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Potential analysis and technical-economic optimization of conversion of steam power plant into combined water and power
Accepted Manuscript Potential Analysis and Technical-Economic Optimization of Conversion of Steam Power Plant into Combined Water and Power M. Amiralipour, R. Kouhikamali PII: DOI: Reference:
S1359-4311(18)37183-7 https://doi.org/10.1016/j.applthermaleng.2019.02.005 ATE 13299
To appear in:
Applied Thermal Engineering
Received Date: Revised Date: Accepted Date:
23 November 2018 16 January 2019 2 February 2019
Please cite this article as: M. Amiralipour, R. Kouhikamali, Potential Analysis and Technical-Economic Optimization of Conversion of Steam Power Plant into Combined Water and Power, Applied Thermal Engineering (2019), doi: https://doi.org/10.1016/j.applthermaleng.2019.02.005
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Potential Analysis and Technical-Economic Optimization of Conversion of Steam Power Plant into Combined Water and Power M. Amiralipoura, R. Kouhikamalib,* a
Department of Mechanical Engineering, University of Guilan, Campus 2 , Rasht, Iran b
Department of Mechanical Engineering, University of Guilan, Rasht, Iran
Abstract The current study deals with a technical-economic analysis of conversion of a steam power plant into a combined water and power (CWP) system. To this end, a steam power plant with nominal capacity of 166 MW is considered and a multi-effect desalination unit is employed for water production. Turbine steam extraction lines are used as motive steam in thermal water desalination process. To thermodynamically analyze the considered system and its components, a mathematical model is presented by describing the equilibrium equations of energy and mass associated with various elements. Then, by considering the total water flow rate and thermodynamic conditions of various points, the steam flow rate of each extraction turbine lines are computed in the design point. After that, the calculated steam flow rates as the input data are utilized to examine the power plant for different conditions of converting to CWP units. A parametric study is performed to analyze the effect of the steam extracted from each turbine extraction on the operation of the power plant and amount of water production. The results show that the high and medium pressure lines corresponding to the production of 8400 and 2000 cubic meters of fresh water per day have the highest and lowest water production capacity, respectively. Moreover, these lines result in losing up 11 and 5.5 MW in net power plants, respectively. Furthermore, an economic analysis is carried out to estimate the cost of water under different production conditions. Finally, by considering the net power and water selling prices as the objective functions, a multi objective optimization is performed to obtain the optimal conditions for each turbine line in the simultaneous production of water and power. Keywords: Steam power plant; Combined water and power; Technical-economic optimization; Potential analysis; Economic Investigation.
1. Introduction With the onset of the energy crisis in the 1970s, developed countries began to investigate new energy systems in order to control the crisis. On the basis of the renewable energy resources, some researchers developed new systems to improve the traditional ones and then studied their efficiency. In developing countries, some factors such as climate change, hot and dry summers and high population growth have led to a rapid increase in electric power consumption and freshwater in recent years. The influences of above*
Corresponding author. [email protected] (R. Kouhikamali). 1
mentioned factors on the performance of power plants have attracted a lot of interests of researchers and governments in Iran to increase their efficiency by developing the co-generation units. Three types of power plants including the gas, steam and combined power plants are responsible for supplying most of the Iran’s electricity. Therefore, converting the gas power plants into water and power co-generation systems has received a lot of attention. By considering long life of the steam power plants and this point that this plants provide about 30% of requiring electricity of Iran [1], a variety of studies was performed on repowering of the old units to increase their efficiency and decrease the thermal wastes. But, studies on converting this type of power plant into co-generation units in Iran are limited. The researches performed on the water desalination market in 2010 were showed an 11% increase in water demand [2]. Water desalination system is an indispensable option to overcome the scarcity of freshwater. Multistage flashing (MSF), multi effect desalination (MED) and reverse osmosis (RO) are considered as well-known processes in this regard. The performance of water desalination units and combined water and power systems corresponding to different conditions and parameters has been extensively investigated in literature [3-9]. For instance, Darvish and Amer [10] used a gas/steam combined cycle to perform a cost analysis on the cogeneration power–desalination plant in Kuwait. A mathematical model for a multi-effect thermal vapor compression desalination system was developed by Amer [11] to examine the performance of considered system and access to its optimized design and working conditions. A hybrid desalination technique was employed by Shahzad et al.[12] to hybridize a MED system. Aberuee et al.[13] investigated the influences of various vital parameters such as the working temperature and solar irradiation on the operational factors and performance of main elements of a multi-generation solar system. Moreover, the optimal working conditions of considered system were determined by employing the Genetic algorithm. On the basis of an experimental study, the performance of a small reverse osmosis unit was examined by Elsayed et al. [14]. In order to analyze the MED, KouhiKamali et al. [15, 16] provided a parametric analysis and optimization by taking the major design parameters into account. They contributed to the field by introducing a new model to predict variables such as heat transfer coefficient, temperature, required surface area, system process design and performance. To study a solar desalination system, Mahian and Kainifar [17] provided the mathematical modeling and experimental investigation. It was illustrated that one can enhance the evaporation rate and consequently freshwater production by employing the low-cost fan with negligible power. Khademi et al. [18] presented the simulation and optimization of a six-effect evaporator utilized in a desalination unit for the steady-state conditions. Ameri et al. [19] investigated the influences of number of effects, vapor pressure, temperature of effects and feed water temperature on performance of a portable thermal system. It was illustrated that the optimum efficiency is a function of the water salt, temperature difference of each effect and feed water temperature. Moreover, it was concluded that increasing the inlet vapor 2
pressure may results in increasing the efficiency. Mathematical modeling and simulation of a multipleeffect evaporators used in the brackish water desalination were provided by Sagharichiha et al.[20]. It was illustrated that for the considered desalination unit, one can improve the gained output ratio value from 3.8 to 7.5 by increasing the effects from 3 to 8. An experimental analysis was performed by Han et al.[21] to examine the effect of preheating and superheating entrained steam on the performance of a thermal vapor compressor entrainment ratio. Shakouri et al. [22] investigated the feasibility of using the thermal desalination unit coupled with a gas turbine for the oil refinery of Lavan Island in Persian Gulf. In this regard, by defining the operation conditions, the minimization of cost of desalination unit was performed through an economic analysis. Maghsoudi et al.[23] contributed to the field by providing thermoeconomic analysis of coupling MED-TVC with a combined cycle power plant. Hosseini et al. [24, 25] carried out economic and optimization analyses on the combined power and water generation units. The desalination unit and its power unit were considered to be MSF and gas turbine, respectively. They used an economic exergy analysis to determine the system’s efficiency. Hanafizadeh et al.[26]employed a multi effect desalination unit to perform a thermo-economic analysis on the combined power and water production in Iran. Ortega-Delgado et al. [27] analyzed a CWP plant composed of a MED and a Rankin cycle. They investigated the effects of thermo-compressor inlet steam pressure and water heat transfer levels of water desalination on system performance. The optimal conditions for the location of the thermo-compressor were determined. Recently, Moghimi et al.[28] proposed an integrated cooling, heating and power and a multi effect desalination for simultaneous producing the fresh water and electricity and refrigeration. They employed a dual-pressure heat recovery steam generator unit to link the Brayton cycle to the water desalination and ejector refrigeration units. Also, He et al.[29] proposed a power-water cogeneration system with single-extracted ORC to have an energy analysis and consequently analyze the effect of extraction parameters on the power generation and water production. Furthermore, some studies on the combined membrane and thermal systems in combination with the power plants are available in the open literature [30-33]. For example, the modified genetic algorithm was used by Wu et al.[34] to provide the optimal configuration and working conditions of power plant and desalination cogeneration units. Also, by proposing a mathematical model for MED-TVC/RO system and employing the genetic algorithm-based multi-objective optimization, Sadri et al.[35] obtained the optimal conditions of considered unit. In order to desalinate the brackish water in Persian Gulf, Mokhtari et al.[36] developed a mathematical modeling for a combined MED-RO system and then provided the thermo-economic and exergy examinations. It was concluded that by employing the gas turbine+MED+RO hybrid units, in addition to supplying the electricity, one can produce enough fresh water for the considered region. Based on exergy accounting approach, Osman A. Hamed [37] provided a thermo-economic analysis to examine the performance of a combined power plant integrated with a hybrid MSF/ RO desalination units. 3
To the authors’ best knowledge, the potential analysis and optimization on the conversion of steam power plant into a CWP system are still unexplored. Therefore, the present study aims to examine the performance of a steam power plant in combination with a thermal desalination unit in Iran from a technical and economic perspective. To select the proper combined structure of the MED and steam power plant in accordance with demand for water and power, a detailed study is performed on the steam of various turbine extraction lines with different conditions for thermal desalination process. In addition, using an economic analysis, the water selling price is estimated. Finally, considering the operating conditions of the system, the co-generation system is optimized through definition of objective functions (water selling price and net power of the steam power plant).Furthermore, in points of view of the steam conditions, the optimal combination of steam power plant and MED unit is presented.
