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Smart thermoelectric waste heat generator: Design, simulation and cost analysis
Sustainable Energy Technologies and Assessments 37 (2020) 100623
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Smart thermoelectric waste heat generator: Design, simulation and cost analysis
T
⁎
Gunay Omera, Abdullah Hakan Yavuzb, , Rasit Ahiskac, Kagan Ekrem Calisald a
Program of Radiotherapy, Vocational School of Health Services, Ankara Medipol University, Ankara, Turkey Faculty of Engineering and Natural Sciences, Gaziosmanpasa University, Tokat, Turkey c Department of Physics, Faculty of Science, Gazi University, Ankara, Turkey d Petkim Petrochemical Holding, Izmir, Turkey b
A R T I C LE I N FO
A B S T R A C T
Keywords: Thermoelectric Waste heat recovery Thermoelectric generators Matlab simulation Payback coefficient
Globally one third of energy consumption is attributable to the industrial sector, with up to fifty percent ultimately wasted as heat. Waste heat is difficult to identify and evaluate both in terms of quantity and quality. Therefore, waste heat recovery is very important in terms of reducing energy costs and environmental impacts. The method used for waste heat recovery must be feasible. In this study, we produced an environmentally friendly and electric- and water-saving smart thermoelectric waste heat generator (STWHG), performed laboratory and fields tests for the generator, and examined power and cost parameters of a STWHG power plant with a capacity of 150 W at ΔT = 100 °C installed in an industrial establishment. We performed MATLAB simulations for real working conditions of TEG modules used in the production of STWHG as well as the entire power plant, and compared the results with directly measured parameters. The payback coefficient of power plant was K = G/M > 1. When ΔT = 100 °C, the power plant begins to profit after 6 years. The results show that the thermoelectric waste heat power plants was very profitable and feasible.
Introduction The optimal and smart usage of source of energy is important due to increasing energy demands. Existing energy resources are limited. Most studies show that fossil fuels will be depleted in the near future, and harmful effects such as greenhouse gases that are generated by the use of these fuels cause global warming. Therefore, the use of renewable energy sources is increasing to reduce greenhouse gas emissions and protect fossil fuel reserves. Efficient use of energy in terms of sustainability is also important [1,2]. One third of energy consumption is used to industrial sector. However, about 50% of the energy used is released as waste heat. Due to increasing energy demand and limited fossil fuels, it is likely that the future will bring increased energy prices. Therefore, the recovery of waste heat is important in terms of energy efficiency [3]. The foundation of the thermoelectric (TE) industry was laid with the discovery of the Seebeck and Peltier effect in early 19th century. However, thermoelectric modules (TEM) did not become wide-spread due to their low efficiency when used as a generator (TEG). In parallel with developments in the semi-conductor technology in mid-20th century, TEGs began to be used in practice. While the industrialization
⁎
around the world within this period is causing pollution, it is also constantly increasing the demand for electrical energy as well. The most important consequence of industrialization that causes environmental pollution is waste heat. As thermoelectric technology converts heat energy directly electrical energy, it is one of important alternatives for the recovery of waste heat. In recent years, there have been more and more studies on the utilization of waste heat using TEGs. Significant improvements have been achieved in TEG efficiency thanks to the developments in TE materials and technology. Comprehensive experimental studies have been conducted on thermoelectric waste heat recovery systems with metal foam placed inside heat flow paths in order to increase heat flow intensity. In one study, using metal foam in the system resulted in an increase of 29.75% in efficiency depending on foam density [4]. Waste heat recovery test data is quite expensive to collect. Therefore, simulation studies are important for TEGs to be designed at high temperatures and under real working conditions. In one experimental and simulative study on TEGs, simulation results were shown to overlap with experimental results with an accuracy of ± 12% [5]. In one study on 5 important parameters of the module that affect the TEG performance (height, length, area, gap, and heat transfer material), height was
Corresponding author. E-mail address: [email protected] (A.H. Yavuz).
https://doi.org/10.1016/j.seta.2019.100623 Received 19 October 2019; Received in revised form 19 December 2019; Accepted 28 December 2019 2213-1388/ © 2019 Published by Elsevier Ltd.
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QC=2N [αITC + 0.5I 2R + K ΔT
shown to have the most effect on the module performance. TEG application tests conducted on internal combustion engines showed that height affected the output power by 30.25–69.6% [6]. While generating energy, TEGs eliminate the hazardous heat dissipated to the environment. The temperature difference between the surfaces needs to be increased in order to improve TEG performance. A water circulation system was used as the hot surface heat transfer system in one study performed using heat pipe in a solar system. In this study, heat pipe was used to transfer heat from hot surface. The system developed also allowed for successfully producing hot water by transferring the discharged heat to water [7]. Many practical cases with waste heat recovery potential such as exhaust gases of reciprocating engines, cement kilns or heat-treating furnaces, are nowadays often integrated with organic Rankine cycle (ORC) to convert waste heat to the mechanical power. However, when dealing with high-temperature waste heat, organic Rankine cycle faces efficiency limit due to the physical properties of the working and thermal fluids. Increased installation costs and practical difficulties at high temperature applications reveal the disadvantages of ORC methods [8]. A power production of 600 W was achieved with TEMs placed on inner walls of internal combustion engines. An efficiency increase of 2.75% was also achieved at 4000 RPM [9]. Thermoelectric generators are used in hybrid systems with other systems to increase efficiency. By using solar concentration systems, heat density is increased and efficiency is increased [10]. Studies on thermoelectric materials have shown that module efficiency can be increased 34 times by using carbon particles [11]. These developments in thermoelectric technology lead researchers to TEG applications. TE technology is used in various fields in waste heat recovery systems. A study has been done on waste heat recovery of white high power leds. With the proposed waste heat recovery system, high heat fluxes have been shown to convert about 1% into electrical energy. Even at this rate, it is possible to achieve significant energy savings on a global scale [12]. In this study, MATLAB simulation is used to simulate the thermoelectric waste heat generator (STWHG) under different temperature, load and series condition. STWHG was designed and tested under different operating conditions in the laboratory. The simulated parameters are then compared with experimental test results. STWHG was installed in industrial establishment. The physical parameters under real working conditions were measured and compared with the simulation results. Using the data obtained, the payback coefficient was calculated and the payback coefficient of the power plant was found K = G/ M > 1. Using the simulation, the break-event points were calculated for different ΔTs.
QH = 2N [αITH −
0.5I 2R
(1) (2)
+ K ΔT ]
Here, QC (W ) is the thermal power absorbed from the cold surface, QH (W ) is the thermal power ejected from the hot surface, R = ρL/ A (Ω) is the total resistance of the module, α (V/K) is the Seebeck coefficient, I (A) is the current drawn from the module, TC (K ) is the temperature of the cold surface, TH (K ) is the temperature of the hot surface, ΔT (K) is the temperature difference between the surfaces (TH − TC ), and K (W/ K) is the thermal heat transfer coefficient of the module. ρ (Ωcm) is the resistivity of the semi-conductors used in the module, k (W / K ) is the thermal conductivity of the semi-conductors, A (cm2) is the footprint area of the semi-conductors, L (cm) is the height of the semi-conductors, and N is the number of thermoelements used in the module. Since the output power of the thermoelectric generator is W = QH − QC , W is obtained as in equation (3) using equations (1) and (2).
W = 2N [α ΔT − I 2R]
(3)
Since the output power changes depending on the load resistance, if the equation is arranged using W = 2NI 2RL = IV , the voltage (V) at the thermoelectric generator output is obtained as in equation (4).
V = 2N [α (TH − TC ) − RI ]
(4)
As shown in Fig. 1, when a load is connected to the ends of the module, a current passes through the load. The load current, voltage, and power generated are expressed as in equations 5–7.
I=
α (TH − TC ) RL + R
V=
2Nα (TH − TC ) RL RL + R
(5)
2Nα 2 (TH
(6)
)2
− TC RL (RL + R)2
W=
(7)
The thermal efficiency is expressed as η = obtained when it is expressed as m =
η=
(1 − ) m (1 + m) − 0.5 (1 − ) +
RL . R
W , QH
and equation (8) is
TC TH
TC TH
T (1 + m)2 C
TH
ZTC
(8)
α2 , ρk
which is the Figure of Merit (FOM). As is known, the Here, Z = condition of RL = R must be met in order to achieve maximum power transfer. In this case, the resistance ratio is m = 1. When RL = 0, then V = 0 and the current is at maximum (ISC). When RL = infinite, then I = 0 and the voltage is at maximum (VOC). VOC and ISC are expressed as in equations 9–10.
