology described in the paper is applicable for
biomass combustion based energy generation systems
and allows for the determination of improvement
measures with the highest optimization potential. The
methodology and the results of the study can be
beneficial in the analysis and design of similar systems.
The exergetic performance assessments presented in the
publication are made in terms of exergetic efficiency,
exergy destruction ratio, relative exergy destruction ratio
and exergy loss ratio.
The main concluding remarks drawn from the results
of the presented study are listed below:
The overall exergetic efficiency of the CHP
system is obtained to be about 10% (the overall
exergy destruction through all the system’s
components is 11.23 MW, the overall exergy
loss is 0.50 MW, and the overall system’s
exergy of product is 1.31 MW).
The exergetic efficiency of the FBCB is 34%,
and it represent the component where the
highest exergy destruction within the CHP
system occurs (8.15 MW).
The exergetic efficiency of the EVA is 49%,
and it represent the component with the second
highest exergy destruction (2.19 MW).
The FBCB and the EVA are responsible of
almost 93% of the overall exergy destruction
within the CHP system (the FBCB contributes
to 73% of the total destructed exergy while the
ORC evaporator contributes to 20% of the total
destructed exergy).
A mathematical model for the biomass combustion
appliance was used to optimise the energy conversion
process at the plant through reducing the exergy
destruction within the fixed bed boiler. The main
optimisation results are described below:
The presented methodology allows for the
determination of influence of different settings
of operational parameters on the exergetic
efficiency of each plant component.
The reduction of fuel water content from 50%
to 20% results in an increase of the exergetic
efficiency of the furnace from 49% to 54%.
The reduction of the air to fuel ratio from 2.2 to
1.4 results in an increase of the exergetic
efficiency of the furnace from 48% to 50.5%.
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[1] Strzalka, R., Ulbrich, R., & Eicker, U. (2010).
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[2] Zahoransky, R. A. (2009). Energetics - systems
for energy conversion (in German). Wiesbaden:
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[3] BIOS Bioenergiesysteme GmbH, Electricity
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[5] Technical Report 07A03061e, “List of Recent
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98
97
88
88
84
75
80
76
75
68
49
50
010 20 30 40 50 60 70 80 90 100
GEN
EXF
TOP
SOP
IAF
APH
TUR
REC
TOECO
CON
EVA
FBCB
Exergetic Efficiency (_ ) in [%]
[15] Tsatsaronis G., Chapter 2 Exergy Analysis,
Script/Class Notes, Energy Engineering,
Master Program, Institute of Energy
Engineering, Technische Universität Berlin,
Winter Semester 2013-2014.
[16] Erhart T., MWe biomass ORCCHP power
plant Setup and evaluation Scharnhauser Park,
Ostfildern, Germany, Centre of Applied
Research zafh.net, Stuttgart University of
Applied Science, 2009.
[17] Strzalka, R., Erhart, T., & Eicker, U.: Analysis
and optimization of a cogeneration system
based on biomass combustion. Applied
Thermal Engineering (50) 2013 , pp. 1418-
1426.
7 AKNOWLEDGEMENTS
The research work was founded by the German
Federal Ministry of Food and Agriculture and by the
Agency of Renewable Resources (FNR).
The authors acknowledge Professor George
Tsatsaronis and Professor Tetyana Morozyuk at the
Institute for Energy Engineering at TU Berlin for
permitting the use of GATEX software.
... Based on the results of the exergy analysis, the boiler is the most important plant component to be optimised in order to reduce the overall exergy destruction ratio within the system. Therefore a simulation based optimisation was carried out in order to improve the overall exergetic efficiency of the conversion system [54]. On the basis of the exergy analysis results, the exergy efficiency enhancement of the biomass furnace was defined as the main goal of the optimisation measures at the analysed cogeneration plant. ...
... Wood-fired ORC cogeneration plant model[54]. ...
... Relative exergy destruction ratios of the plant components[54]. ...
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Energetics -systems for energy conversion
  • R A Zahoransky
Zahoransky, R. A. (2009). Energetics -systems for energy conversion (in German). Wiesbaden: Vieweg + Tuebner.
Assesment of CCHP systems based on [15] Tsatsaronis G., Chapter
  • D Maraver
  • A Sin
  • J Royo
  • F Sebastian
Maraver, D., Sin, A., Royo, J., & Sebastian, F. (2013). Assesment of CCHP systems based on [15] Tsatsaronis G., Chapter 2 Exergy Analysis, Script/Class Notes, Energy Engineering, Master Program, Institute of Energy Engineering, Technische Universität Berlin, Winter Semester 2013-2014.