2. System Modeling 2.1. Descriptive Model The considered system consists of a steam power plant and a multi-effect desalination unit. The schematic of the co-generation system is shown in Fig.1. The steam power plant includes boiler, steam turbine at three low, medium and high pressure levels, condenser, five closed heaters (one HP, two MP and two LP), one deaerator and pressure pumps. Six steam lines are extracted from different stages of the turbine to heat the feed water and subsequently increase the power plant efficiency. As illustrated in Fig. 1, the steam of turbine’s extraction lines are divided into two parts. One part of steam enters the heaters and the other parts enter the desalination unit. The steam entered in desalination unit can be varied up to 100% of the capacity of each extraction line, which is finally condensed by losing its heat in the first effect of the desalination unit and then returns from the condenser pump outlet. It should be remarked that since the steam extracted from each extraction line is constant at design points, no change occurs in flow through the steam turbines. In fact, due to a mass balance in the heaters, the temperature of main line of power plant only changes which results in varying the net power of plant. The desalination unit at the present study is assumed a multi effect desalination with five effects condenser and thermo-compressor. The considered desalination unit is a well-known utilizing thermal system in south of Iran.
4
Fig. 1. Schematic of co-generation of power and water
2.2. Mathematical Model A mathematical model is presented to analyze the system and its components thermodynamically. The fully parametric modeling is performed by employing EES Software. In order to model the equilibrium equations of energy and mass, each component of the elements is scripted based on their volume of control on a steady state. In modeling the power plant, the designed parameters are in accordance with Montazer al-Qaem Steam Plant with nominal capacity of 166 MW in Iran. It should be remarked that due to availability of the needed data, this power plant is selected for modeling. On the other hand, since this power plant is similar to the other ones employed in Iran (for instance, Bandarabbas steam power plant), all of the utilized values can be changed to simulate the similar power plants near the salty water resources by employing the methodology presented herein. For steam power plant, by considering the total water flow rate as well as the thermodynamic conditions of various points, the steam flow rate of each extraction turbine lines will be calculated in the design point. Then, the calculated steam flow rates as the input data will be used to analyze the power plant for different conditions of converting to CWP units.
5
2.2.1. Boiler Considering the heat transfer schematically presented in Fig.1, the heat transferred to the boiler is calculated based on the following: (1) The fuel required in the power plant boiler is expressed as below: (2) in which the subscript
denotes the boiler.
2.2.2. Feed Water Heater, Condenser and Pump in Power Plant The presence of heaters and their proper functions have a significant effect on increasing the temperature of water entered to boiler and reducing the amount of consumed fuel. The heater situation and steam of extraction lines corresponding to different stages of turbine depend on the design conditions and power plant outlet. In feed water heaters, three parameters including terminal temperature difference (TTD), drain cooling approach (DCA) and temperature rise (TR) are the functional indicators. It should be noticed that amounts of TTD and DCA depend on the design conditions of heaters under different loads in power plant but, no changes occur in TTD and DCA by varying the temperature. However, for different conditions underlying power plant, TR as indicative of inlet water temperature difference is varied. Considering Fig. 1 and graphical representation of closed and open heaters illustrated in Fig. 2, the coupled energy and mass equilibrium equations of five closed heaters and deaerator associated with the modeled power plant is shown in Table 1(Eqs. (3-8)). Furthermore, equations corresponding to the heat transfer in the power plant condenser and energy equilibrium of pumps can be expressed by Eqs. (9)-(12). Table 1.Energy equilibrium equations in heaters, condenser and pump Equations
Descriptions FWH 1 FWH 2 FWH 3 FWH 4 FWH 5 De-Aerator
(3) (4) (5) (6) (7) (8) (9)
Condenser (10) (11)
6
Pump
Extraction Turbine line
(12)
Extraction line
Steam from cloased heater
Water Deaerator
Water Steam
Water
Water
Fig. 2. Graphical representation of closed and open heaters
2.2.3. Turbine The steam turbine in the power plant studied is a tri-stage turbine (low, medium and high pressure). The mass and energy equations are presented as below: (13) (14) (15) Total outlet power relevant to the plant is written in the following form; (16) The steam flow rate from the turbine extraction lines for the desalination system can be described as (Eqs.(15) and (16)): (17) (18) in which the subscripts “ex”, “he” and “MED” stand for the extraction, heater and multi-effect desalination, respectively. The net power plant
and efficiency of power plant
are obtained as follows (19) (20)
2.2.4. MED Unit Considering the steam extent and condition in water desalination system, MED can be generally divided into three categories. Under the first condition, i.e. MED as low-enthalpy energy source, low pressure and temperature are used as the source of heat. Under the second condition, i.e. MED-MVC, the steam is 7
compressed by a compressor and this state is used when there is no steam in the system. Under the third condition, i.e. MED-TVC, steam derived from middle pressure operates as driving steam in thermocompressor and the thermo-compressor sucks the steam from last effect and mixes it with the motive steam and then transfers the output to the first effect. MED-TVC is commonly used in large scale hybrid systems. In the present research, in order to convert the power plant into power and water cogeneration system, the MED-TVC is employed for the high and medium pressure lines whereas MED process is used for the lowest pressure line. In the process of designing the desalination systems, to express the mass and energy equations, three sub-models including effects, condenser and thermo-compressor must be considered simultaneously. Table 2shows the variables and unknown values of MED. The summation of the variables is equal to 10n+8, which the same number of equations is required to design the relevant system. Table 3 shows the mass and energy equations governing the desalination system. Further explanations on the performance and modelling MED-TVC are presented in[16, 38]. Table 2. MED variables Descriptions Symbol Temperature Total feed water and effect temperatures Temperatures of the steam from each effect Condenser product Total feed water and effect flow rate Inlet steam flow rate Water flow rate, cooling water, motive steam Thermo-compressor suction rate Wastewater flow rate Condenser surface Wastewater concentration Table3. Mass and energy equations in MED Description Mass equilibrium at each stage Salt mass equilibrium at each stage
Equation (21) (22)
Energy equilibrium at each stage
(23)
Total heat transfer rate at each stage
(24)
Total heat transfer coefficient at each stage
(25)
Condenser mass equilibrium
(26)
Condenser energy equilibrium
(27)
Overall condenser heat transfer rate
(28) 8
Total condenser heat transfer coefficient
(29)
Increased boiling temperature difference
(30)
Temperature difference between each step
(31)
Condenser logarithmic temperature difference
(32)
Feed water/condenser temperature difference
(33)
Water flow rate equality at each stage
(34)
Water supply temperature equality with total feed water at each stage
(35)
Overall product equality with total effect product
(36)
Feed water/product flow rate
(37)
Thermo-compressor mass equilibrium
(38)
Gain output ratio (GOR)
(39)
3. Economical Investigation In order to provide an economic model for the considered system, in addition to taking the purchase and maintenance costs into account, the interest rate corresponding to localized conditions should be considered to estimate the water selling price. In addition, the benefits of converting the power plant into water and power co-generation should be estimated economically and technically. It is remarked that although the initial investment as the most significant economic dimension of a co-generation system cannot determine the profitability or risk of funding, but this price plays an important role in decision making. Since the present study considers the operating conditions of the steam power plant, the equipment cost is not considered. The purchase cost of MED with five effects in accordance with the offer proposed by one of the biggest MED-TVC manufacture in Iran can be expressed approximately by the following equation [39] (40) To estimate water selling price in the co-generation system, both initial investment cost and the loss of net power should be considered. In this study, and equal to 0.05
is regarded as the desalination investment cost (Eq.(40)),
as the cost of electricity based on released data by Iran ministry of energy is assumed to be [1].
