Thermodynamic analysis and multi-criteria optimization of a waste-to-energy plant integrated with thermoelectric generator

Energy Conversion and Management 205 (2020) 112207

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Thermodynamic analysis and multi-criteria optimization of a waste-toenergy plant integrated with thermoelectric generator

T

Ehsan Houshfar School of Mechanical Engineering, College of Engineering, University of Tehran, P.O. Box 11155-4563, Tehran, Iran

ARTICLE INFO

ABSTRACT

Keywords: Waste-to-energy Thermoelectric generator Gasification TEG Multi-criteria optimization

A new integrated energy plant is suggested and studied in the current research, aiming at enhancing the exergetic efficiency and minimizing the total product cost of a waste-to-energy (WTE) plant. For the integration, the condenser of the WTE plant is substituted with a thermoelectric generator. Accordingly, the conventional and integrated energy systems are studied comprehensively from energy, exergy, exergoeconomic, and environmental viewpoints and compared together. The parametric study indicated that the proposed system has important advantages over the conventional WTE plant, demonstrating higher exergy efficiency, higher power output, lower total product cost, and lower CO2 emission. In addition, the suggested integrated model is optimized using a multi-criteria optimization (MCO) approach with a specific MATLAB program. The MCO analysis for the best operating point reveals an exergetic efficiency of 17.22% and total cost rate of 184.2 $/h. Furthermore, investigating the scatter distribution of the effective parameters demonstrates that the TEG inlet pressure and figure of merit are the most sensitive parameters and should be kept at their lowest value. It can be concluded that the proposed integration would improve the performance of WTE plants while reducing the total product cost and levelized CO2 emissions.

1. Introduction Recently, scientists have focused on more efficacious power production units due to increased demand and also concerns correlated to global warming. In this regard, investigators are on the brink of making major advances in utilizing energy resources more efficiently. Energy and exergy efficiency as the potential tools are usually considered to evaluate the performance of the energy systems. However, thermodynamic losses for a system cannot be assessed by energy efficiency while exergy efficiency shows how an energy system operates compared to a perfect one taking the 2nd law of thermodynamics into account. Moreover, exergoeconomic evaluation can help us examine the economic aspects of an energy system considering product cost, cost rate, or exergoeconomic factor. These parameters reveal the performance of a component from the thermoeconomic viewpoint. The exergoeconomic factor helps evaluation of the performance of a component considering the relative significance of non-exergy related costs and cost of exergy destruction and exergy loss. An energy system may be optimized by several tactics, e.g., recovering the waste heat, increasing the exergy efficiency, and reducing total cost rate of the system. Integrating the energy systems is one of the important techniques that can simultaneously increase exergy efficiency, reduce total cost rate, and mitigate environmental

contamination. Environmental impact of the energy systems is also an important parameter which shows the levelized emission (CO2 or other harmful exhaust gases) of a system. Subsequently, designing an efficient and affordable power plant would be among the most important topics of energy system researches. 1.1. Gasification technology The energy content of solid waste or biomass is conventionally converted through combustion, gasification, and pyrolysis technologies [1]. Many researchers tried to investigate, design, and optimize gasification-based systems. Multi-criteria optimization is applied to the biomass gasification-based plants to not only increase the exergy efficiency of the system, but also reduce its total cost rate. Ibrahim et al. [1] showed that exergy efficiency is a crucial objective function which clearly reveals the performance of a system. Habibollahzade et al. [2] examined the thermodynamic performance of a combination of the gasification-based waste-to-energy plant with solar chimney, and in a later investigation optimized the SCPP-WTE proposed plant from exergy, energy, and economic points of view [3]. They reported that the integrated system would increment the output of solar chimney by 20–1200% and the increase in the exergetic efficiency of the proposed framework is 0.15% throughout dark hours, i.e. night-time. Zhang et al.

E-mail address: [email protected]. https://doi.org/10.1016/j.enconman.2019.112207 Received 19 July 2019; Received in revised form 16 October 2019; Accepted 17 October 2019 0196-8904/ © 2019 Elsevier Ltd. All rights reserved.