Material and methods Material
ISC =
The basic structure of TEGs is formed by p- and n-type semiconductor thermoelements (TEs). TEs are connected electrically in a serial manner to increase the output voltage of the TEG and connected thermally in parallel to decrease the thermal resistance of the TEG. The structure and the equivalent circuit of a TEG have been given, in Fig. 1 [13]. TEM devices can typically be classified into thermoelectric generators (TEGs) and thermoelectric coolers (TECs). TEGs convert thermal energy from a temperature gradient to electrical energy (Seebeck effect), whereas TECs convert electrical energy into a temperature gradient (Peltier effect) [14]. When a TEM is run as a generator, there must be a temperature difference between the surfaces. This allows for heat transfer from one surface to another. When a load is connected to the ends of the TEM, a current passes through the load and generates power. Equations 1–5 show the thermal equations for a TEM used in the generator mode.
α ΔT R
(9) (10)
VOC = 2Nα ΔT
To find the maximum power value, if the numerator and the deR nominator in equation (7) are divided by R, m = RL = 1 is placed in the equation, the derivative is calculated according to m and equalized to 0, then the maximum power Wmax and the maximum efficiency ηmax are expressed as in equations 11–12.
Wmax =
2Nα 2 (TH − TC )2 4R
(1 + ZTave − 1 T ηmax = ⎛1 − C ⎞ T T (1 + Z Tave − TC H⎠ ⎝ H ⎜
(11)
⎟
(12)
Here, Tave = (TH + TC )/2 . The load maximum voltage value Vmax, the load maximum current value Imax, and the load maximum thermal 2
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Fig. 1. A TEM in the generator mode and the equivalent circuit of the TEM.
Method
efficiency value ηmaxp are expressed as in equations (13) and (14).
Imax =
α (TH − TC ) 2R
(13)
Vmax =
2Nα (TH − TC ) 2
(14)
ηmaxp =
(1 − ) (2) − 0.5 (1 − ) +
TEG MATLAB simulation In TEG systems, the goal is to achieve maximum output performance. As indicated by the TEG thermal and electrical equations given in the previous section, the output performance changes depending on the geometric properties, semi-conductor’s properties, and temperature. In this study, a model was created in order to design the most appropriate system according to effective parameters for TEG modules. Designing a system which can produce system performance curves using input parameters (ρ, α, k, A, h) of a single TE and depending on the number of thermoelements and the estimated application temperature values provides great convenience in terms of application. The interface of the model developed. The simulation study can also calculate the effective material properties according to the catalog data. The effective material properties are parameters that also include the dynamic working parameters of the module in question. Designing the system using these parameters is important for obtaining results that are closest to a real application [15]. Another concern in renewable energy studies is the cost and payback time. The model developed in this study allows for calculating and evaluating parameters related to the payback time as well. This model can be used both in TEM design stage and large-scale generator modeling designed using TEMs. HZ-2, a commercial module manufactured by Hi-Z, and TGM199-1.4-2.0, a commercial module manufactured by Kyrotherm, were used to test the reliability of the model. Table 1 shows the parameters belonging to these models. The parameters shown in Table 1 were entered into the simulation study, which produced the output parameters. Table 2 shows the results comparatively. A comparison between the results obtained from the simulation study and the catalog information showed that the parameters in question were very similar. The results indicate that the model is reliable. The simulation study allows for calculating effective semiconductor material parameters by entering the experimentally measured parameters of any module into the system. Performance curves and current-
TC TH
TC TH
T 4 C
TH
ZTC
(15)
TEG manufacturers provide the catalog data related to the parameters of ISC, VOC, Wmax, and η max depending on the values of TH and TC. Values obtained by using thermoelectric ideal equations are usually different from experimentally found data. This is because ideal equations do not include changes in semi-conductor materials depending on temperature, do not consider losses such as the Thomson effect, and ignore losses caused by thermal resistances. It is quite difficult to consider these losses. It is possible to find effective material parameters based on the experimental data given for TEG modules. The maximum module parameters and the effective parameters depending on geometric properties are expressed as in equation 16–19 [15]. A
ρe =
4( L ) Wmax 2NImax 2
(16)
αe =
4Wmax 2NImax (TH − TC )
Ze =
max C 1 ⎛ ⎛ 1 + ηC TH ⎜ η Tave ⎜ ⎜⎜ 1 − max ηC ⎝⎝
η
ke =
αe 2 Ze ρe
T
(17) 2
⎞ ⎞ ⎟⎟ − 1⎟ ⎟ ⎠ ⎠
(18)
(19)
Here, ηC = (1 − TC / TH ) is the Carnot efficiency. Effective material properties calculated in this way include contact resistances, Thomson heat losses, and heat losses caused by radiation and convection. Similar to the new method previously developed for TECs based on the equations given above, the foundation for a new method was laid for TEGs in this study. The formulas were used to find the basic parameters after recoding Imax, Wmax, TH, and TC, which were easily measured using this method developed for TEGs. Similar to TEPAS, a TEGPAS (Thermoelectric Generator Performance Analysis System) system was also created to examine TEG modules or TEG systems [13,16,17]. Additionally, MATLAB simulations were developed for the formulas above, which were used for theoretical examination of the TEG system.
Table 1 HZ-2 and TGM199-1.4-2.0 catalog data.
TC (°C) TH (°C) N A (mm2) h (mm) Sizes (mm) α (µV/K) ρ (Ωcm) k (W/K)
3
HZ-2
TGM199-1.4-2.0
30 230 97 2.1 2.87 30 × 30 × 4.5 167.526 1.532 × 10−3 0.016
30 200 199 1.96 2 40 × 40 × 4.4 162.856 1.024 × 10−3 0.015
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Table 2 Comparison between simulation and catalog data. HZ-2 Simulation Data
HZ-2 Catalog Data
TGM199-1.4-2.0 Simulation Data
TGM199-1.42.0 Catalog Data
R = 4.062 Ω ISC = 1.60 A VOC = 6.50 V Wmax = 2.60 V η max = 4.546%
R=4Ω ISC = 1.60 A VOC = 6.50 V Wmax = 2.60 V η max = 4.5%
R = 4.159 Ω ISC = 2.65 A VOC = 11.02 V Wmax = 7.3 V η max = 4.35%
R = 3.7 Ω ISC = 2.65 A VOC = 11 V Wmax = 7.3 V η max = 5.3%
dependent output parameters of the module under various temperature differences and at various load resistances can be determined using the model. Additionally, it is possible to obtain preliminary information about the total system performance by entering the number of series and parallel modules to be used in a generator to be designed using the tested module into the simulation study. Since the simulation results were quite similar to the catalog data, it is obvious that these can be used to design larger systems.
Fig. 3. STWHG application diagram.
The surface of the pipe used in the project varies between approximately 400 °C and 440 °C depending on the process (the output load of the gas turbine). This surface temperature is a high temperature value for the thermoelectric modules to be used in the project, which are produced in the laboratory of TES Thermoelectric Systems Ltd. in Ankara. The steady-state working temperature value of the modules to be used in the project varies from 150 °C to 200 °C at most. The aluminum surface smoother designed for the project formed a smooth surface for healthy contact of the modules to the hot surface and reduced the temperature picked up by the modules to an appropriate value. On the cold surface side, the same type of aluminum material was used to construct a water-cooled system. The process water of the company’s closed-loop cooling system, the temperature of which varies from 26 °C to 32 °C depending on the season, was circulated within this system. Fig. 3 shows the application diagram of the thermoelectric generator. The control circuit allows for measuring the temperature, current, and voltage on the system. The ATMEGA 328 microcontrollerbased control circuit is used for switching the TEGs, which were designed as two blocks, to series and to parallel. The input of the charge control circuit in the control circuit has the limit values of maximum 75 V and 20 A. In order to avoid exceeding these values, the control circuit switches the TEGs to parallel when the measured voltage value exceeds 60 V by controlling 2 relays. When the voltage value drops below 25 V, the circuit switches the TEGs to series. While the TEG outputs feed the charge regulator, it is possible to feed DC loads using the accumulator and to feed AC loads using the inverter. The control circuit also serves as a Data Logger. The control circuit has Wi-Fi connection capabilities; therefore, it is possible to collect data remotely if there is internet infrastructure. It is also possible to collect data directly on-site using a PC. The control circuit is equipped with a touch to display measurement values. The flowchart is shown Fig. 4.