9
As a result, the water selling price can be calculated using the following equation which includes the variations corresponding to local conditions and Iran interest rate (41) where
signifies the considered maintenance factor and CRF is capital recovery factor which considers
the two variables interest rate (i) and operation years (n). CRF can be expressed as below: (42) It should be remarked that in the steam power plants, the pressure of extraction lines (heaters’ pressure) is usually constant and the extraction steam flow rates are varied. Moreover, the capacity of desalination plant is related to amount of motive steam and its pressure. As discussed before, in the present study, the steam of extraction lines are used as motive steams in the desalination unit. Depending on these steams and the number of effects of MED, the capacity of desalination unit is determined. At a given pressure, increasing and decreasing the number of effects result in increasing and decreasing this capacity, respectively. But, increasing the number of effects leads to increasing the cost. On the other hand, the GOR parameter as the ratio of desalted water-to-motive steam defined in Eq. (39) is increased by increasing the number of effects. However, according to the previously-published work by the same author(s) [38], although more increasing the number of effects leads to increasing the GOR parameter, but no considerable increase is happened in the produced water. Thus, the desalination unit with five effects as an optimal condition is considered in the present study. 4. Optimization Although increasing the steam extracted from any turbine line maybe results in increasing the water production capacity, but it leads to losing the power plant performance. On the other hand, an increase in the production capacity leads to a reduction in the water selling price. Therefore, it is required to perform a multi-objective optimization. In the present study, by selecting the net power of the steam plant and water selling price as two objective functions, first, the required outputs are obtained from EES software in the form of multi-functions, and then the resulting objective functions are optimized using the evolutionary algorithm and an extended code in MATLAB. Obviously, in the present optimization, maximizing the power is consistent with minimizing the water selling price in the co-generation system. Generally, the vector
can be optimized throughout the optimization process: (43)
where
is decision variables vector and
is the objective function vector which should be
minimized or maximized. In the current method, to find the optimal solutions, genetic algorithm is used.
10
4.1. Evolutionary algorithm: Genetic algorithm Genetic algorithms as an iterative and stochastic search strategy are employed to find an optimal solution and imitate in a simplified manner principles of biological evolution. A characteristic of an evolutionary algorithm is a population of individuals, where an individual consists of the values of the decision variables (structural and process variables here) and is a potential solution to the optimization problem. More details about genetic algorithm and its procedure can be found in [40, 41]. The input thermodynamic parameters in modeling of CWP system and the required parameters in computing the purchase equipment cost and economic factors are presented in Tables 4 and 5, respectively. Also, the thermodynamic conditions including the temperature, pressure and steam flow rate of each extraction line corresponding to Montazer-Qaem power plant are presented in Table 6.
Table 4. Input variables in cogeneration system modeling Variable
Value
Unit
Fuel consumption
12
kg/s
Combustion efficiency
87
%
Fuel Thermal Value (LHV)
37000
kj/kg
Pump isentropic efficiency
80
%
Turbine isentropic efficiency
80
%
35000
mg/lit
Product water concentration
0
mg/lit
Feed water temperature
25
c
Desalinations’ recovery coefficient
35
%
Number of MED effect
5
-
Feed inlet water concentration
Table 5.Economic Factors Economic parameters
Value
Interest rate (%)
12
Function year (Year)
20
Operation and maintenance coefficient
1.06
Hours of the system function annually (Hour)
4300
Selling price of electricity
0.05
11
Table 6. Input thermodynamic conditions in power plant modeling Line
Temperature (c)
Pressure (kPa)
Stream flow rate (kg/s)
15
354.6
3308
11.33
16
449
1644
5.25
17
361.1
884
3.87
18
288.4
503
4.36
19
226
280
7.30
20
118.3
85.4
8.16
5
43.59
8.9
97.75
5. Results and Discussion 5.1. Basic Model The results obtained from modeling the power plant in peak capacity are given in Table 7. Moreover, the temperature difference of both sides of the heaters, the power consumption of pumps and net power of the power plant under condition of 100% steam corresponding to five different turbine extraction lines (line15 (HP extractions), lines 16 &18 (MP extractions), lines 19&20 (LP extractions)) for water production are provided in this table.
Table 7. Result of CWP unit Description
Efficiency
Symbol
Unit
Plant Performance
HP heater
IP heaters
line 15
line 16 38.52
LP heaters line 18
line 19
line 20
39.89
37.20
38.62
37.86
37.78
MW
154.09
143.68
148.77
149.18
146.24
145.93
Boiler outlet temperature
C
540.4
489.7
514.5
516.2
501.7
500.2
Total pumps’ net power
MW
2.24
2.44
2.45
2.39
2.36
2.35
C
37.7
0
38.9
38.8
39.3
39.4
C
24.8
21.8
3.2
25.2
25.5
25.5
C
20.7
19
19.9
0
21.06
21.07
C
35.51
32.45
34.01
34.77
0.79
35.91
C
50.49
45. 29
47.95
46.81
44.49
4.01
Power plant net power
FWH1 Temperature Difference FWH 2 Temperature Difference FWH 3 Temperature Difference FWH 4 Temperature Difference FWH 5 Temperature Difference
(%)
12
5.2. Validation Thermodynamic modeling of steam power plant is the most important part of the modeling of the CWP system. To validate the developed model, in the nominal capacity considered for the system and on the basis of the thermodynamics of extraction lines and steam flow rate, the temperature of different lines of power plant are obtained and compared with those of Montazer al-Qaem Power Plant in Iran with same nominal capacity, as given in Table 8. The needed data can be found in [42]. A reasonable agreement can be seen.
Table 8. Comparison between temperatures of different lines of power plant resulted from model and actual data in nominal capacity Line
Model[T(C)]
Montazer al-Qaem[ T(C)] [42]
Error (%)
2
46.23
46.33
0.1
3
96.72
89.33
7.4
4
96.49
90.1
6.4
5
133
126.4
6.6
6
152.7
148.6
4.1
7
177
175.5
1.5
8
201.8
199.6
2.2
9
239.5
235.4
4.1
10
540.4
540.7
0.3
12
540.4
534.6
5.8
5.3. Parametric Analysis Parametric study is performed to analyze the system performance under combined water and power generation. Figs. 3 and 4 illustrate the variation of net power of power plant and fresh water production capacity versus the steam outlet percentage corresponding to various turbine extraction lines, respectively. In accordance with these figures, one can select the proper hybrid structure corresponding to the water and power demands. Also, these figures illustrate the steam extraction modes up to 100% of the capacity of each line. Furthermore, it can be seen that the maximum and minimum water productions belong to HP and one of the MP extraction lines, respectively, so that using the steam from the line15 can lead to generating about 8400-m3 and using the line18 produces about 2000-m3 daily desalinated water. On the other hand, using these lines can lead losing up to 11 MW and 5.5 MW in the net power plant, 13
respectively. Moreover, the importance of positions of heaters as well as the steam flow rate of each line on the amount of water production and loss power are demonstrated in these figures. 154 152
wnet(Mw)
150 148 146
p=33 bar p=16.4 bar p=5.3 bar p=2.8 bar p=0.85 bar
144 142 0
0.2
0.4
0.6
0.8
1
steam outlet percentage(*100%) Fig. 3. The net power of power plant versus the steam outlet percentage corresponding to different extraction lines
water production(m3/day)
10000
8000
p=33 bar p=16.44 bar p=5.03 bar p=2.8 bar
6000
p=0.854 bar
4000
2000
0 0
0.2
0.4
0.6
0.8
1
steam outlet percentage(*100%) Fig. 4. The water production versus the steam outlet percentage corresponding to different extraction lines
14
The temperature rises in the heaters corresponding to various extraction lines versus the steam outlet percentage are illustrated in Fig. 5. It is observed that increasing the steam outlet percentage decreases the temperature difference at the two sides of the heaters, so that at higher steam outlet percentages, it is diminished. 50 p=33 bar p=16.44 bar
40
p=5.03 bar p=2.8 bar
TR(C)
30
p=0.85 bar
20
10
0 0
0.2
0.4
0.6
0.8
1
steam outlet perentage(*100%) Fig. 5. Temperature rise in the heaters versus the steam outlet percentage associated with various extraction lines
In addition to the technical conditions, the proper conditions for converting the power plant into cogeneration system should be determined throughout an economic analysis. Depicted in Fig. 6 is the influence of steam outlet percentage on the water selling price for various turbine extraction lines. By considering this point that the water generation capacity at each line is different and the water selling price is a function of daily water generation, an increase in capacity results in declining trend of selling price. As indicated, the high pressure lines have greater water generation capacity and this can lead to a reduction in water price. It is noted that to determine the water price, the cost of water desalination unit and the loss of power are taken into account. With increasing the amount of steam extracted from each line, more power loss happens. It shows the disadvantage of the electricity sales of the power plant. However, it is observed that the price of water has dropped by reducing the initial purchase price of water desalination unit. It illustrates the importance of this cost on the economic analysis of the simultaneous production systems during the operation.