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Nomenclature c C E ƒ h HHV ir κ LHV M m MC n1, n2,… P Q R s ΔTPP ΔTsup Tg w W Z Z zH zC zO ZTm

c CC Ch CI CO CRF D f G h i L lm m MCO MSW o OM P Ph Pm ST SG TEG tot wt

Cost per unit exergy ($/GJ) Cost rate ($/hr) Exergy rate (kW) Exergoeconomic factor Specific enthalpy (kJ/kg) Higher heating value (kJ/kg) Interest rate Thermal conductivity Lower heating value (kJ/kg) Molar mass (kg/kmol) Mass flowrate (kg/s) Moisture content (%) the mole number of components in reactions Pressure (kPa) Heating load (kW) Resistance Specific entropy (kJ/kg⋅K) Pinch point temperature difference (°C) Difference between TIT (turbine inlet temperature) and saturated TIT (°C) Gasification temperature (°C) kmole of moisture per kmol of MSW Power (kW) Investment cost of components ($) Investment cost rate of component ($/hr) Weigh fraction of hydrogen Weigh fraction of carbon Weigh fraction of oxygen Figure of merit

Cold side of steam generator/TEG Combustion chamber Chemical Capital investment Condenser Capital recovery factor Destruction fuel Gasifier Hot side of steam generator/TEG inlet Loss Log mean temperature difference mean Multi-criteria optimization Municipal solid waste outlet Operation and maintenance Product Physical Pump Steam turbine Steam generator Thermoelectric generator total weight

Greek symbols II

is

i

Subscript and abbreviations

τ ε

1, 2, 3,… State points [4] examined the influence of important factors on gasification technology based on energy and exergoeconomic viewpoints. It was reported that the energy efficiency of the studied reactor would be 44.25% at a carbon conversion ratio of 0.7. Wu et al. [5] analysed the performance of a medium-size gasification plant (1.2 MW) in Zhejiang province, China. The main effective parameters, e.g., moisture content and equivalence ratio are assessed on the performance of the system. In a later study, Soltani et al. [6] performed a comparative analysis of two biomass-based power generation units from thermodynamic standpoints. They showed that the integrated system (with co-firing) might have higher efficiency compared to the combined arrangements with external firing. Al-Sulaiman et al. [7] investigated a biomass-based trigeneration structure using the ORC concept where they reported that the gasifier destructs the major part of exergy. Their study further indicates that the exergy efficiency declines by incrementing the pinch point temperature. Datta et al. [8] assessed the effect of various parameters (TIT-turbine inlet temperature and PR-pressure ratio) on thermal performance of a gas turbine (external firing), when the system is coupled with a biomass gasifier. It is reported that a specific PR should be set in order to reach the highest thermal efficiency, while higher TIT has a direct effect on increasing efficiency. Another seminal study, the energy/exergy efficiencies and the influence of key effective factors on an integrated biomass-based gasification cycle were examined [9], reporting that combustion chamber has the maximum exergetic efficiency and the temperature ratio would increment the thermal efficiency. Khalid et al. [10] assessed the influence of temperature of the combustion chamber and inlet pressure of the turbine on integrated energy systems which are using combined form of solar and

Exergy efficiency Isentropic efficiency Exergy efficiency of ith component Annual plant operation hours (hr) Emission indicator (t/MWh)

biomass-based energies. They reported that if the original combustion temperature (700 °C) is raided by 200 °C, the total energy efficiency and exergetic efficiency augmented by 3% and 14%, respectively. A subsequent investigation examined the thermal performance of a 1 MW gasification combined power generation unit, consisting of a gas turbine and Rankine cycle [11]. The outcomes indicated that the lowest destruction of exergy occurs in the pump and the minimum and maximum exergy efficiency corresponds to ‘gasifier and combustion chamber’ and ‘gas turbine and compressor’, respectively. Rosen and Dinçer [12] assessed the correlation of exergy and environmental characteristics of various thermodynamic systems, reporting that higher level of exergy destruction is equivalent to more environmental concerns. Ahmadi and Dinçer [13] implemented MCO method based on a GA (genetic algorithm) technique to find the optimum cost rate and exergy efficiency for a real energy generation unit in Iran. The results showed that in the best solution point, the exergy efficiency is 33.56% and the environmental impact may decrease by about 50.50%. Recently, a number of authors have considered the effects of combining gasification technology with fuel cell [14,15]. 1.2. Thermoelectric generator Thermoelectric generators (TEGs) are among the emerging thermal technologies because of their various advantages and applications, e.g., the potential to directly convert thermal energy to electricity, CO2-free performance, having no chemical reactions, silent operation, and low operating and maintenance cost. Thermodynamic analysis and design/optimization of various types 2