Cost of thermoelectric waste heat generator In order to calculate the post-application cost and benefit of the TEG system accurately, it is first necessary to define the system and to select the scientifically correct evaluation methods. Scientifically, what is in question here is the cost and benefit evaluation of a renewable, smart, and grid-connected power plant based on thermoelectric waste heat recovery. The evaluation must be performed in line with this scientific definition. Since the new power plant built as a result of the project is a thermoelectric waste heat plant, the conventional efficiency definition is meaningless and unnecessary. Because the efficiency of thermoelectric generators comes from their small size and the fact that the heat converted into electricity in this case is waste heat, which is discharged to the environment in an uncontrolled manner, pollutes the environment, and has zero cost. Accordingly, instead of the conventional concept of efficiency in the thermoelectric generator science and technology, the concept used for TEGs is K (payback coefficient) = G (power sales revenue generated throughout the warranty period)/M (total cost of TEG). In this case, the condition of K = G/M > 1 must be met for a thermoelectric waste heat power plant to be profitable. Since the TEG system is a power plant relying on a renewable energy resource, the amount of incentive provided by the Turkish Energy Market Regulatory Authority, USD 0.133/kWhour, must be used to calculate G. Hardware and software design We decided to make a prototype in order to evaluate whether or not the TEG system would work on the relevant pipe surface. After deciding on the materials necessary for the prototype, we used the services of a professional mechanical design firm for mechanical drawings. Fig. 2 shows the drawings made in Autodesk Inventor Professional which include the final form of the 4-part TEG structure.
Fig. 2. A view of the TEG structure and the thermoelectric waste heat generator with a capacity of 150 W at ΔT = 100 °C. 4
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using a gas cylinder and tested. The generator worked without any issues. A LED strip block was used as load as shown in Fig. 5 in order to perform the load tests under laboratory environment. In this way, the project was completed by TES Ltd. and was ready for field application. Industrial application The industrial application of the TEG system was a first not only in Turkey, but also in the world. This did not only involve an application, but scientific findings were also obtained within a certain period of time and a theoretical examination was performed as well. When placing the TEG on the pipe, a heat insulation material was applied between the generator and the pipe to reduce the temperature on the pipe surface, which was 300–350 °C. The measurements performed on the insulation material showed a temperature of about 108 °C, while the temperature on the pipe surface was higher than 275 °C. The measurements were made with a FLUKE brand thermal imaging camera. The existing water circulation system of the industrial establishment was used to discharge heat from the cold surface of the STWHG and the flow rate of this system was measured to be 1200 l/h. AC and DC LED projectors were used as loads. Fig. 6 shows the industrial application environment. The open-circuit voltage and short-circuit current values of the TEG blocks when connected in series were measured. The power was calculated. The results are shown in Table 3. Simulation results Table 4 shows the catalog parameters of the modules used in the design of the STWHG. These values were calculated by entering catalog values into the simulation model. The simulation results and the application results were compared by using the temperature values obtained from the industrial application, TH and TC, in the simulation study. The simulation study showed that Voc would be 48.8 V and Isc would be 3.54 A if 20 modules were connected in series. The maximum Voc ∗ Isc = 43.16W . There was a STWHG power was calculated as P = 4 4.5% between the simulation value and the experimentally found power value, 41.3 W. According to the simulation results, the efficiency achieved at application temperatures was 2.15%. The difference between the application value and the simulation value for power arises from the module contact surfaces not being able to provide the necessary heat flow during application. Placing the STWHG on a circular surface causes challenges related to the application. Chimneys that funnel hot gas are subjected to deformations due to the temperature.
Fig. 4. Flowchart of control circuit.
Results and analysis Laboratory tests The TEG was designed to have 4 blocks and 5 TEG modules were used in each block. Two of these blocks are connected in series and the blocks connected in series can be switched to parallel by the control circuit. A mini water circulation system was setup in order to test the STWHG under laboratory conditions. A waste heat resource was formed
Fig. 5. LED performance test operations of the 4-block TEG. 5
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Fig. 6. View of the first operational smart thermoelectric waste heat power plant in Turkey AC and DC LED projectors. Table 3 Measurement results of the industrial application. TH (°C)
TC (°C)
ΔT (°C)
VOC (V)
ISC (A)
W (W)
114
37
77
51.6
3.2
41.3
Table 4 Data of the module used in the STWHG. Catalog Data TC (°C) TH (°C) N A (mm2) h (mm) Sizes (mm) VOC (V) ISC (A) Wmax (W) η max (%)
30 130 127 5.76 1.13 50 × 50 × 38 4 5.8 5.8 3.5
Effective Module Parameters α (µV/K) ρ (Ωcm) k (W/K)
157.5 × 10−6 1.203 × 10−3 0.011
Calculate Output Parameters VOC (V) ISC (A) Wmax (W) η max (%) Rin (Ω)
4 5.8 5.8 3.44 0.69
Fig. 7. Performance curves of the module.
simulation study. The results shown in Fig. 7 were used to make estimation for the application. The graphs show that, for instance, the power generated per module is 7.6 W and the thermal efficiency is 4.2% when ΔT = 100 °C. It is possible to achieve a power value of 20 × 7.6 W = 152 W when contact problems are eliminated. A power value of 342 W can be achieved for ΔT = 150 °C. In this case, the efficiency would be 6.1%. The current-dependent performance curves of the module were found to be as shown in Fig. 8. In the curve found for ΔT = 100 °C, the maximum power was achieved at 3.32 A and 2.3 V. In the industrial application, three different loads were connected under field conditions. The current and voltage values were measured and recorded for each load. The power was calculated. The load resistance was calculated based on the results, which can be seen in Fig. 8. The RL-W graph of the TEG was obtained for ΔT = 77 °C using the simulation and the experimental results were added to this graph. Fig. 9 shows the results obtained. As indicated by the graph, the simulation results and the experimental results were quite similar.
Table 5 Load-dependent measurement results. No
I (A)
V (V)
P (W)
RL
1 2 3
2.5 2.32 2.17
9.3 12.2 13.4
23.3 28.3 29.1
3.7 5.2 6.2
For this reason, various problems inevitably occur on contact surfaces (see Table 5). The ΔT-dependent graphs of the module were obtained using the 6
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$1250, and a revenue of $0.133 per kWh, the ΔT-dependent payback time was calculated. Fig. 10 shows the results of this calculation. The results show that the payback time rapidly decreases depending on ΔT. When ΔT = 100 °C, 152 W of power is achieved. While the payback time is estimated to be 7 years in this case, this drops to 1.7 years when ΔT = 200 °C. Since the TEG system is a power plant relying on a renewable energy resource, the amount of incentive provided by the Turkish Energy Market Regulatory Authority, USD 0.133/kWhour, must be used to calculate G. The post-application cost and benefit evaluation for an OnGrid TEG system, which was considered to be installed on hot pipes by a company, was performed separately for ΔT = 100 °C and ΔT = 200 °C. Since the cost value M is the same in both cases, let us calculate this first. 40 pieces of 4-block TEGs will be placed on a 20 m hot pipe and the total power produced by these TEGs will be P = 150 × 40 = 6 kW for ΔT = 100 °C and P = 600 × 40 = 24 kW for ΔT = 200 °C. The cost of this power plant will made up of the cost of the thermoelectric blocks plus the cost of the grid-tied inverter. The total cost of the TE power plant will be M = $50,000. Since P = 150 × 40 = 6 kW for ΔT = 100 °C, G = 6 × 24 × 365 × 5 × 0.133 = $34,952.4 and K = $34,952.4/$50,000 = 0.7 < 1. In this case, the payback time will be T = 5/K = 7.1 years. Also, there will be hot pipe insulation costs associated with this system. Additionally, the smart water heating system will provide hot water with a temperature of 60 °C. This water can, for instance, be used in a greenhouse or anywhere else. This will both reduce the cost and increase the revenue. Of course, this will reduce the payback time significantly. Since P = 600 × 40 = 24 kW for ΔT = 200 °C, G = 24 × 24 × 365 × 5 × 0.133 = $139,809.6 and K = $139,809.6/ $50000 = 2.8 > 1. In this case, the payback time will be T = 5 /K = 1.8 years. After 1.8 years, this will allow the company to generate a revenue by selling the electricity for 3.2 years until the warranty period is over and this revenue will be approximately $90,000. Since the life time of the modules is 25 years, the revenue generated by the company will be approximately $750,000 until the end of module life cycle. Table 6 shows the change in the value of the power generated by the thermoelectric power plant and the costs associated at the end of the first 5 years and 25 years depending on temperature difference. When ΔT = 100 °C, the power plant begins to profit after 6 years and the profit will be 13.3/4 = 3.3 times higher at the end of 25 years. Also, the temperature difference necessary for the power plant to begin to profit at the end of the warranty period is ΔT = 120 °C and the profit will be 13.3/3 = 4.4 times higher at the end of 25 years. When ΔT = 200 °C, the power plant begins to profit after 2 years and the profit will be 13.3/5 = 2.7 times higher at the end of the warranty period and 13.3/1 = 13.3 times higher at the end of 25 years. Again, as shown in the table, the temperature difference must be ΔT = 270 °C in order to begin to profit in the first year. In this case, the profit of the power plant will be 13.3/3 = 4.4 times higher at the end of the warranty period and 13.3/1 = 13.3 times higher at the end of 25 years. Of course, the installation of this power plant will eliminate the insulation and hot water production problems of the company, which will lead to even higher profits. Additionally, it will be possible to achieve higher profits within shorter time periods by using more powerful thermoelectric modules. TES Ltd. is the only company in Turkey that designs and produces modules. Fig. 11 shows the properties of the On-Grid TEG system to be produced by TES Ltd. The essential cost of the thermoelectric power plant is the thermoelectric module cost. By reducing the module costs, it is possible that the unit cost of the power generated using the TEG and the payback time will be reduced as well.