15
3.4
water selling price($/m3)
3.2 p=33 bar p=16.44 bar p=5.03 bar p=2.8 bar p=0.85 bar
3 2.8 2.6 2.4 2.2 2 1.8 0
0.2
0.4
0.6
0.8
1
steam outlet percentage(*100%) Fig. 6. Water selling price versus the steam outlet percentage associated with different turbine extraction lines 6. Optimization Results In optimization process, the power of steam plant and the water selling price are considered as two main objective functions. The selected variable is the steam capacity of each turbine extraction line which varies from 10% to 100%. Considering the technical and economic considerations, each turbine line can act as the basis for the design of the power plant to become a system for co-generation of water and power. Therefore, the optimum conditions for the use of each lines should be considered. The results obtained from the optimal conditions for using different lines in the water and power cogeneration system are shown in Pareto Diagram (Fig. 7). In this diagram, the initial and the end points indicate the maximum power and the lowest water price. As can be seen, the price increases with increasing power, which indicates a decrease in water production. The specified points are A, B, C, D and M, whose values are shown in Table 9 Given the condition of the diagrams, it can be considered as a compromise point between the objective functions.
Table 9. Optimal values of objective functions at points A, B, C, D and M Point
A
B
C
D
M
Power
148.62
150.7
150.56
149.7
149.5
Cost
1.88
2.09
2.59
3.21
3.23
16
Pareto Front
3.6
Water selling price($/m3)
3.4
M
3.2 D
3 2.8 2.6 2.4
p=33 bar p=16.44 bar p=5.03 bar p=2.8 bar p=0.85 bar
C
B
2.2 2 1.8
A 1.6 142 143 144 145 146 147 148 149 150 151 152 153 154
Power(MW)
Fig. 7. Pareto optimal solutions for water selling price versus net power
7. Conclusion Considering the need of different communities to electric power and freshwater, it is important to analyze and optimize the conditions for the conversion of power plants into CWP systems. The current study was analyzed the technical and economic conditions of the conversion of a steam power plant and the potential of using each turbine extraction line in CWP system. Then, water selling price was estimated and the optimal conditions of each extraction line was specified by defining objective functions of the net power of steam plant and water selling price in the form of Pareto chart. The most important results are as follows:
It was observed that the thermodynamic conditions of the extraction lines and heaters are important in choosing each line in the co-generation system, so that at the studied power plant, the high-pressure line produces about 8,400 cubic meters per day and medium pressure lines produces about 3800and 2000cubic meters of water per day. Also, the low pressure lines produce about 3000 and 2500 cubic meters of fresh water per day.
The role of each heater in the power plant is important. The steam extracted from each turbine line reduces the performance of heaters and consequently results in decreasing the water temperature of the power plant and net power. In investigated power plant, the high pressure line which produces the largest amount of water in the plant, causes a drop of 7.4% and one of the medium pressure line which has the lowest water capacity resulted in a 3.57% power loss in the net power.
17
Economic analysis is necessary to estimate the price of water in the system. Two main parameters "the purchase cost of desalination unit" and "losses from electricity sales of power plants" were considered in determining the price of water. It was observed that, selling prices were lower in higher pressure lines that have the potential to produce more water in comparison with low pressure lines.
The optimum conditions for the use of each turbine extraction line were observed in the simultaneous water and power generation system. Points A, B, C, D, and M with values 1.88,2.09,2.59,3.21and3.23 cubic meters per dollar and 148.62,150.7,150.76,149.7 and 149.5 MW are selected as the compromise points of objective functions in each line.
Compliance with Ethical Standards: The authors declare that they have no conflict of interest.
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[13] M. J. Aberuee, E. Baniasadi, and M. Ziaei-Rad, "Performance analysis of an integrated solar based thermo-electric and desalination system," Applied Thermal Engineering, vol. 110, pp. 399-411, 2017. [14] M. Elsayed, H. Refaey, O. Abdellatif, R. Sakr, and R. Afify, "Experimental investigation on the performance of a small reverse osmosis unit," Journal of the Brazilian Society of Mechanical Sciences and Engineering, vol. 40, p. 218, 2018. [15] R. Kamali and S. Mohebinia, "Experience of design and optimization of multi-effects desalination systems in Iran," Desalination, vol. 222, pp. 639-645, 2008. [16] R. Kamali, A. Abbassi, and S. S. Vanini, "A simulation model and parametric study of MED–TVC process," Desalination, vol. 235, pp. 340-351, 2009. [17] O. Mahian and A. Kianifar, "Mathematical modelling and experimental study of a solar distillation system," Proceedings of the institution of mechanical engineers, Part C: Journal of Mechanical Engineering Science, vol. 225, pp. 1203-1212, 2011. [18] M. Khademi, M. Rahimpour, and A. Jahanmiri, "Simulation and optimization of a six-effect evaporator in a desalination process," Chemical Engineering and Processing: Process Intensification, vol. 48, pp. 339-347, 2009. [19] M. Ameri, S. S. Mohammadi, M. Hosseini, and M. Seifi, "Effect of design parameters on multieffect desalinationsystem specifications," Desalination, vol. 245, pp. 266-283, 2009. [20] M. Sagharichiha, A. Jafarian, M. Asgari, and R. Kouhikamali, "Simulation of a forward feed multiple effect desalination plant with vertical tube evaporators," Chemical Engineering and Processing: Process Intensification, vol. 75, pp. 110-118, 2014. [21] B. Han, Z. Liu, H. Wu, and Y. Li, "Experimental study on a new method for improving the performance of thermal vapor compressors for multi-effect distillation desalination systems," Desalination, vol. 344, pp. 391-395, 2014. [22] M. Shakouri, H. Ghadamian, and R. Sheikholeslami, "Optimal model for multi effect desalination system integrated with gas turbine," Desalination, vol. 260, pp. 254-263, 2010. [23] K. Maghsoudi, M. Aliasghari, and A. Mehrpanahi, "Thermoeconomic investigation of coupling MED-TVC with a combined cycle power plant," Desalination and Water Treatment, vol. 57, pp. 17707-17721, 2016. [24] S. R. Hosseini, M. Amidpour, and A. Behbahaninia, "Thermoeconomic analysis with reliability consideration of a combined power and multi stage flash desalination plant," Desalination, vol. 278, pp. 424-433, 2011. [25] S. R. Hosseini, M. Amidpour, and S. E. Shakib, "Cost optimization of a combined power and water desalination plant with exergetic, environment and reliability consideration," Desalination, vol. 285, pp. 123-130, 2012. [26] P. Hanafizadeh, M. Mirzakhani Siahkalroudi, A. Taklifi, and M. A. Akhavan-Behabadi, "Thermoeconomic analysis of combined power and water production in Iran by multi effect desalination method," Desalination and Water Treatment, vol. 57, pp. 8161-8173, 2016. [27] B. Ortega-Delgado, P. Palenzuela, and D.-C. Alarcón-Padilla, "Parametric study of a multi-effect distillation plant with thermal vapor compression for its integration into a Rankine cycle power block," Desalination, vol. 394, pp. 18-29, 2016. [28] M. Moghimi, M. Emadi, A. M. Akbarpoor, and M. Mollaei, "Energy and exergy investigation of a combined cooling, heating, power generation, and seawater desalination system," Applied Thermal Engineering, vol. 140, pp. 814-827, 2018. [29] W.F.He, F.Wu, Y. P. Kong, T.Wen, J. J. Chen, and D.Han, "Parametric analysis of a power-water cogeneration system based on single-extraction organic Rankine cycle," Applied Thermal Engineering, vol. 148, pp. 382-390, 2019. [30] A. Almulla, A. Hamad, and M. Gadalla, "Integrating hybrid systems with existing thermal desalinationplants," Desalination, vol. 174, pp. 171-192, 2005.