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of thermoelectric generators are investigated by different researchers [16–18]. In addition, integrating TEGs with traditional power generation units are proposed and examined in the literature form energy and exergy viewpoints, in recent studies. Chávez-Urbiola et al. [19] assessed the integration of a TEG-solar system which was designed to operate at 50–200 °C. This study revealed that the TEG efficiency would reach 4% at a presumed working condition. A key study in performance analysis of combined TEG-PV systems is the work by Lin et al. [20] which was performed in 2015. In another study, integration of concentrated photovoltaic cells and TEG is assessed thermodynamically, where the optimum operating conditions for maximum power output and efficiency

are reported [21]. Zare and Palideh [22] suggested a TEG-Kalina integrated system to increase the power production and reported that the net cycle output would increment by 7.3% in the integrated system in comparison with the standalone Kalina cycle. Ziapour et al. [23] suggested the TEG-ORC (organic Rankine cycle) combined cycle to increase the power production using two models. In model one, condenser of the ORC system is replaced with the TEG cycle, while for model 2, the TEG is combined with the ORC cycle establishing a transitional heat exchanger. Their outcomes revealed that the thermal efficiency of the integrated plant based on model 1 and 2 can increase by 0.21% and 0.2%, respectively. Integration of gasifier-TEG is quite

Fig. 1. The proposed integrated models: a) Conventional WTE plant b) WTE-TEG integrated system. 3

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recently proposed for increasing efficiency of biomass power generation units [24]. The optimum economic conditions and maximum increase of the efficiency are determined. Maraver and Royo [25] used a relatively simpler concept as a biomass-based ORC-TEG integrated system. They achieved up to 8% raise for the exergetic efficiency using the integrated approach. To the extent of our knowledge, there exists no all-inclusive investigation on energy, exergy, exergoeconomic, environmental impacts, and MCO of a combined TEG-WTE plant. Therefore, this can be the first investigation to attempt extensive research on combined WTE-TEG systems from thermodynamic perspectives. The objective of the current research is, thereby, to enhance the exergy efficiency, increase the power output, and reduce both total product cost and emission indicator of the WTE plants. Accordingly, a new model is proposed by implementing TEG as the condenser of the system. Exergy efficiency as an important performance indicator, levelized CO2 emission as an environmental impact indicant, and total cost rate/total product cost and exergoeconomic factor as the potential exergoeconomic parameters are considered for the evaluation of the systems. Accordingly, energy, exergy, exergoeconomic, and environmental impact analysis and parametric study of the suggested model are conducted and compared with the conventional WTE plant. Ultimately, the MCO method is implemented to optimize the integrated system. Therefore, the key purposes and originalities of this study could be abridged as:

flowing via the turbine, enters the condenser/TEG (state 4). Water and air, acting as cooling media, cool down the steam (states 12, 13, 14 and 15) and thereby sub-cooled water enters the pump. The water is then pumped again to the boiler section. The following presumptions are made to make the analyses simplified [22]:

• Steady-state condition is applied to render the analysis. • Variations of potential and kinetic energy are neglected. • Pressure loss inside the pipelines and piping system is negligible. • Pump and turbine are assumed to be adiabatic equipment as the heat loss from these components is negligible. • Pressure drop through the steam generator, condenser, and the combustion chamber is 5%. • Because of the high temperature inside the gasifier and combustion •

3. Modelling A complete thermodynamic analysis of the models is performed and compared together via the parametric investigation. The corresponding equations are solved by implementing the Engineering Equation Solver (EES) package. For conducting comprehensive thermodynamic analyses, each ingredient is assumed to be a distinct control volume, in which the 1st and 2nd laws of thermodynamics should be satisfied. Additionally, the exergoeconomic analysis is performed using specific exergy costing (SPECO) method.

• Integration of two energy generation cycles is proposed by estab• • •

chamber, syngas, air, and combustion products are supposed to be treated as ideal gases. The composition of air considered as 21% O2 and 79% N2 and other elements e.g. CO2 and Ar are ignored.

lishing TEG in place of the condenser to enhance the exergy efficiency, increase the power output, reduce total product cost, and mitigate environmental pollution. Performance of the new proposed system is studied from thermodynamic-environmental perspectives and compared to the conventional WTE plant. An MCO technique is applied to the suggested system to ascertain the optimum working conditions from exergy/exergoeconomic viewpoints together with the best evenly-adjusted point from exergy/economic aspects. Optimal results are congregated as a Pareto frontier and the scatter distribution diagrams are plotted and examined for the major operational factors.