Fig. 8. Current-dependent V, W graphs.
Fig. 9. RL-W graphs.
Fig. 10. ΔT-Payback time graph.
It is necessary to know the warranty time (years), TEG cost ($), and the sales price of the energy generated ($/kWh) in order to perform a cost analysis for TEGs. Assuming a warranty time of 5 years, a cost of
Conclusion Striking results are obtained when the scientific data shown in the 7
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thermoelectric waste heat generator (STWHG) under different temperature, load and series condition. STWHG was designed and tested under different operating conditions in the laboratory. The simulated parameters are then compared with experimental test results. STWHG was installed in industrial establishment. The physical parameters under real working conditions were measured and compared with the simulation results. Using the data obtained, the payback coefficient was calculated and the payback coefficient of the power plant was found K = G/M > 1. Using the simulation, the break-event points were calculated for different ΔTs. The results obtained in this study show that TE technology is the most important alternative in converting waste heat to electrical energy in industrial systems. The designed system produces 150 W power at 100 °C temperature difference. The payback time of the system is calculated as 6 years. The hot surface temperatures of the modules used are maximum 200 °C. Therefore, heat insulation material is placed between the heat source and the modules. It is possible to increase the temperature difference by designing TEG with modules used at higher temperatures. In TEG systems, power increases in proportion to the square of the temperature difference. In this application, when the temperature difference is increased 2 times, the payback time decreases up to 2 years. Considering factors such as low installation costs of TE systems and low maintenance costs, TEG's is highly feasible in terms of waste heat recovery and energy efficiency.
Table 6 Change in TEG costs depending on temperature difference. ΔT
P800 kW
f1 USD/ kWh
f2 USD/ kWh
f3 USD/ kWh
f4 USD/ kWh
f5 USD/ kWh
f25 USD/ kWh
10 20 30 40 50 60 70 80 90 100 110 120 130 140 150 160 170 180 190 200 210 220 230 240 250 260 270 280
0.1 0.2 0.6 1.0 1.5 2.2 3.0 3.9 5.0 6.2 7.5 8.9 10.4 12.1 13.9 15.8 17.8 20.0 22.2 24.6 27.2 29.8 32.6 35.5 38.5 41.6 44.9 48.3
92.66 23.16 10.30 5.79 3.71 2.57 1.89 1.45 1.14 0.93 0.77 0.64 0.55 0.47 0.41 0.36 0.32 0.29 0.26 0.23 0.21 0.19 0.18 0.16 0.15 0.14 0.13 0.12
46.33 11.58 5.15 2.90 1.85 1.29 0.95 0.72 0.57 0.46 0.38 0.32 0.27 0.24 0.21 0.18 0.16 0.14 0.13 0.12 0.11 0.10 0.09 0.08 0.07 0.07 0.06 0.06
30.89 7.72 3.43 1.93 1.24 0.86 0.63 0.48 0.38 0.31 0.26 0.21 0.18 0.16 0.14 0.12 0.11 0.10 0.09 0.08 0.07 0.06 0.06 0.05 0.05 0.05 0.04 0.04
23.16 5.79 2.57 1.45 0.93 0.64 0.47 0.36 0.29 0.23 0.19 0.16 0.14 0.12 0.10 0.09 0.08 0.07 0.06 0.06 0.05 0.05 0.04 0.04 0.04 0.03 0.03 0.03
18.53 4.63 2.06 1.16 0.74 0.51 0.38 0.29 0.23 0.19 0.15 0.13 0.11 0.09 0.08 0.07 0.06 0.06 0.05 0.05 0.04 0.04 0.04 0.03 0.03 0.03 0.03 0.02
3.71 0.93 0.41 0.23 0.15 0.10 0.08 0.06 0.05 0.04 0.03 0.03 0.02 0.02 0.02 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.00
CRediT authorship contribution statement Gunay Omer: . : Writing - review & editing. Abdullah Hakan Yavuz: . : Investigation, Software. Rasit Ahiska: Conceptualization, Methodology. Kagan Ekrem Calisal: Resources, Funding acquisition. Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Acknowledgements This research is sponsored by Petkim Petrochemical Holding. References [1] Emeksiz C, Demirci B. The determination of offshore wind energy potential of Turkey by using novelty hybrid site selection method. Sustainable Energy Technol Assess 2019;36:1–21. https://doi.org/10.1016/j.seta.2019.100562. [2] Emeksiz C, Cetin T. In case study: investigation of tower shadow disturbance and wind shear variations effects on energy production, wind speed and power characteristics. Sustainable Energy Technol Assess 2019;35:148–59. https://doi.org/10. 1016/j.seta.2019.07.004. [3] Wolley E, Luo Y, Simeone A. Industrial waste heat recovery: a systematic approach. Sustainable Energy Technol Assess 2018;29:50–9. [4] Tongcai W, Weiling L, Tongjun L, Shan-Tung T, Jinyue Y. Performance enhancement of thermoelectric waste heat recovery system by using metal foam inserts. Energy Convers Manage 2016;124:13–9. https://doi.org/10.1016/j.enconman. 2016.07.006. [5] Aranguren P, Araiz M, Astrain D, Martínez A. Thermoelectric generators for waste heat harvesting: a computational and experimental approach. Energy Convers Manage 2017;148:680–91. https://doi.org/10.1016/j.enconman.2017.06.040. [6] Dongxu J, Zhongbao W, Stefano M, Marco M, Srithar R, Jiyun Z, et al. Thermoelectric generation for waste heat recovery: application of a system level design optimization approach via Taguchi method. Energy Convers Manage 2018;172:507–16. https://doi.org/10.1016/j.enconman.2018.06.016. [7] Gunay O, Abdullah HY, Rasit A. Heat pipes thermoelectric solar collectors for energy applications. Int J Hydrogen Energy 2017;42:8310–3. https://doi.org/10. 1016/j.ijhydene.2017.01.132. [8] Kirill AA, Andrea B, Aldo B, Techno-economic analysis of combined inverted Brayton – organic Rankine cycle for high-temperature waste heat recovery. Energy Convers Manage: X Available online 6 July 2019, 100014 in press. doi: 10.1016/j. ecmx.2019.100014. [9] Moh'd AA, Ahmed AA. Internal combustion engine waste heat recovery by a thermoelectric generator inserted at combustion chamber walls. Int J Energy Res
Fig. 11. Power generation capacity of the grid-tied TEG depending on temperature difference.
table are analyzed in terms of the company’s benefit. This analysis must be based on the incentive amount provided by the Turkish EMRA, which is $0.133 per kWh, and the warranty period of the TE modules, which is 5 years. The power generation capacity of a TEG is directly proportional to the square of the temperature difference between the surfaces of the thermoelectric module. An accurate cost analysis of a thermoelectric generator is only possible after a survey on the heat resource. Therefore, similar to other renewable energy resources, a survey must be conducted for each waste heat resource and the thermoelectric system utilizing this resource as in the company in question. A scientifically accurate examination and interpretation of the table given above clearly show how important the thermoelectric technology is and that this technology is one of the most significant technologies of the 21st century and beyond, and explain why scientific studies and billions of dollars of investments increasingly continue in this field around the world. In this study, MATLAB simulation is used to simulate the 8
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2015;97:265–72. https://doi.org/10.1016/j.enconman.2015.03.068. [14] Tsai HL, Lin JM. Model building and simulation of thermoelectric module using Matlab/Simulink. J Electron Mater 2009;39:2105–11. https://doi.org/10.1007/ s11664-009-0994-x. [15] Abdulmunaem HE, Hassan F, Housung L, Alaa A. Theoretical approach to predict the performance of thermoelectric generator modules. J Electron Mater 2017;46(2):872–81. https://doi.org/10.1007/s11664-016-4948-9. [16] Ahıska R, Dislitas S. Computer controlled test system for measuring the parameters of the real thermoelectric module. Energy Convers Manage 2011;52:27–36. https:// doi.org/10.1016/j.enconman.2010.06.023. [17] Ahıska R, Mamur H. Development and application of a new power analysis system for testing of geothermal thermoelectric generators. Int J Green Energy 2016;13(7):672–81. https://doi.org/10.1080/15435075.2015.1017102.