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[31] M. G. Marcovecchio, S. F. Mussati, P. A. Aguirre, and N. J. Scenna, "Optimization of hybrid desalination processes including multi stage flash and reverse osmosis systems," Desalination, vol. 182, pp. 111-122, 2005. [32] M. K. Manesh, H. Ghalami, M. Amidpour, and M. Hamedi, "Optimal coupling of site utility steam network with MED-RO desalination through total site analysis and exergoeconomic optimization," Desalination, vol. 316, pp. 42-52, 2013. [33] H. El-Dessouky, H. Ettouney, H. Al-Fulaij, and F. Mandani, "Multistage flash desalination combined with thermal vapor compression," Chemical Engineering and Processing: Process Intensification, vol. 39, pp. 343-356, 2000. [34] L. Wu, Y. Hu, and C. Gao, "Optimum design of cogeneration for power and desalination to satisfy the demand of water and power," Desalination, vol. 324, pp. 111-117, 2013. [35] S. Sadri, M. Ameri, and R. H. Khoshkhoo, "Multi-objective optimization of MED-TVC-RO hybrid desalination system based on the irreversibility concept," Desalination, vol. 402, pp. 97-108, 2017. [36] H. Mokhtari and M. Sepahvand, "Thermoeconomic and exergy analysis in using hybrid systems (GT+ MED+ RO) for desalination of brackish water in Persian Gulf," Desalination, vol. 399, pp. 115, 2016. [37] O. A. Hamed, "Thermoeconomic analysis of combined power cycle integrated with MSF/SWRO desalination plant," Desalination and Water Treatment, vol. 57, pp. 26552-26561, 2016. [38] R. Kamali, A. Abbassi, S. S. Vanini, and M. S. Avval, "Thermodynamic design and parametric study of MED-TVC," Desalination, vol. 222, pp. 596-604, 2008. [39] F. Company. http:// www.fanniroogroup.com. [40] N. Nariman-Zadeh, K. Atashkari, A. Jamali, A. Pilechi, and X. Yao, "Inverse modelling of multiobjective thermodynamically optimized turbojet engines using GMDH-type neural networks and evolutionary algorithms," Engineering Optimization, vol. 37, pp. 437-462, 2005. [41] A. Ghaffarizadeh, K. Ahmadi, and N. S. Flann, "Sorting unsigned permutations by reversals using multi-objective evolutionary algorithms with variable size individuals," in Evolutionary Computation (CEC), 2011 IEEE Congress on, 2011, pp. 292-295. [42] B. Golkar, R. Ranna-Akhavan, M. Tanasan, and R. Haghighi-Khoshkho, "Technical and economic investigations of repowering of Montazer al-Qaem steam power plant," presented at the 10th International Energy Conference, Tehran, 2014.
20
Research Highlights:
Technical-economic analysis of conversion of steam power plant into CWP
Solving the coupled energy and mass balance equations
Studying the effect of thermodynamic condition and steam flow on the produced water
Performing an economic estimation on the selling water price
Performing the multi-objective optimization of CWP
21
S1359-4311(18)37183-7 https://doi.org/10.1016/j.applthermaleng.2019.02.005 ATE 13299
To appear in:
Applied Thermal Engineering
Received Date: Revised Date: Accepted Date:
23 November 2018 16 January 2019 2 February 2019
Please cite this article as: M. Amiralipour, R. Kouhikamali, Potential Analysis and Technical-Economic Optimization of Conversion of Steam Power Plant into Combined Water and Power, Applied Thermal Engineering (2019), doi: https://doi.org/10.1016/j.applthermaleng.2019.02.005
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Potential Analysis and Technical-Economic Optimization of Conversion of Steam Power Plant into Combined Water and Power M. Amiralipoura, R. Kouhikamalib,* a
Department of Mechanical Engineering, University of Guilan, Campus 2 , Rasht, Iran b
Department of Mechanical Engineering, University of Guilan, Rasht, Iran
Abstract The current study deals with a technical-economic analysis of conversion of a steam power plant into a combined water and power (CWP) system. To this end, a steam power plant with nominal capacity of 166 MW is considered and a multi-effect desalination unit is employed for water production. Turbine steam extraction lines are used as motive steam in thermal water desalination process. To thermodynamically analyze the considered system and its components, a mathematical model is presented by describing the equilibrium equations of energy and mass associated with various elements. Then, by considering the total water flow rate and thermodynamic conditions of various points, the steam flow rate of each extraction turbine lines are computed in the design point. After that, the calculated steam flow rates as the input data are utilized to examine the power plant for different conditions of converting to CWP units. A parametric study is performed to analyze the effect of the steam extracted from each turbine extraction on the operation of the power plant and amount of water production. The results show that the high and medium pressure lines corresponding to the production of 8400 and 2000 cubic meters of fresh water per day have the highest and lowest water production capacity, respectively. Moreover, these lines result in losing up 11 and 5.5 MW in net power plants, respectively. Furthermore, an economic analysis is carried out to estimate the cost of water under different production conditions. Finally, by considering the net power and water selling prices as the objective functions, a multi objective optimization is performed to obtain the optimal conditions for each turbine line in the simultaneous production of water and power. Keywords: Steam power plant; Combined water and power; Technical-economic optimization; Potential analysis; Economic Investigation.