3.1. Energy and exergy analysis The basic equations for energy conservation and exergy balance of each equipment in the model may be written as follows [26]:

QC . V

WC . V =

ED =

Ein

mout hout

Eout

min hin

(1) (2)

E includes physical and chemical exergy and E = me where e is the total specific exergy. Physical exergy for the whole system is then obtained by [27]:

2. Cycle description and assumptions Representative diagrams of the suggested energy generation arrangements are demonstrated in Fig. 1. Model (a) is considered as a conventional WTE plant (Tehran’s WTE plant) and Model (b) is the newly suggested system in which a TEG is used instead of the condenser. As the figure shows, the WTE power generation unit involves two major fragments: the gasification system and the conventional Rankine cycle. Municipal solid waste (MSW) is first dropped off into the solid fuel chamber, from where the operator feeds a certain amount of MSW into the gasification chamber through a rake (state 5). The first portion of the oxidizing agent (primary air) then flows into the gasification chamber and is mixed with the fuel (state 6). At the end of the gasifier, the produced syngas passes through a transfer channel and enters the combustion chamber (states 8a and 8) where the secondary air is injected (state 9). Acid scrubber separates hazardous acids from the combustion products (state 10a). Flue gases, after passing through the acid scrubber, enter the steam generator to heat the water of the Rankine cycle (state 10). Eventually, flue gases leave the cycle from the chimney (states 11a and 11). In the heat engine part with steam as the working fluid, firstly the fluid enters the pump (state 1). The water is then directed toward the boiler by means of the pump (state 2). The steam generator (boiler) increases the water temperature and generates steam. The superheated steam is then passed over the steam turbine (state 3). Steam, after

e¯ ph = h

h0

T0 (s

s0)

(3)

Finally, the chemical exergy and total exergy can be calculated by [28]: j

e¯ch =

¯ 0 yi e¯ich + RT

i=1

e=

e¯ ph

+

n

yi ln (yi ) i=1

e¯ch

(4) (5)

3.1.1. Gasifier and combustion chamber To accomplish a complete survey of energy and exergy terms for the gasification chamber and the combustion zone, initially, the chemical reactions which take place in these two components should be considered [29,30]. Following a proximate analysis approach, the moisture content of solid waste—mass fraction—is expressed by [31]:

MC =

m water × 100 mMSW

(6)

So, for the standard reaction, each mole of MSW will be accompanied with w mole water:

w=

4

MMSW . MC 18(1 MC )

(7)

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The global reaction which occurs in the gasifier is [32]:

CHa Ob Nc + wH2 O + n1 (O2 + 3.76N2 ) + Ash

3.2. Exergoeconomic evaluation

n2

Implementing a TEG unit as a replacement for the condenser, obviously increases the exergetic efficiency and net power output but what will happen to the total product cost of the whole plant is not easily predictable. The total product cost is among the key effective factors (as an economic indicant) of an energy generation plant and must be considered during the design of the system. In this regard, for a more reasonable comparison of the systems, exergoeconomic evaluation is subsequently performed. The cost balance equations for the kth item are [35]:

H2 + n3 CO + n4 CO2 + n5 H2 O + n6 (8)

CH4 + n 7 N2 + Ash

In the combustion chamber, after syngas reaction with the air coming in as the secondary oxidizer agent, a complete oxidation reaction is presumed as [11]:

n2 H2 + n3 CO + n4 CO2 + n5 H2 O + n6 CH4 + n7 N2 + n (O2 + 3.76N2 ) n8 CO2 + n 9 H2 O + n10 O2 + (n7 + 3.76nair ,1 ) N2

(9)

Cout , k + CW , k =

in which n′ is the mole numbers of the secondary air. Following Eq. (1), the energy conservation could be practiced for the gasification and combustion chamber. For determining the coefficients a, b, and c in Eq. (8), the moisture-free ultimate analysis of MSW in Tehran, i.e., C: 40.5 wt%, H: 3.5 wt%, O: 40.2 wt%, N: 0.8 wt%, ash: 15 wt%, and gross calorific value of 8955 kJ/kg are considered. Coefficients of the combustion products in Eq. (9) are subsequently ascertained using the conservation of mass and implementing the available data for the chemical equilibrium of the reaction. The effect of bottom ash is considered for calculating LHV of the input MSW, though the fly ash is omitted.

CI

TEG

=

TEG

=

Carnot

1 + ZTm +

=1

Tc Th

QELEGANT = m12 (h13

ZTm =

2T m

R

h14 )

=

1 (Tc + Th ) 2 V T

(20)

Cq = cq Eq

(21)

CRF =

(22)

CRF

Zk

(23)

ir (1 + ir ) n (1 + ir ) n 1

(24)

Afterwards, Zk for the present year (2019) can be calculated [38]:

Cost at present year = original cost ×

Cost index of the present year Cost index of the base year (25)

Table A.2 in Appendix presents the equations for the calculation of relevant costs (Zk) for every equipment within the model [27,28,39]. The cost balance and auxiliary equations are analysed for every single part of the system (see Table A.3, Appendix) and thereby, the cost of unknown streams is ascertained. cF , k (the unit cost of fuel), cP, k (the unit cost of product), CD, k (the cost rate of destructed exergy), and fk (the exergoeconomic factor) are the most important parameters for evaluating economic aspects of the system [40]:

(13) (14)

where κ and R refer to the thermal conductivity and resistance of the TEG system. Tm and ψ are expressed as:

Tm =

Cout = cout Eout

where τ refers to the annual plant operation hours (8000 h in the current study) and CRF denotes capital recovery factor [37]:

(12)

h12) + m14 (h15

(19)

CI

where Tc and Th refer to the temperature of the TEG system in its cold and hot side, QELEGANT denotes efficient liquid-based power production component within the TEG and ZTm refers to the figure of merit, a key factor which indicates internal conversion efficiency of the TEG unit. Carnot ,QELEGANT , and ZTm can be expressed as follow [19,34]: Carnot

C = cE

Zk =

(11)

QELEGANT

(18)

in which refers to the operating and maintenance costs. Furthermore, the levelized annual cost of the kth item may be obtained from [36]:

(10)

WTEG

OM

Zk = Zk + Zk

OM Zk

1 Tc Th

(17)

CW = cW W

3.1.2. TEG and Rankine cycle The relevant equations for calculating the TEG power generation potential is expressed as [19,33]:

1 + ZTm

Cin, k + Cq, k + Zk

(15) (16)

cF . k =

CF . k EF . k

(26)

cP . k =

CP . k EP . k

(27) (28)

CD . k = cF . k ED . k

Average of temperatures at states 1 and 4 are assigned to the TEG’s hot side, and for the cold side, the average temperature of states 12–15 is taken. To enhance the lifetime and durability of the TEGs, the mass flowrates of the cooling fluids should be higher than the mass flow rate of the heating fluid. The mass flowrates of the cooling fluids for the Tehran’s WTE plant is 3.875 kg/s for cooling water and 208.2 kg/s for the cooling air. Corresponding mass flowrate for the heating side is 2.3 kg/s at the base case. Accordingly, the TEG unit can operate with reliable durability and long lifetime in the WTE plant. Eventually, exergy balance and exergy efficiency equations for the Rankine cycle components and TEG unit are listed in Table A.1 in the Appendix.

fk =

Zk Zk + CD . k +CL . k

(29)

3.3. Performance examination Performance and financial indicators—exergetic efficiency, total cost rate, and total product cost of the systems—are defined as follows: II , a

5

=

WST

WPm ch

ch ch eMSW + w × e water + 4.76 × (n1 + n') × eair

(30)

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performance should be preserved, but also the cost associated with the long-term operation of the system has to be considered. In this regard, an MCO based on genetic algorithm (GA) is a lucrative and attainable option to discover the optimum design point and determine the relevant set points for the key constraints. Hence, in the present research, by means of an in-house MATLAB program, an MCO approach built upon the evolutionary algorithm is utilized. Accordingly, maximizing the total exergy efficiency (Eqs. (30)–(31)) and minimizing total system cost rate (Eq. (32)) are considered as conflicting objectives.

Table 1 The syngas composition in this study compared to experimental and numerical reported data. Syngas composition

Present study

Measured by Jayah et al. [42]

Jarungthammachote equilibrium model [43]

H2 CO CH4 CO2 N2

17.34 19.49 0.63 10.97 51.57

17 18.4 1.3 10.6 52.7

18.04 17.86 0.11 11.84 52.15

WST

WPm + WTEG

II , b

=

4. Results and discussion

ch ch eMSW + w × ewater + 4.76 × (n1 + n') ×

Ctot =

cP, tot =

nk i=1

Zk +

nF i=1

ch eair

(31)

CFi

(32)

Ctot k E i = 1 Pi

(33)

where subscripts a and b refer to model (a) and model (b), and defined as [41]: z

ch eMSW = LHVMSW

A parametric study is accomplished to assess and compare the effect of key constraints on the efficiency of the system. Effect of the crucial parameters on net power output, total cost rate, total product cost, amount of CO2 emission and exergy efficiency are examined. Eventually, MCO is applied to the new proposed model and scatter distributions of the key affecting factors are reported.

1.044 + 0.016 zH C

1

z

ch eMSW

is

4.1. Verification and validation

z

0.3493 zO (1 + 0.0531 zH ) C

z 0.4124 zO C

The composition of syngas obtained in the present study is compared to the measured data by Jayah et al. [42] and the numerical data reported by Jarungthammachote and Dutta [43] as shown in Table 1. Wood is considered as the feedstock at T = 1100 K and MC = 16 wt%. Furthermore, to ensure the outcomes of the TEG modelling, the analogy of TEG efficiency and power output of the current study is examined against the results of a recent study [23] as illustrated in Fig. 2.