2018;42:4853–65. https://doi.org/10.1002/er.4241. [10] Tae-Hyeon K, Sanghyeon K, Dae-Han J, Dae-Myeong G. A highly-efficient, concentrating-photovoltaic/thermoelectric hybrid generator. Nano Energy 2017;37:242–7. https://doi.org/10.1016/j.nanoen.2017.05.023. [11] Xiaofei Z, Wenqiang G, Xiaowen S, Fulei W, Baishan L, Jian-Jun W, et al. Conversion of solar power to chemical energy based on carbon nanoparticle modified photo-thermoelectric generator and electrochemical water splitting system. Nano Energy 2018;48:481–8. https://doi.org/10.1016/j.nanoen.2018.03.055. [12] Szobolovszky R, Siffalovic P, Hoads M, Jergel M, Sabol D, Macha M, et al. Waste heat recovery in solid-state based on thin film thermoelectric generators. Sustainable Energy Technol Assess 2016;18:1–5. https://doi.org/10.1016/j.seta. 2016.09.005. [13] Ahıska R, Mamur H. Application of a DC–DC boost converter with maximum power point tracking for low power thermoelectric generators. Energy Convers Manage
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Contents lists available at ScienceDirect
Sustainable Energy Technologies and Assessments journal homepage: www.elsevier.com/locate/seta
Smart thermoelectric waste heat generator: Design, simulation and cost analysis
T
⁎
Gunay Omera, Abdullah Hakan Yavuzb, , Rasit Ahiskac, Kagan Ekrem Calisald a
Program of Radiotherapy, Vocational School of Health Services, Ankara Medipol University, Ankara, Turkey Faculty of Engineering and Natural Sciences, Gaziosmanpasa University, Tokat, Turkey c Department of Physics, Faculty of Science, Gazi University, Ankara, Turkey d Petkim Petrochemical Holding, Izmir, Turkey b
A R T I C LE I N FO
A B S T R A C T
Keywords: Thermoelectric Waste heat recovery Thermoelectric generators Matlab simulation Payback coefficient
Globally one third of energy consumption is attributable to the industrial sector, with up to fifty percent ultimately wasted as heat. Waste heat is difficult to identify and evaluate both in terms of quantity and quality. Therefore, waste heat recovery is very important in terms of reducing energy costs and environmental impacts. The method used for waste heat recovery must be feasible. In this study, we produced an environmentally friendly and electric- and water-saving smart thermoelectric waste heat generator (STWHG), performed laboratory and fields tests for the generator, and examined power and cost parameters of a STWHG power plant with a capacity of 150 W at ΔT = 100 °C installed in an industrial establishment. We performed MATLAB simulations for real working conditions of TEG modules used in the production of STWHG as well as the entire power plant, and compared the results with directly measured parameters. The payback coefficient of power plant was K = G/M > 1. When ΔT = 100 °C, the power plant begins to profit after 6 years. The results show that the thermoelectric waste heat power plants was very profitable and feasible.
Introduction The optimal and smart usage of source of energy is important due to increasing energy demands. Existing energy resources are limited. Most studies show that fossil fuels will be depleted in the near future, and harmful effects such as greenhouse gases that are generated by the use of these fuels cause global warming. Therefore, the use of renewable energy sources is increasing to reduce greenhouse gas emissions and protect fossil fuel reserves. Efficient use of energy in terms of sustainability is also important [1,2]. One third of energy consumption is used to industrial sector. However, about 50% of the energy used is released as waste heat. Due to increasing energy demand and limited fossil fuels, it is likely that the future will bring increased energy prices. Therefore, the recovery of waste heat is important in terms of energy efficiency [3]. The foundation of the thermoelectric (TE) industry was laid with the discovery of the Seebeck and Peltier effect in early 19th century. However, thermoelectric modules (TEM) did not become wide-spread due to their low efficiency when used as a generator (TEG). In parallel with developments in the semi-conductor technology in mid-20th century, TEGs began to be used in practice. While the industrialization
⁎
around the world within this period is causing pollution, it is also constantly increasing the demand for electrical energy as well. The most important consequence of industrialization that causes environmental pollution is waste heat. As thermoelectric technology converts heat energy directly electrical energy, it is one of important alternatives for the recovery of waste heat. In recent years, there have been more and more studies on the utilization of waste heat using TEGs. Significant improvements have been achieved in TEG efficiency thanks to the developments in TE materials and technology. Comprehensive experimental studies have been conducted on thermoelectric waste heat recovery systems with metal foam placed inside heat flow paths in order to increase heat flow intensity. In one study, using metal foam in the system resulted in an increase of 29.75% in efficiency depending on foam density [4]. Waste heat recovery test data is quite expensive to collect. Therefore, simulation studies are important for TEGs to be designed at high temperatures and under real working conditions. In one experimental and simulative study on TEGs, simulation results were shown to overlap with experimental results with an accuracy of ± 12% [5]. In one study on 5 important parameters of the module that affect the TEG performance (height, length, area, gap, and heat transfer material), height was
Corresponding author. E-mail address: [email protected] (A.H. Yavuz).
https://doi.org/10.1016/j.seta.2019.100623 Received 19 October 2019; Received in revised form 19 December 2019; Accepted 28 December 2019 2213-1388/ © 2019 Published by Elsevier Ltd.
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QC=2N [αITC + 0.5I 2R + K ΔT
shown to have the most effect on the module performance. TEG application tests conducted on internal combustion engines showed that height affected the output power by 30.25–69.6% [6]. While generating energy, TEGs eliminate the hazardous heat dissipated to the environment. The temperature difference between the surfaces needs to be increased in order to improve TEG performance. A water circulation system was used as the hot surface heat transfer system in one study performed using heat pipe in a solar system. In this study, heat pipe was used to transfer heat from hot surface. The system developed also allowed for successfully producing hot water by transferring the discharged heat to water [7]. Many practical cases with waste heat recovery potential such as exhaust gases of reciprocating engines, cement kilns or heat-treating furnaces, are nowadays often integrated with organic Rankine cycle (ORC) to convert waste heat to the mechanical power. However, when dealing with high-temperature waste heat, organic Rankine cycle faces efficiency limit due to the physical properties of the working and thermal fluids. Increased installation costs and practical difficulties at high temperature applications reveal the disadvantages of ORC methods [8]. A power production of 600 W was achieved with TEMs placed on inner walls of internal combustion engines. An efficiency increase of 2.75% was also achieved at 4000 RPM [9]. Thermoelectric generators are used in hybrid systems with other systems to increase efficiency. By using solar concentration systems, heat density is increased and efficiency is increased [10]. Studies on thermoelectric materials have shown that module efficiency can be increased 34 times by using carbon particles [11]. These developments in thermoelectric technology lead researchers to TEG applications. TE technology is used in various fields in waste heat recovery systems. A study has been done on waste heat recovery of white high power leds. With the proposed waste heat recovery system, high heat fluxes have been shown to convert about 1% into electrical energy. Even at this rate, it is possible to achieve significant energy savings on a global scale [12]. In this study, MATLAB simulation is used to simulate the thermoelectric waste heat generator (STWHG) under different temperature, load and series condition. STWHG was designed and tested under different operating conditions in the laboratory. The simulated parameters are then compared with experimental test results. STWHG was installed in industrial establishment. The physical parameters under real working conditions were measured and compared with the simulation results. Using the data obtained, the payback coefficient was calculated and the payback coefficient of the power plant was found K = G/ M > 1. Using the simulation, the break-event points were calculated for different ΔTs.
QH = 2N [αITH −
0.5I 2R
(1) (2)
+ K ΔT ]
Here, QC (W ) is the thermal power absorbed from the cold surface, QH (W ) is the thermal power ejected from the hot surface, R = ρL/ A (Ω) is the total resistance of the module, α (V/K) is the Seebeck coefficient, I (A) is the current drawn from the module, TC (K ) is the temperature of the cold surface, TH (K ) is the temperature of the hot surface, ΔT (K) is the temperature difference between the surfaces (TH − TC ), and K (W/ K) is the thermal heat transfer coefficient of the module. ρ (Ωcm) is the resistivity of the semi-conductors used in the module, k (W / K ) is the thermal conductivity of the semi-conductors, A (cm2) is the footprint area of the semi-conductors, L (cm) is the height of the semi-conductors, and N is the number of thermoelements used in the module. Since the output power of the thermoelectric generator is W = QH − QC , W is obtained as in equation (3) using equations (1) and (2).
W = 2N [α ΔT − I 2R]
(3)
Since the output power changes depending on the load resistance, if the equation is arranged using W = 2NI 2RL = IV , the voltage (V) at the thermoelectric generator output is obtained as in equation (4).
V = 2N [α (TH − TC ) − RI ]
(4)
As shown in Fig. 1, when a load is connected to the ends of the module, a current passes through the load. The load current, voltage, and power generated are expressed as in equations 5–7.