1. Introduction With the onset of the energy crisis in the 1970s, developed countries began to investigate new energy systems in order to control the crisis. On the basis of the renewable energy resources, some researchers developed new systems to improve the traditional ones and then studied their efficiency. In developing countries, some factors such as climate change, hot and dry summers and high population growth have led to a rapid increase in electric power consumption and freshwater in recent years. The influences of above*
Corresponding author. [email protected] (R. Kouhikamali). 1
mentioned factors on the performance of power plants have attracted a lot of interests of researchers and governments in Iran to increase their efficiency by developing the co-generation units. Three types of power plants including the gas, steam and combined power plants are responsible for supplying most of the Iran’s electricity. Therefore, converting the gas power plants into water and power co-generation systems has received a lot of attention. By considering long life of the steam power plants and this point that this plants provide about 30% of requiring electricity of Iran [1], a variety of studies was performed on repowering of the old units to increase their efficiency and decrease the thermal wastes. But, studies on converting this type of power plant into co-generation units in Iran are limited. The researches performed on the water desalination market in 2010 were showed an 11% increase in water demand [2]. Water desalination system is an indispensable option to overcome the scarcity of freshwater. Multistage flashing (MSF), multi effect desalination (MED) and reverse osmosis (RO) are considered as well-known processes in this regard. The performance of water desalination units and combined water and power systems corresponding to different conditions and parameters has been extensively investigated in literature [3-9]. For instance, Darvish and Amer [10] used a gas/steam combined cycle to perform a cost analysis on the cogeneration power–desalination plant in Kuwait. A mathematical model for a multi-effect thermal vapor compression desalination system was developed by Amer [11] to examine the performance of considered system and access to its optimized design and working conditions. A hybrid desalination technique was employed by Shahzad et al.[12] to hybridize a MED system. Aberuee et al.[13] investigated the influences of various vital parameters such as the working temperature and solar irradiation on the operational factors and performance of main elements of a multi-generation solar system. Moreover, the optimal working conditions of considered system were determined by employing the Genetic algorithm. On the basis of an experimental study, the performance of a small reverse osmosis unit was examined by Elsayed et al. [14]. In order to analyze the MED, KouhiKamali et al. [15, 16] provided a parametric analysis and optimization by taking the major design parameters into account. They contributed to the field by introducing a new model to predict variables such as heat transfer coefficient, temperature, required surface area, system process design and performance. To study a solar desalination system, Mahian and Kainifar [17] provided the mathematical modeling and experimental investigation. It was illustrated that one can enhance the evaporation rate and consequently freshwater production by employing the low-cost fan with negligible power. Khademi et al. [18] presented the simulation and optimization of a six-effect evaporator utilized in a desalination unit for the steady-state conditions. Ameri et al. [19] investigated the influences of number of effects, vapor pressure, temperature of effects and feed water temperature on performance of a portable thermal system. It was illustrated that the optimum efficiency is a function of the water salt, temperature difference of each effect and feed water temperature. Moreover, it was concluded that increasing the inlet vapor 2
pressure may results in increasing the efficiency. Mathematical modeling and simulation of a multipleeffect evaporators used in the brackish water desalination were provided by Sagharichiha et al.[20]. It was illustrated that for the considered desalination unit, one can improve the gained output ratio value from 3.8 to 7.5 by increasing the effects from 3 to 8. An experimental analysis was performed by Han et al.[21] to examine the effect of preheating and superheating entrained steam on the performance of a thermal vapor compressor entrainment ratio. Shakouri et al. [22] investigated the feasibility of using the thermal desalination unit coupled with a gas turbine for the oil refinery of Lavan Island in Persian Gulf. In this regard, by defining the operation conditions, the minimization of cost of desalination unit was performed through an economic analysis. Maghsoudi et al.[23] contributed to the field by providing thermoeconomic analysis of coupling MED-TVC with a combined cycle power plant. Hosseini et al. [24, 25] carried out economic and optimization analyses on the combined power and water generation units. The desalination unit and its power unit were considered to be MSF and gas turbine, respectively. They used an economic exergy analysis to determine the system’s efficiency. Hanafizadeh et al.[26]employed a multi effect desalination unit to perform a thermo-economic analysis on the combined power and water production in Iran. Ortega-Delgado et al. [27] analyzed a CWP plant composed of a MED and a Rankin cycle. They investigated the effects of thermo-compressor inlet steam pressure and water heat transfer levels of water desalination on system performance. The optimal conditions for the location of the thermo-compressor were determined. Recently, Moghimi et al.[28] proposed an integrated cooling, heating and power and a multi effect desalination for simultaneous producing the fresh water and electricity and refrigeration. They employed a dual-pressure heat recovery steam generator unit to link the Brayton cycle to the water desalination and ejector refrigeration units. Also, He et al.[29] proposed a power-water cogeneration system with single-extracted ORC to have an energy analysis and consequently analyze the effect of extraction parameters on the power generation and water production. Furthermore, some studies on the combined membrane and thermal systems in combination with the power plants are available in the open literature [30-33]. For example, the modified genetic algorithm was used by Wu et al.[34] to provide the optimal configuration and working conditions of power plant and desalination cogeneration units. Also, by proposing a mathematical model for MED-TVC/RO system and employing the genetic algorithm-based multi-objective optimization, Sadri et al.[35] obtained the optimal conditions of considered unit. In order to desalinate the brackish water in Persian Gulf, Mokhtari et al.[36] developed a mathematical modeling for a combined MED-RO system and then provided the thermo-economic and exergy examinations. It was concluded that by employing the gas turbine+MED+RO hybrid units, in addition to supplying the electricity, one can produce enough fresh water for the considered region. Based on exergy accounting approach, Osman A. Hamed [37] provided a thermo-economic analysis to examine the performance of a combined power plant integrated with a hybrid MSF/ RO desalination units. 3
To the authors’ best knowledge, the potential analysis and optimization on the conversion of steam power plant into a CWP system are still unexplored. Therefore, the present study aims to examine the performance of a steam power plant in combination with a thermal desalination unit in Iran from a technical and economic perspective. To select the proper combined structure of the MED and steam power plant in accordance with demand for water and power, a detailed study is performed on the steam of various turbine extraction lines with different conditions for thermal desalination process. In addition, using an economic analysis, the water selling price is estimated. Finally, considering the operating conditions of the system, the co-generation system is optimized through definition of objective functions (water selling price and net power of the steam power plant).Furthermore, in points of view of the steam conditions, the optimal combination of steam power plant and MED unit is presented.
2. System Modeling 2.1. Descriptive Model The considered system consists of a steam power plant and a multi-effect desalination unit. The schematic of the co-generation system is shown in Fig.1. The steam power plant includes boiler, steam turbine at three low, medium and high pressure levels, condenser, five closed heaters (one HP, two MP and two LP), one deaerator and pressure pumps. Six steam lines are extracted from different stages of the turbine to heat the feed water and subsequently increase the power plant efficiency. As illustrated in Fig. 1, the steam of turbine’s extraction lines are divided into two parts. One part of steam enters the heaters and the other parts enter the desalination unit. The steam entered in desalination unit can be varied up to 100% of the capacity of each extraction line, which is finally condensed by losing its heat in the first effect of the desalination unit and then returns from the condenser pump outlet. It should be remarked that since the steam extracted from each extraction line is constant at design points, no change occurs in flow through the steam turbines. In fact, due to a mass balance in the heaters, the temperature of main line of power plant only changes which results in varying the net power of plant. The desalination unit at the present study is assumed a multi effect desalination with five effects condenser and thermo-compressor. The considered desalination unit is a well-known utilizing thermal system in south of Iran.
4
Fig. 1. Schematic of co-generation of power and water
2.2. Mathematical Model A mathematical model is presented to analyze the system and its components thermodynamically. The fully parametric modeling is performed by employing EES Software. In order to model the equilibrium equations of energy and mass, each component of the elements is scripted based on their volume of control on a steady state. In modeling the power plant, the designed parameters are in accordance with Montazer al-Qaem Steam Plant with nominal capacity of 166 MW in Iran. It should be remarked that due to availability of the needed data, this power plant is selected for modeling. On the other hand, since this power plant is similar to the other ones employed in Iran (for instance, Bandarabbas steam power plant), all of the utilized values can be changed to simulate the similar power plants near the salty water resources by employing the methodology presented herein. For steam power plant, by considering the total water flow rate as well as the thermodynamic conditions of various points, the steam flow rate of each extraction turbine lines will be calculated in the design point. Then, the calculated steam flow rates as the input data will be used to analyze the power plant for different conditions of converting to CWP units.
5
2.2.1. Boiler Considering the heat transfer schematically presented in Fig.1, the heat transferred to the boiler is calculated based on the following: (1) The fuel required in the power plant boiler is expressed as below: (2) in which the subscript
denotes the boiler.