C

(34)

where z C , zH , and z O are the wt% of carbon, hydrogen, and oxygen in the fuel, respectively. Eqs. (30), (31) and (34) are used to calculate the exergy efficiency of the systems and Eq. (32) is implemented to determine the total cost rate of the systems. Sum of total cost rate of the components and the cost rate of the fuels (biomass cost rate is the only fuel cost rate in this study) is considered for this purpose. Accordingly, total product cost of the plant (Eq. (33)) is calculated by dividing total cost rate of the system to exergy of the product of the system (in this study total power output is the exergy of product). The product cost is one of the important parameters which is extensively considered for the comparison of the energy systems from the exergoeconomic viewpoint.

4.2. Parametric study Impacts of the key influencing parameters on the performance of the plant, and environmental-economic indices are examined in this section. Real data of the WTE plant in Tehran is considered for simulation purpose as listed in Table 2. The temperature difference for the cooling water in the condenser/ TEG cannot be effective on the model (a) but as depicted in Fig. 3, the parameter would actively be influencing system performance and economic aspects of the model (b). When the temperature difference is enlarged, the cold side temperature of the TEG system increases which, therefore, causes reduction of the net power output, TEG efficiency, and total exergy efficiency. In addition, by raising the parameter in the reasonable range, total product cost slightly rises while the total cost rate decreases. Similar to the influence of the previously mentioned parameter, cooling air temperature difference in the condenser/TEG affects only the efficiency and exergoeconomic index of the model (b). As Fig. 4

3.4. Environmental assessment The total quantity of carbon dioxide discharged out of the chimney is taken as an indicator for evaluating the environmental performance of the suggested system. For this purpose, Eqs. (35) and (36) are applied to model (a) and (b), correspondingly, as emission indicants: a

=

b

=

mCO2, emitted WST

WPm mCO2, emitted

WST

WPm + WTEG

(35) (36)

In these equations, to determine the levelized emission of the systems, the CO2 emissions out of the stack (state 11) is calculated and divided into the plant’s net power output. 3.5. Multi-criteria optimization (MCO) A general controversy at the design and operation stage of thermal energy plants is accosting with numerous contradictory purposes that ought to be unravelled concurrently. Typically, constructing a system with higher performance requires more budget compared to a plant with lower efficiency. In contrast with single objective optimization technique, in the MCO method, a bunch of optimum solution points––videlicet Pareto frontier––is acquired. The primary purpose of the MCO is to determine an ideal point, which balances the exergetic efficiency and the cost rate. Ascertaining such point can be rather arduous since there could be numerous effective design parameters. Consequently, to find the target point, not only a reasonable

Fig. 2. Verification of modelling of the TEG unit. 6

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parameter that can be altered over time in the plant. By increasing the feeding rate, the exergy efficiencies remain constant, but the total product costs decrease. On the other hand, power output and total cost rate are expected to rise, as can be seen on the right-hand side of the graph. As illustrated in Fig. 9, the moisture content of MSW could also be effective on the system performance. By increasing the moisture content, a clear decreasing trend could be observed for the power outputs, total cost rates, and exergy efficiency, while the total product costs increase. This is justified because the higher value of moisture content means lower LHV of MSW and thereby less turbine power output. Effect of turbine inlet pressure is demonstrated in Fig. 10. From the graph, increasing the pressure leads to a clear increase in the enthalpy of steam and exergy efficiencies, power outputs, and total cost rate, as expected. Additionally, the total product cost reduces by raising the pressure. Effect of the TEG inlet pressure, which is an essential design parameter, on the system performance is illustrated in Fig. 11. At higher pressures, enthalpy of the fluid entering the TEG system and power output of the TEG part increase but net power output decreases since the output power of the turbine declines dramatically. Accordingly, exergy efficiencies, net power outputs, and total cost rates of the model are expected to decrease. On the other hand, total product costs increase by raising the turbine inlet pressure. The figure of merit, which reflects the level of TEG performance, is also a crucial design constraint. Fig. 12 demonstrates that when the figure of merit is augmented, the power output of TEG rises correspondingly which leads to a distinct enhancement in the exergy efficiency of the model (b). Moreover, total cost rate of the system (b) increases (because ZTEG increases) and therefore the total product cost of the model decreases. The parameter is not effective in the model (a) since there is no TEG unit in the model and the performance and economic indices for the model (a) are presented only for comparison purpose. Last but not least effective parameter is the combustion temperature. As shown in Fig. 13, by increasing the combustion temperature, which results in a greater available enthalpy for the steam generator, the exergetic efficiency, net power outputs, and total cost rates increase while the total product cost drops.