I=
α (TH − TC ) RL + R
V=
2Nα (TH − TC ) RL RL + R
(5)
2Nα 2 (TH
(6)
)2
− TC RL (RL + R)2
W=
(7)
The thermal efficiency is expressed as η = obtained when it is expressed as m =
η=
(1 − ) m (1 + m) − 0.5 (1 − ) +
RL . R
W , QH
and equation (8) is
TC TH
TC TH
T (1 + m)2 C
TH
ZTC
(8)
α2 , ρk
which is the Figure of Merit (FOM). As is known, the Here, Z = condition of RL = R must be met in order to achieve maximum power transfer. In this case, the resistance ratio is m = 1. When RL = 0, then V = 0 and the current is at maximum (ISC). When RL = infinite, then I = 0 and the voltage is at maximum (VOC). VOC and ISC are expressed as in equations 9–10.
Material and methods Material
ISC =
The basic structure of TEGs is formed by p- and n-type semiconductor thermoelements (TEs). TEs are connected electrically in a serial manner to increase the output voltage of the TEG and connected thermally in parallel to decrease the thermal resistance of the TEG. The structure and the equivalent circuit of a TEG have been given, in Fig. 1 [13]. TEM devices can typically be classified into thermoelectric generators (TEGs) and thermoelectric coolers (TECs). TEGs convert thermal energy from a temperature gradient to electrical energy (Seebeck effect), whereas TECs convert electrical energy into a temperature gradient (Peltier effect) [14]. When a TEM is run as a generator, there must be a temperature difference between the surfaces. This allows for heat transfer from one surface to another. When a load is connected to the ends of the TEM, a current passes through the load and generates power. Equations 1–5 show the thermal equations for a TEM used in the generator mode.
α ΔT R
(9) (10)
VOC = 2Nα ΔT
To find the maximum power value, if the numerator and the deR nominator in equation (7) are divided by R, m = RL = 1 is placed in the equation, the derivative is calculated according to m and equalized to 0, then the maximum power Wmax and the maximum efficiency ηmax are expressed as in equations 11–12.
Wmax =
2Nα 2 (TH − TC )2 4R
(1 + ZTave − 1 T ηmax = ⎛1 − C ⎞ T T (1 + Z Tave − TC H⎠ ⎝ H ⎜
(11)
⎟
(12)
Here, Tave = (TH + TC )/2 . The load maximum voltage value Vmax, the load maximum current value Imax, and the load maximum thermal 2
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Fig. 1. A TEM in the generator mode and the equivalent circuit of the TEM.
Method
efficiency value ηmaxp are expressed as in equations (13) and (14).
Imax =
α (TH − TC ) 2R
(13)
Vmax =
2Nα (TH − TC ) 2
(14)
ηmaxp =
(1 − ) (2) − 0.5 (1 − ) +
TEG MATLAB simulation In TEG systems, the goal is to achieve maximum output performance. As indicated by the TEG thermal and electrical equations given in the previous section, the output performance changes depending on the geometric properties, semi-conductor’s properties, and temperature. In this study, a model was created in order to design the most appropriate system according to effective parameters for TEG modules. Designing a system which can produce system performance curves using input parameters (ρ, α, k, A, h) of a single TE and depending on the number of thermoelements and the estimated application temperature values provides great convenience in terms of application. The interface of the model developed. The simulation study can also calculate the effective material properties according to the catalog data. The effective material properties are parameters that also include the dynamic working parameters of the module in question. Designing the system using these parameters is important for obtaining results that are closest to a real application [15]. Another concern in renewable energy studies is the cost and payback time. The model developed in this study allows for calculating and evaluating parameters related to the payback time as well. This model can be used both in TEM design stage and large-scale generator modeling designed using TEMs. HZ-2, a commercial module manufactured by Hi-Z, and TGM199-1.4-2.0, a commercial module manufactured by Kyrotherm, were used to test the reliability of the model. Table 1 shows the parameters belonging to these models. The parameters shown in Table 1 were entered into the simulation study, which produced the output parameters. Table 2 shows the results comparatively. A comparison between the results obtained from the simulation study and the catalog information showed that the parameters in question were very similar. The results indicate that the model is reliable. The simulation study allows for calculating effective semiconductor material parameters by entering the experimentally measured parameters of any module into the system. Performance curves and current-
TC TH
TC TH
T 4 C
TH
ZTC
(15)
TEG manufacturers provide the catalog data related to the parameters of ISC, VOC, Wmax, and η max depending on the values of TH and TC. Values obtained by using thermoelectric ideal equations are usually different from experimentally found data. This is because ideal equations do not include changes in semi-conductor materials depending on temperature, do not consider losses such as the Thomson effect, and ignore losses caused by thermal resistances. It is quite difficult to consider these losses. It is possible to find effective material parameters based on the experimental data given for TEG modules. The maximum module parameters and the effective parameters depending on geometric properties are expressed as in equation 16–19 [15]. A
ρe =
4( L ) Wmax 2NImax 2
(16)
αe =
4Wmax 2NImax (TH − TC )
Ze =
max C 1 ⎛ ⎛ 1 + ηC TH ⎜ η Tave ⎜ ⎜⎜ 1 − max ηC ⎝⎝
η
ke =
αe 2 Ze ρe
T
(17) 2
⎞ ⎞ ⎟⎟ − 1⎟ ⎟ ⎠ ⎠
(18)
(19)
Here, ηC = (1 − TC / TH ) is the Carnot efficiency. Effective material properties calculated in this way include contact resistances, Thomson heat losses, and heat losses caused by radiation and convection. Similar to the new method previously developed for TECs based on the equations given above, the foundation for a new method was laid for TEGs in this study. The formulas were used to find the basic parameters after recoding Imax, Wmax, TH, and TC, which were easily measured using this method developed for TEGs. Similar to TEPAS, a TEGPAS (Thermoelectric Generator Performance Analysis System) system was also created to examine TEG modules or TEG systems [13,16,17]. Additionally, MATLAB simulations were developed for the formulas above, which were used for theoretical examination of the TEG system.
Table 1 HZ-2 and TGM199-1.4-2.0 catalog data.
TC (°C) TH (°C) N A (mm2) h (mm) Sizes (mm) α (µV/K) ρ (Ωcm) k (W/K)
3
HZ-2
TGM199-1.4-2.0
30 230 97 2.1 2.87 30 × 30 × 4.5 167.526 1.532 × 10−3 0.016
30 200 199 1.96 2 40 × 40 × 4.4 162.856 1.024 × 10−3 0.015
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Table 2 Comparison between simulation and catalog data. HZ-2 Simulation Data
HZ-2 Catalog Data
TGM199-1.4-2.0 Simulation Data
TGM199-1.42.0 Catalog Data
R = 4.062 Ω ISC = 1.60 A VOC = 6.50 V Wmax = 2.60 V η max = 4.546%
R=4Ω ISC = 1.60 A VOC = 6.50 V Wmax = 2.60 V η max = 4.5%
R = 4.159 Ω ISC = 2.65 A VOC = 11.02 V Wmax = 7.3 V η max = 4.35%
R = 3.7 Ω ISC = 2.65 A VOC = 11 V Wmax = 7.3 V η max = 5.3%
dependent output parameters of the module under various temperature differences and at various load resistances can be determined using the model. Additionally, it is possible to obtain preliminary information about the total system performance by entering the number of series and parallel modules to be used in a generator to be designed using the tested module into the simulation study. Since the simulation results were quite similar to the catalog data, it is obvious that these can be used to design larger systems.
Fig. 3. STWHG application diagram.
The surface of the pipe used in the project varies between approximately 400 °C and 440 °C depending on the process (the output load of the gas turbine). This surface temperature is a high temperature value for the thermoelectric modules to be used in the project, which are produced in the laboratory of TES Thermoelectric Systems Ltd. in Ankara. The steady-state working temperature value of the modules to be used in the project varies from 150 °C to 200 °C at most. The aluminum surface smoother designed for the project formed a smooth surface for healthy contact of the modules to the hot surface and reduced the temperature picked up by the modules to an appropriate value. On the cold surface side, the same type of aluminum material was used to construct a water-cooled system. The process water of the company’s closed-loop cooling system, the temperature of which varies from 26 °C to 32 °C depending on the season, was circulated within this system. Fig. 3 shows the application diagram of the thermoelectric generator. The control circuit allows for measuring the temperature, current, and voltage on the system. The ATMEGA 328 microcontrollerbased control circuit is used for switching the TEGs, which were designed as two blocks, to series and to parallel. The input of the charge control circuit in the control circuit has the limit values of maximum 75 V and 20 A. In order to avoid exceeding these values, the control circuit switches the TEGs to parallel when the measured voltage value exceeds 60 V by controlling 2 relays. When the voltage value drops below 25 V, the circuit switches the TEGs to series. While the TEG outputs feed the charge regulator, it is possible to feed DC loads using the accumulator and to feed AC loads using the inverter. The control circuit also serves as a Data Logger. The control circuit has Wi-Fi connection capabilities; therefore, it is possible to collect data remotely if there is internet infrastructure. It is also possible to collect data directly on-site using a PC. The control circuit is equipped with a touch to display measurement values. The flowchart is shown Fig. 4.