2.2.2. Feed Water Heater, Condenser and Pump in Power Plant The presence of heaters and their proper functions have a significant effect on increasing the temperature of water entered to boiler and reducing the amount of consumed fuel. The heater situation and steam of extraction lines corresponding to different stages of turbine depend on the design conditions and power plant outlet. In feed water heaters, three parameters including terminal temperature difference (TTD), drain cooling approach (DCA) and temperature rise (TR) are the functional indicators. It should be noticed that amounts of TTD and DCA depend on the design conditions of heaters under different loads in power plant but, no changes occur in TTD and DCA by varying the temperature. However, for different conditions underlying power plant, TR as indicative of inlet water temperature difference is varied. Considering Fig. 1 and graphical representation of closed and open heaters illustrated in Fig. 2, the coupled energy and mass equilibrium equations of five closed heaters and deaerator associated with the modeled power plant is shown in Table 1(Eqs. (3-8)). Furthermore, equations corresponding to the heat transfer in the power plant condenser and energy equilibrium of pumps can be expressed by Eqs. (9)-(12). Table 1.Energy equilibrium equations in heaters, condenser and pump Equations
Descriptions FWH 1 FWH 2 FWH 3 FWH 4 FWH 5 De-Aerator
(3) (4) (5) (6) (7) (8) (9)
Condenser (10) (11)
6
Pump
Extraction Turbine line
(12)
Extraction line
Steam from cloased heater
Water Deaerator
Water Steam
Water
Water
Fig. 2. Graphical representation of closed and open heaters
2.2.3. Turbine The steam turbine in the power plant studied is a tri-stage turbine (low, medium and high pressure). The mass and energy equations are presented as below: (13) (14) (15) Total outlet power relevant to the plant is written in the following form; (16) The steam flow rate from the turbine extraction lines for the desalination system can be described as (Eqs.(15) and (16)): (17) (18) in which the subscripts “ex”, “he” and “MED” stand for the extraction, heater and multi-effect desalination, respectively. The net power plant
and efficiency of power plant
are obtained as follows (19) (20)
2.2.4. MED Unit Considering the steam extent and condition in water desalination system, MED can be generally divided into three categories. Under the first condition, i.e. MED as low-enthalpy energy source, low pressure and temperature are used as the source of heat. Under the second condition, i.e. MED-MVC, the steam is 7
compressed by a compressor and this state is used when there is no steam in the system. Under the third condition, i.e. MED-TVC, steam derived from middle pressure operates as driving steam in thermocompressor and the thermo-compressor sucks the steam from last effect and mixes it with the motive steam and then transfers the output to the first effect. MED-TVC is commonly used in large scale hybrid systems. In the present research, in order to convert the power plant into power and water cogeneration system, the MED-TVC is employed for the high and medium pressure lines whereas MED process is used for the lowest pressure line. In the process of designing the desalination systems, to express the mass and energy equations, three sub-models including effects, condenser and thermo-compressor must be considered simultaneously. Table 2shows the variables and unknown values of MED. The summation of the variables is equal to 10n+8, which the same number of equations is required to design the relevant system. Table 3 shows the mass and energy equations governing the desalination system. Further explanations on the performance and modelling MED-TVC are presented in[16, 38]. Table 2. MED variables Descriptions Symbol Temperature Total feed water and effect temperatures Temperatures of the steam from each effect Condenser product Total feed water and effect flow rate Inlet steam flow rate Water flow rate, cooling water, motive steam Thermo-compressor suction rate Wastewater flow rate Condenser surface Wastewater concentration Table3. Mass and energy equations in MED Description Mass equilibrium at each stage Salt mass equilibrium at each stage
Equation (21) (22)
Energy equilibrium at each stage
(23)
Total heat transfer rate at each stage
(24)
Total heat transfer coefficient at each stage
(25)
Condenser mass equilibrium
(26)
Condenser energy equilibrium
(27)
Overall condenser heat transfer rate
(28) 8
Total condenser heat transfer coefficient
(29)
Increased boiling temperature difference
(30)
Temperature difference between each step
(31)
Condenser logarithmic temperature difference
(32)
Feed water/condenser temperature difference
(33)
Water flow rate equality at each stage
(34)
Water supply temperature equality with total feed water at each stage
(35)
Overall product equality with total effect product
(36)
Feed water/product flow rate
(37)
Thermo-compressor mass equilibrium
(38)
Gain output ratio (GOR)
(39)
3. Economical Investigation In order to provide an economic model for the considered system, in addition to taking the purchase and maintenance costs into account, the interest rate corresponding to localized conditions should be considered to estimate the water selling price. In addition, the benefits of converting the power plant into water and power co-generation should be estimated economically and technically. It is remarked that although the initial investment as the most significant economic dimension of a co-generation system cannot determine the profitability or risk of funding, but this price plays an important role in decision making. Since the present study considers the operating conditions of the steam power plant, the equipment cost is not considered. The purchase cost of MED with five effects in accordance with the offer proposed by one of the biggest MED-TVC manufacture in Iran can be expressed approximately by the following equation [39] (40) To estimate water selling price in the co-generation system, both initial investment cost and the loss of net power should be considered. In this study, and equal to 0.05
is regarded as the desalination investment cost (Eq.(40)),
as the cost of electricity based on released data by Iran ministry of energy is assumed to be [1].
9
As a result, the water selling price can be calculated using the following equation which includes the variations corresponding to local conditions and Iran interest rate (41) where
signifies the considered maintenance factor and CRF is capital recovery factor which considers
the two variables interest rate (i) and operation years (n). CRF can be expressed as below: (42) It should be remarked that in the steam power plants, the pressure of extraction lines (heaters’ pressure) is usually constant and the extraction steam flow rates are varied. Moreover, the capacity of desalination plant is related to amount of motive steam and its pressure. As discussed before, in the present study, the steam of extraction lines are used as motive steams in the desalination unit. Depending on these steams and the number of effects of MED, the capacity of desalination unit is determined. At a given pressure, increasing and decreasing the number of effects result in increasing and decreasing this capacity, respectively. But, increasing the number of effects leads to increasing the cost. On the other hand, the GOR parameter as the ratio of desalted water-to-motive steam defined in Eq. (39) is increased by increasing the number of effects. However, according to the previously-published work by the same author(s) [38], although more increasing the number of effects leads to increasing the GOR parameter, but no considerable increase is happened in the produced water. Thus, the desalination unit with five effects as an optimal condition is considered in the present study. 4. Optimization Although increasing the steam extracted from any turbine line maybe results in increasing the water production capacity, but it leads to losing the power plant performance. On the other hand, an increase in the production capacity leads to a reduction in the water selling price. Therefore, it is required to perform a multi-objective optimization. In the present study, by selecting the net power of the steam plant and water selling price as two objective functions, first, the required outputs are obtained from EES software in the form of multi-functions, and then the resulting objective functions are optimized using the evolutionary algorithm and an extended code in MATLAB. Obviously, in the present optimization, maximizing the power is consistent with minimizing the water selling price in the co-generation system. Generally, the vector
can be optimized throughout the optimization process: (43)
where
is decision variables vector and
is the objective function vector which should be
minimized or maximized. In the current method, to find the optimal solutions, genetic algorithm is used.
10
4.1. Evolutionary algorithm: Genetic algorithm Genetic algorithms as an iterative and stochastic search strategy are employed to find an optimal solution and imitate in a simplified manner principles of biological evolution. A characteristic of an evolutionary algorithm is a population of individuals, where an individual consists of the values of the decision variables (structural and process variables here) and is a potential solution to the optimization problem. More details about genetic algorithm and its procedure can be found in [40, 41]. The input thermodynamic parameters in modeling of CWP system and the required parameters in computing the purchase equipment cost and economic factors are presented in Tables 4 and 5, respectively. Also, the thermodynamic conditions including the temperature, pressure and steam flow rate of each extraction line corresponding to Montazer-Qaem power plant are presented in Table 6.
Table 4. Input variables in cogeneration system modeling Variable
Value
Unit
Fuel consumption
12
kg/s
Combustion efficiency
87
%
Fuel Thermal Value (LHV)
37000
kj/kg
Pump isentropic efficiency
80
%
Turbine isentropic efficiency
80
%
35000
mg/lit
Product water concentration
0
mg/lit
Feed water temperature
25
c
Desalinations’ recovery coefficient
35
%
Number of MED effect
5
-
Feed inlet water concentration
Table 5.Economic Factors Economic parameters
Value
Interest rate (%)
12
Function year (Year)
20
Operation and maintenance coefficient
1.06
Hours of the system function annually (Hour)
4300
Selling price of electricity
0.05
11
Table 6. Input thermodynamic conditions in power plant modeling Line
Temperature (c)
Pressure (kPa)
Stream flow rate (kg/s)
15
354.6
3308
11.33
16
449
1644
5.25
17
361.1
884
3.87
18
288.4
503
4.36
19
226
280
7.30
20
118.3
85.4
8.16
5
43.59
8.9
97.75
5. Results and Discussion 5.1. Basic Model The results obtained from modeling the power plant in peak capacity are given in Table 7. Moreover, the temperature difference of both sides of the heaters, the power consumption of pumps and net power of the power plant under condition of 100% steam corresponding to five different turbine extraction lines (line15 (HP extractions), lines 16 &18 (MP extractions), lines 19&20 (LP extractions)) for water production are provided in this table.