Table 2 Real cycle data of Tehran’s WTE plant as the input of the simulation purpose. Parameter

Description

Value

T0 (°C) P0 (kPa) ɳis,Pm (%) ɳis,ST (%) T8 (°C) T10 (°C) T7 (°C) P3 (kPa) P4 (kPa) ΔTsup (°C) ΔTPP (°C)

Ambient temperature Ambient pressure Isentropic efficiency: pump Isentropic efficiency: steam turbine Temperature: gasifier Temperature: Combustor Bottom ash temperature Turbine inlet pressure Condensation pressure Superheater temperature difference Temperature difference at the pinch point: boiler (steam generator) Cooling air temperature difference in the condenser/TEG Cooling water temperature difference in the condenser/ TEG Cooling water mass flowrate MSW feeding rate Figure of merit

298 101.3 85 80 950 1100 400 2100 39 198 222.5

T15-T14 (°C) T13-T12 (°C)

m 12 (kg/s) m 5 (ton/day) ZTm

25 10 3.875 100 0.8

depicts, similar trends would be expected by increasing the parameter. The cold end temperature difference is another effective parameter, which can be effective on both proposed models. As shown in Fig. 5, when this parameter is augmented, the exergetic performance and power generation increases in the model (b) while model (a) does not show any sensitivity. The behaviour may be clarified by the fact that rising the temperature difference increments the temperature at the hot side of the TEG system; thus, the TEG efficiency increases and, afterward, the total exergetic efficiency and net power raise in model (b). Additionally, by raising the temperature difference from 5 °C to 35 °C, total product cost of both models decreases while total cost rate of model (a) declines and that of model (b) rises. Another effective parameter is the temperature difference at the pinch point of the steam generator. Effect of this factor on the operating indicators is presented in Fig. 6. From the figure, it can be seen that augmenting the parameter dramatically decreases the efficiency, total cost rate, and power output of both models while total product costs of the systems are expected to increase. The superheater temperature difference can also be effective as represented in Fig. 7. The graphs show that by increasing the parameter from 150 °C to 250 °C, power outputs, exergy efficiency, and total cost rates of the models increase and the rate of increment in the model (b) is even faster in the given range. The increment of power and exergy efficiency may be explained by the fact that raising the superheater temperature increases the temperature of the fluid that gets into the turbine and the TEG. In addition, the total product costs are reduced by raising ΔTsup. Fig. 8 displays the influence of MSW feeding rate on the system performance. The feeding rate of MSW is one more important

4.3. Environmental assessment To assess the environmental impact of the projected integrated systems, emission indicators of the model are compared together through the parametric study. As Fig. 14 illustrates, model (b) has lower emission and is a more environmentally benign system. The outcomes of the current parametric study and environmental assessment disclose that integrating the TEG unit with the WTE plant is a promising way of enhancing the power production level, increasing the exergetic efficiency, and reducing total product cost and

Fig. 3. Effect of the temperature difference of the cooling water in the condenser/TEG on the system performance. 7

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Fig. 4. Effect of the cooling air temperature difference in the condenser/TEG on the system performance.

Fig. 5. Influence of the cold end temperature difference on the system performance.

Fig. 6. Influence of the pinch point of the steam generator on the performance of the systems.

Fig. 7. Effect of the superheater temperature difference on the system performance.

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Fig. 8. Effect of throughput of the MSW on the system performance.

Fig. 9. Influence of the MSW moisture content on the system performance.

Fig. 10. Impact of the turbine inlet pressure on the system performance.

Fig. 11. Influence of TEG inlet pressure on the performance of the system.

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Fig. 12. Effect of the figure of merit on the system's performance.

Fig. 13. Influence of combustion temperature on the performance of the systems.

Fig. 14. Effect of the key influencing parameters on emission indicator.

environmental contaminations. Then again, despite the TEG increases the total cost rate of the system, it has the potential to decrease the total product cost because selling the generated electricity of the TEG overcomes the increased cost rate of the plant. Total product cost is a more important parameter since a proper comparison can be performed considering this parameter. In fact, the total product cost is a levelized economic indicator, which can be used for comparison of different energy systems, i.e., different scales.

Furthermore, results of the exergoeconomic analysis are provided in Table 4. Exergy of fuel, exergy of products, destructed exergy, exergoeconomic parameters like the cost of exergy destruction, the product and fuel costs, exergetic efficiency, and exergoeconomic factor for each element and for the whole system are listed in Table 4. A higher level of exergoeconomic factor indicates that a high purchase cost is associated with the component. Hence, the high amount of f for the pump and steam turbine shows that decreasing the capital cost would be cost-efficient at these parts. On the other hand, the lower exergoeconomic factors (such as combustion chamber) indicate a high value of Zk + CD , which is the result of more irreversibility.