Cost of thermoelectric waste heat generator In order to calculate the post-application cost and benefit of the TEG system accurately, it is first necessary to define the system and to select the scientifically correct evaluation methods. Scientifically, what is in question here is the cost and benefit evaluation of a renewable, smart, and grid-connected power plant based on thermoelectric waste heat recovery. The evaluation must be performed in line with this scientific definition. Since the new power plant built as a result of the project is a thermoelectric waste heat plant, the conventional efficiency definition is meaningless and unnecessary. Because the efficiency of thermoelectric generators comes from their small size and the fact that the heat converted into electricity in this case is waste heat, which is discharged to the environment in an uncontrolled manner, pollutes the environment, and has zero cost. Accordingly, instead of the conventional concept of efficiency in the thermoelectric generator science and technology, the concept used for TEGs is K (payback coefficient) = G (power sales revenue generated throughout the warranty period)/M (total cost of TEG). In this case, the condition of K = G/M > 1 must be met for a thermoelectric waste heat power plant to be profitable. Since the TEG system is a power plant relying on a renewable energy resource, the amount of incentive provided by the Turkish Energy Market Regulatory Authority, USD 0.133/kWhour, must be used to calculate G. Hardware and software design We decided to make a prototype in order to evaluate whether or not the TEG system would work on the relevant pipe surface. After deciding on the materials necessary for the prototype, we used the services of a professional mechanical design firm for mechanical drawings. Fig. 2 shows the drawings made in Autodesk Inventor Professional which include the final form of the 4-part TEG structure.
Fig. 2. A view of the TEG structure and the thermoelectric waste heat generator with a capacity of 150 W at ΔT = 100 °C. 4
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using a gas cylinder and tested. The generator worked without any issues. A LED strip block was used as load as shown in Fig. 5 in order to perform the load tests under laboratory environment. In this way, the project was completed by TES Ltd. and was ready for field application. Industrial application The industrial application of the TEG system was a first not only in Turkey, but also in the world. This did not only involve an application, but scientific findings were also obtained within a certain period of time and a theoretical examination was performed as well. When placing the TEG on the pipe, a heat insulation material was applied between the generator and the pipe to reduce the temperature on the pipe surface, which was 300–350 °C. The measurements performed on the insulation material showed a temperature of about 108 °C, while the temperature on the pipe surface was higher than 275 °C. The measurements were made with a FLUKE brand thermal imaging camera. The existing water circulation system of the industrial establishment was used to discharge heat from the cold surface of the STWHG and the flow rate of this system was measured to be 1200 l/h. AC and DC LED projectors were used as loads. Fig. 6 shows the industrial application environment. The open-circuit voltage and short-circuit current values of the TEG blocks when connected in series were measured. The power was calculated. The results are shown in Table 3. Simulation results Table 4 shows the catalog parameters of the modules used in the design of the STWHG. These values were calculated by entering catalog values into the simulation model. The simulation results and the application results were compared by using the temperature values obtained from the industrial application, TH and TC, in the simulation study. The simulation study showed that Voc would be 48.8 V and Isc would be 3.54 A if 20 modules were connected in series. The maximum Voc ∗ Isc = 43.16W . There was a STWHG power was calculated as P = 4 4.5% between the simulation value and the experimentally found power value, 41.3 W. According to the simulation results, the efficiency achieved at application temperatures was 2.15%. The difference between the application value and the simulation value for power arises from the module contact surfaces not being able to provide the necessary heat flow during application. Placing the STWHG on a circular surface causes challenges related to the application. Chimneys that funnel hot gas are subjected to deformations due to the temperature.
Fig. 4. Flowchart of control circuit.
Results and analysis Laboratory tests The TEG was designed to have 4 blocks and 5 TEG modules were used in each block. Two of these blocks are connected in series and the blocks connected in series can be switched to parallel by the control circuit. A mini water circulation system was setup in order to test the STWHG under laboratory conditions. A waste heat resource was formed
Fig. 5. LED performance test operations of the 4-block TEG. 5
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Fig. 6. View of the first operational smart thermoelectric waste heat power plant in Turkey AC and DC LED projectors. Table 3 Measurement results of the industrial application. TH (°C)
TC (°C)
ΔT (°C)
VOC (V)
ISC (A)
W (W)
114
37
77
51.6
3.2
41.3
Table 4 Data of the module used in the STWHG. Catalog Data TC (°C) TH (°C) N A (mm2) h (mm) Sizes (mm) VOC (V) ISC (A) Wmax (W) η max (%)
30 130 127 5.76 1.13 50 × 50 × 38 4 5.8 5.8 3.5
Effective Module Parameters α (µV/K) ρ (Ωcm) k (W/K)
157.5 × 10−6 1.203 × 10−3 0.011
Calculate Output Parameters VOC (V) ISC (A) Wmax (W) η max (%) Rin (Ω)
4 5.8 5.8 3.44 0.69
Fig. 7. Performance curves of the module.
simulation study. The results shown in Fig. 7 were used to make estimation for the application. The graphs show that, for instance, the power generated per module is 7.6 W and the thermal efficiency is 4.2% when ΔT = 100 °C. It is possible to achieve a power value of 20 × 7.6 W = 152 W when contact problems are eliminated. A power value of 342 W can be achieved for ΔT = 150 °C. In this case, the efficiency would be 6.1%. The current-dependent performance curves of the module were found to be as shown in Fig. 8. In the curve found for ΔT = 100 °C, the maximum power was achieved at 3.32 A and 2.3 V. In the industrial application, three different loads were connected under field conditions. The current and voltage values were measured and recorded for each load. The power was calculated. The load resistance was calculated based on the results, which can be seen in Fig. 8. The RL-W graph of the TEG was obtained for ΔT = 77 °C using the simulation and the experimental results were added to this graph. Fig. 9 shows the results obtained. As indicated by the graph, the simulation results and the experimental results were quite similar.
Table 5 Load-dependent measurement results. No
I (A)
V (V)
P (W)
RL
1 2 3
2.5 2.32 2.17
9.3 12.2 13.4
23.3 28.3 29.1
3.7 5.2 6.2
For this reason, various problems inevitably occur on contact surfaces (see Table 5). The ΔT-dependent graphs of the module were obtained using the 6
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$1250, and a revenue of $0.133 per kWh, the ΔT-dependent payback time was calculated. Fig. 10 shows the results of this calculation. The results show that the payback time rapidly decreases depending on ΔT. When ΔT = 100 °C, 152 W of power is achieved. While the payback time is estimated to be 7 years in this case, this drops to 1.7 years when ΔT = 200 °C. Since the TEG system is a power plant relying on a renewable energy resource, the amount of incentive provided by the Turkish Energy Market Regulatory Authority, USD 0.133/kWhour, must be used to calculate G. The post-application cost and benefit evaluation for an OnGrid TEG system, which was considered to be installed on hot pipes by a company, was performed separately for ΔT = 100 °C and ΔT = 200 °C. Since the cost value M is the same in both cases, let us calculate this first. 40 pieces of 4-block TEGs will be placed on a 20 m hot pipe and the total power produced by these TEGs will be P = 150 × 40 = 6 kW for ΔT = 100 °C and P = 600 × 40 = 24 kW for ΔT = 200 °C. The cost of this power plant will made up of the cost of the thermoelectric blocks plus the cost of the grid-tied inverter. The total cost of the TE power plant will be M = $50,000. Since P = 150 × 40 = 6 kW for ΔT = 100 °C, G = 6 × 24 × 365 × 5 × 0.133 = $34,952.4 and K = $34,952.4/$50,000 = 0.7 < 1. In this case, the payback time will be T = 5/K = 7.1 years. Also, there will be hot pipe insulation costs associated with this system. Additionally, the smart water heating system will provide hot water with a temperature of 60 °C. This water can, for instance, be used in a greenhouse or anywhere else. This will both reduce the cost and increase the revenue. Of course, this will reduce the payback time significantly. Since P = 600 × 40 = 24 kW for ΔT = 200 °C, G = 24 × 24 × 365 × 5 × 0.133 = $139,809.6 and K = $139,809.6/ $50000 = 2.8 > 1. In this case, the payback time will be T = 5 /K = 1.8 years. After 1.8 years, this will allow the company to generate a revenue by selling the electricity for 3.2 years until the warranty period is over and this revenue will be approximately $90,000. Since the life time of the modules is 25 years, the revenue generated by the company will be approximately $750,000 until the end of module life cycle. Table 6 shows the change in the value of the power generated by the thermoelectric power plant and the costs associated at the end of the first 5 years and 25 years depending on temperature difference. When ΔT = 100 °C, the power plant begins to profit after 6 years and the profit will be 13.3/4 = 3.3 times higher at the end of 25 years. Also, the temperature difference necessary for the power plant to begin to profit at the end of the warranty period is ΔT = 120 °C and the profit will be 13.3/3 = 4.4 times higher at the end of 25 years. When ΔT = 200 °C, the power plant begins to profit after 2 years and the profit will be 13.3/5 = 2.7 times higher at the end of the warranty period and 13.3/1 = 13.3 times higher at the end of 25 years. Again, as shown in the table, the temperature difference must be ΔT = 270 °C in order to begin to profit in the first year. In this case, the profit of the power plant will be 13.3/3 = 4.4 times higher at the end of the warranty period and 13.3/1 = 13.3 times higher at the end of 25 years. Of course, the installation of this power plant will eliminate the insulation and hot water production problems of the company, which will lead to even higher profits. Additionally, it will be possible to achieve higher profits within shorter time periods by using more powerful thermoelectric modules. TES Ltd. is the only company in Turkey that designs and produces modules. Fig. 11 shows the properties of the On-Grid TEG system to be produced by TES Ltd. The essential cost of the thermoelectric power plant is the thermoelectric module cost. By reducing the module costs, it is possible that the unit cost of the power generated using the TEG and the payback time will be reduced as well.