Table 7. Result of CWP unit Description
Efficiency
Symbol
Unit
Plant Performance
HP heater
IP heaters
line 15
line 16 38.52
LP heaters line 18
line 19
line 20
39.89
37.20
38.62
37.86
37.78
MW
154.09
143.68
148.77
149.18
146.24
145.93
Boiler outlet temperature
C
540.4
489.7
514.5
516.2
501.7
500.2
Total pumps’ net power
MW
2.24
2.44
2.45
2.39
2.36
2.35
C
37.7
0
38.9
38.8
39.3
39.4
C
24.8
21.8
3.2
25.2
25.5
25.5
C
20.7
19
19.9
0
21.06
21.07
C
35.51
32.45
34.01
34.77
0.79
35.91
C
50.49
45. 29
47.95
46.81
44.49
4.01
Power plant net power
FWH1 Temperature Difference FWH 2 Temperature Difference FWH 3 Temperature Difference FWH 4 Temperature Difference FWH 5 Temperature Difference
(%)
12
5.2. Validation Thermodynamic modeling of steam power plant is the most important part of the modeling of the CWP system. To validate the developed model, in the nominal capacity considered for the system and on the basis of the thermodynamics of extraction lines and steam flow rate, the temperature of different lines of power plant are obtained and compared with those of Montazer al-Qaem Power Plant in Iran with same nominal capacity, as given in Table 8. The needed data can be found in [42]. A reasonable agreement can be seen.
Table 8. Comparison between temperatures of different lines of power plant resulted from model and actual data in nominal capacity Line
Model[T(C)]
Montazer al-Qaem[ T(C)] [42]
Error (%)
2
46.23
46.33
0.1
3
96.72
89.33
7.4
4
96.49
90.1
6.4
5
133
126.4
6.6
6
152.7
148.6
4.1
7
177
175.5
1.5
8
201.8
199.6
2.2
9
239.5
235.4
4.1
10
540.4
540.7
0.3
12
540.4
534.6
5.8
5.3. Parametric Analysis Parametric study is performed to analyze the system performance under combined water and power generation. Figs. 3 and 4 illustrate the variation of net power of power plant and fresh water production capacity versus the steam outlet percentage corresponding to various turbine extraction lines, respectively. In accordance with these figures, one can select the proper hybrid structure corresponding to the water and power demands. Also, these figures illustrate the steam extraction modes up to 100% of the capacity of each line. Furthermore, it can be seen that the maximum and minimum water productions belong to HP and one of the MP extraction lines, respectively, so that using the steam from the line15 can lead to generating about 8400-m3 and using the line18 produces about 2000-m3 daily desalinated water. On the other hand, using these lines can lead losing up to 11 MW and 5.5 MW in the net power plant, 13
respectively. Moreover, the importance of positions of heaters as well as the steam flow rate of each line on the amount of water production and loss power are demonstrated in these figures. 154 152
wnet(Mw)
150 148 146
p=33 bar p=16.4 bar p=5.3 bar p=2.8 bar p=0.85 bar
144 142 0
0.2
0.4
0.6
0.8
1
steam outlet percentage(*100%) Fig. 3. The net power of power plant versus the steam outlet percentage corresponding to different extraction lines
water production(m3/day)
10000
8000
p=33 bar p=16.44 bar p=5.03 bar p=2.8 bar
6000
p=0.854 bar
4000
2000
0 0
0.2
0.4
0.6
0.8
1
steam outlet percentage(*100%) Fig. 4. The water production versus the steam outlet percentage corresponding to different extraction lines
14
The temperature rises in the heaters corresponding to various extraction lines versus the steam outlet percentage are illustrated in Fig. 5. It is observed that increasing the steam outlet percentage decreases the temperature difference at the two sides of the heaters, so that at higher steam outlet percentages, it is diminished. 50 p=33 bar p=16.44 bar
40
p=5.03 bar p=2.8 bar
TR(C)
30
p=0.85 bar
20
10
0 0
0.2
0.4
0.6
0.8
1
steam outlet perentage(*100%) Fig. 5. Temperature rise in the heaters versus the steam outlet percentage associated with various extraction lines
In addition to the technical conditions, the proper conditions for converting the power plant into cogeneration system should be determined throughout an economic analysis. Depicted in Fig. 6 is the influence of steam outlet percentage on the water selling price for various turbine extraction lines. By considering this point that the water generation capacity at each line is different and the water selling price is a function of daily water generation, an increase in capacity results in declining trend of selling price. As indicated, the high pressure lines have greater water generation capacity and this can lead to a reduction in water price. It is noted that to determine the water price, the cost of water desalination unit and the loss of power are taken into account. With increasing the amount of steam extracted from each line, more power loss happens. It shows the disadvantage of the electricity sales of the power plant. However, it is observed that the price of water has dropped by reducing the initial purchase price of water desalination unit. It illustrates the importance of this cost on the economic analysis of the simultaneous production systems during the operation.
15
3.4
water selling price($/m3)
3.2 p=33 bar p=16.44 bar p=5.03 bar p=2.8 bar p=0.85 bar
3 2.8 2.6 2.4 2.2 2 1.8 0
0.2
0.4
0.6
0.8
1
steam outlet percentage(*100%) Fig. 6. Water selling price versus the steam outlet percentage associated with different turbine extraction lines 6. Optimization Results In optimization process, the power of steam plant and the water selling price are considered as two main objective functions. The selected variable is the steam capacity of each turbine extraction line which varies from 10% to 100%. Considering the technical and economic considerations, each turbine line can act as the basis for the design of the power plant to become a system for co-generation of water and power. Therefore, the optimum conditions for the use of each lines should be considered. The results obtained from the optimal conditions for using different lines in the water and power cogeneration system are shown in Pareto Diagram (Fig. 7). In this diagram, the initial and the end points indicate the maximum power and the lowest water price. As can be seen, the price increases with increasing power, which indicates a decrease in water production. The specified points are A, B, C, D and M, whose values are shown in Table 9 Given the condition of the diagrams, it can be considered as a compromise point between the objective functions.
Table 9. Optimal values of objective functions at points A, B, C, D and M Point
A
B
C
D
M
Power
148.62
150.7
150.56
149.7
149.5
Cost
1.88
2.09
2.59
3.21
3.23
16
Pareto Front
3.6
Water selling price($/m3)
3.4
M
3.2 D
3 2.8 2.6 2.4
p=33 bar p=16.44 bar p=5.03 bar p=2.8 bar p=0.85 bar
C
B
2.2 2 1.8
A 1.6 142 143 144 145 146 147 148 149 150 151 152 153 154
Power(MW)
Fig. 7. Pareto optimal solutions for water selling price versus net power
7. Conclusion Considering the need of different communities to electric power and freshwater, it is important to analyze and optimize the conditions for the conversion of power plants into CWP systems. The current study was analyzed the technical and economic conditions of the conversion of a steam power plant and the potential of using each turbine extraction line in CWP system. Then, water selling price was estimated and the optimal conditions of each extraction line was specified by defining objective functions of the net power of steam plant and water selling price in the form of Pareto chart. The most important results are as follows:
It was observed that the thermodynamic conditions of the extraction lines and heaters are important in choosing each line in the co-generation system, so that at the studied power plant, the high-pressure line produces about 8,400 cubic meters per day and medium pressure lines produces about 3800and 2000cubic meters of water per day. Also, the low pressure lines produce about 3000 and 2500 cubic meters of fresh water per day.
The role of each heater in the power plant is important. The steam extracted from each turbine line reduces the performance of heaters and consequently results in decreasing the water temperature of the power plant and net power. In investigated power plant, the high pressure line which produces the largest amount of water in the plant, causes a drop of 7.4% and one of the medium pressure line which has the lowest water capacity resulted in a 3.57% power loss in the net power.
17
Economic analysis is necessary to estimate the price of water in the system. Two main parameters "the purchase cost of desalination unit" and "losses from electricity sales of power plants" were considered in determining the price of water. It was observed that, selling prices were lower in higher pressure lines that have the potential to produce more water in comparison with low pressure lines.
The optimum conditions for the use of each turbine extraction line were observed in the simultaneous water and power generation system. Points A, B, C, D, and M with values 1.88,2.09,2.59,3.21and3.23 cubic meters per dollar and 148.62,150.7,150.76,149.7 and 149.5 MW are selected as the compromise points of objective functions in each line.
Compliance with Ethical Standards: The authors declare that they have no conflict of interest.
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Research Highlights:
Technical-economic analysis of conversion of steam power plant into CWP
Solving the coupled energy and mass balance equations
Studying the effect of thermodynamic condition and steam flow on the produced water
Performing an economic estimation on the selling water price
Performing the multi-objective optimization of CWP
21