Fig. 8. Current-dependent V, W graphs.
Fig. 9. RL-W graphs.
Fig. 10. ΔT-Payback time graph.
It is necessary to know the warranty time (years), TEG cost ($), and the sales price of the energy generated ($/kWh) in order to perform a cost analysis for TEGs. Assuming a warranty time of 5 years, a cost of
Conclusion Striking results are obtained when the scientific data shown in the 7
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thermoelectric waste heat generator (STWHG) under different temperature, load and series condition. STWHG was designed and tested under different operating conditions in the laboratory. The simulated parameters are then compared with experimental test results. STWHG was installed in industrial establishment. The physical parameters under real working conditions were measured and compared with the simulation results. Using the data obtained, the payback coefficient was calculated and the payback coefficient of the power plant was found K = G/M > 1. Using the simulation, the break-event points were calculated for different ΔTs. The results obtained in this study show that TE technology is the most important alternative in converting waste heat to electrical energy in industrial systems. The designed system produces 150 W power at 100 °C temperature difference. The payback time of the system is calculated as 6 years. The hot surface temperatures of the modules used are maximum 200 °C. Therefore, heat insulation material is placed between the heat source and the modules. It is possible to increase the temperature difference by designing TEG with modules used at higher temperatures. In TEG systems, power increases in proportion to the square of the temperature difference. In this application, when the temperature difference is increased 2 times, the payback time decreases up to 2 years. Considering factors such as low installation costs of TE systems and low maintenance costs, TEG's is highly feasible in terms of waste heat recovery and energy efficiency.
Table 6 Change in TEG costs depending on temperature difference. ΔT
P800 kW
f1 USD/ kWh
f2 USD/ kWh
f3 USD/ kWh
f4 USD/ kWh
f5 USD/ kWh
f25 USD/ kWh
10 20 30 40 50 60 70 80 90 100 110 120 130 140 150 160 170 180 190 200 210 220 230 240 250 260 270 280
0.1 0.2 0.6 1.0 1.5 2.2 3.0 3.9 5.0 6.2 7.5 8.9 10.4 12.1 13.9 15.8 17.8 20.0 22.2 24.6 27.2 29.8 32.6 35.5 38.5 41.6 44.9 48.3
92.66 23.16 10.30 5.79 3.71 2.57 1.89 1.45 1.14 0.93 0.77 0.64 0.55 0.47 0.41 0.36 0.32 0.29 0.26 0.23 0.21 0.19 0.18 0.16 0.15 0.14 0.13 0.12
46.33 11.58 5.15 2.90 1.85 1.29 0.95 0.72 0.57 0.46 0.38 0.32 0.27 0.24 0.21 0.18 0.16 0.14 0.13 0.12 0.11 0.10 0.09 0.08 0.07 0.07 0.06 0.06
30.89 7.72 3.43 1.93 1.24 0.86 0.63 0.48 0.38 0.31 0.26 0.21 0.18 0.16 0.14 0.12 0.11 0.10 0.09 0.08 0.07 0.06 0.06 0.05 0.05 0.05 0.04 0.04
23.16 5.79 2.57 1.45 0.93 0.64 0.47 0.36 0.29 0.23 0.19 0.16 0.14 0.12 0.10 0.09 0.08 0.07 0.06 0.06 0.05 0.05 0.04 0.04 0.04 0.03 0.03 0.03
18.53 4.63 2.06 1.16 0.74 0.51 0.38 0.29 0.23 0.19 0.15 0.13 0.11 0.09 0.08 0.07 0.06 0.06 0.05 0.05 0.04 0.04 0.04 0.03 0.03 0.03 0.03 0.02
3.71 0.93 0.41 0.23 0.15 0.10 0.08 0.06 0.05 0.04 0.03 0.03 0.02 0.02 0.02 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.00
CRediT authorship contribution statement Gunay Omer: . : Writing - review & editing. Abdullah Hakan Yavuz: . : Investigation, Software. Rasit Ahiska: Conceptualization, Methodology. Kagan Ekrem Calisal: Resources, Funding acquisition. Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Acknowledgements This research is sponsored by Petkim Petrochemical Holding. References [1] Emeksiz C, Demirci B. The determination of offshore wind energy potential of Turkey by using novelty hybrid site selection method. Sustainable Energy Technol Assess 2019;36:1–21. https://doi.org/10.1016/j.seta.2019.100562. [2] Emeksiz C, Cetin T. In case study: investigation of tower shadow disturbance and wind shear variations effects on energy production, wind speed and power characteristics. Sustainable Energy Technol Assess 2019;35:148–59. https://doi.org/10. 1016/j.seta.2019.07.004. [3] Wolley E, Luo Y, Simeone A. Industrial waste heat recovery: a systematic approach. Sustainable Energy Technol Assess 2018;29:50–9. [4] Tongcai W, Weiling L, Tongjun L, Shan-Tung T, Jinyue Y. Performance enhancement of thermoelectric waste heat recovery system by using metal foam inserts. Energy Convers Manage 2016;124:13–9. https://doi.org/10.1016/j.enconman. 2016.07.006. [5] Aranguren P, Araiz M, Astrain D, Martínez A. Thermoelectric generators for waste heat harvesting: a computational and experimental approach. Energy Convers Manage 2017;148:680–91. https://doi.org/10.1016/j.enconman.2017.06.040. [6] Dongxu J, Zhongbao W, Stefano M, Marco M, Srithar R, Jiyun Z, et al. Thermoelectric generation for waste heat recovery: application of a system level design optimization approach via Taguchi method. Energy Convers Manage 2018;172:507–16. https://doi.org/10.1016/j.enconman.2018.06.016. [7] Gunay O, Abdullah HY, Rasit A. Heat pipes thermoelectric solar collectors for energy applications. Int J Hydrogen Energy 2017;42:8310–3. https://doi.org/10. 1016/j.ijhydene.2017.01.132. [8] Kirill AA, Andrea B, Aldo B, Techno-economic analysis of combined inverted Brayton – organic Rankine cycle for high-temperature waste heat recovery. Energy Convers Manage: X Available online 6 July 2019, 100014 in press. doi: 10.1016/j. ecmx.2019.100014. [9] Moh'd AA, Ahmed AA. Internal combustion engine waste heat recovery by a thermoelectric generator inserted at combustion chamber walls. Int J Energy Res
Fig. 11. Power generation capacity of the grid-tied TEG depending on temperature difference.
table are analyzed in terms of the company’s benefit. This analysis must be based on the incentive amount provided by the Turkish EMRA, which is $0.133 per kWh, and the warranty period of the TE modules, which is 5 years. The power generation capacity of a TEG is directly proportional to the square of the temperature difference between the surfaces of the thermoelectric module. An accurate cost analysis of a thermoelectric generator is only possible after a survey on the heat resource. Therefore, similar to other renewable energy resources, a survey must be conducted for each waste heat resource and the thermoelectric system utilizing this resource as in the company in question. A scientifically accurate examination and interpretation of the table given above clearly show how important the thermoelectric technology is and that this technology is one of the most significant technologies of the 21st century and beyond, and explain why scientific studies and billions of dollars of investments increasingly continue in this field around the world. In this study, MATLAB simulation is used to simulate the 8
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