4.4. Thermodynamic and exergoeconomic properties Thermodynamic properties of all stream points of the studied systems are presented in Table 3. 10

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Table 3 Thermodynamic and exergoeconomic parameters of each stream point. Stream

T (°C)

P (kPa)

m( )

E (kW )

c(

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

58.6 58.61 410.3 75.45 25 25 400 980 25 1100 230 25 35 25 50

37.34 2101 1996 39.3 101.3 101.3 101.3 101.3 101.3 95.95 91.15 101.3 101.3 101.3 101.3

2.312 2.312 2.312 2.312 1.155 2.167 0.115 3.207 3.189 6.396 6.396 3.875 3.875 208.2 208.2

16.92 21.04 2636 805.2 10,323 0 3.106 6797 0 5918 1269 0 2.659 0 201.05

9.28 20.67 9.28 9.28 2 0 0.1 3.839 0 4.419 4.419 0 2780 0 0

kg s

$ ) GJ

Table 5 Major effective parameters that are used in MCO and their reasonable ranges.

$ h

C( ) 0.5656 1.562 88.03 26.92 74.33 0 0.001118 93.93 0 94.16 20.19 0 26.63 0 0

Parameter

Range

ΔTPP (°C) P3 (kPa) P4 (kPa) T10 (°C) ZTm

150 < ΔTPP < 250 700 < P3 < 4000 30 < P4 < 80 1000 < T10 < 1400 0.2 < ZTm < 1.6

4.5. Multi-criteria optimization Five major effective parameters of the new proposed model are considered for the MCO analysis. These key factors and their rational limits are presented in Table 5. The main objective functions (total cost rate and exergetic efficiency) are depicted as a Pareto frontier in Fig. 15, following a procedure based on genetic algorithm. The graph reveals that the total cost rate of the combined system raises by the exergetic efficiency. Moving from point A to C, both the exergetic efficiency and total cost rate decrease. Actually, point A would be regarded as the optimum solution point when exergetic performance is the target parameter. Point C is, on the other hand, the optimal point with respect to the total cost rate. The ideal solution point of the studied system is determined from the graph, in a place where the highest possible exergetic efficiency and at the same time the likely lowest total cost rate could be attained. It is evidently unimaginable to reach such operating conditions; since, the used objective functions can under no circumstances reach their superlative levels concurrently. Hence, the closest point on the Pareto frontier line to the imaginary best point is chosen as the optimal solution because this point (point B) provides a balance between economic-performance factors. The important design parameters and their relevant values at points A, B, and C are listed in Table 6. Scatter distribution of the main influencing factors is illustrated in Fig. 16. The inference from the figure is that the range of optimal solution points for the effective parameters would be:

Fig. 15. Optimum solution points of the new proposed model (Pareto frontier).

parameters as low as possible would be a decent choice that helps the system to operate efficiently. 5. Conclusion In this research paper, a new WTE plant model (model (b)) is suggested where the condenser is substituted with a TEG to improve the power generation and increase the exergetic efficiency while at the same time reduce the total product cost. Thermoeconomic and environmental performance of the new system are studied and the results are presented in comparison with that of the conventional WTE plant (model (a)). Results of the parametric study reveal that the proposed system could be a favourable technique to improve the exergetic efficiency and mitigate environmental contaminations of the WTE plants. Eventually, the MCO scheme based on a genetic algorithm is applied to the model and optimal points are presented in a Pareto frontier.

150 < TPP (°C) < 250, 1000 < P3 (kPa) < 3800, 30 < P4 (kPa) < 50, 1000 < T10 (°C) < 1360 and 0.2 < Z Tm < 1.6. For TEG inlet pressure and figure of merit, majority of the plotted solution points are adjacent to their lowest value, so keeping these Table 4 Results of the exergoeconomic analysis. Component

EF (kW )

EP (kW )

ED (kW )

EL (kW )

Gasifier Combustion chamber Pump Steam turbine Steam generator Condenser TEG unit Stack Total: Model (a) Total: Model (b)

10,227 6797 4.123 1830 4650 788.3 788.3 – 10,227 10,227

6797 5918 4.123 1508 2615 207.3 285.6 – 1508 1589.9

3430 879 0 322 2035 581 502.7 – 8719 8637.1

0 0 0 0 0 0 0 1269 1269 1269

11

(%)

CD ( )

CL ( )

Z( )

$ h

f (%)

66.41 86.85 100 82.38 56.91 26.22 36.17 – 14.74 15.54

24.93 12.14 0 10.78 32.38 19.41 16.82 – 62.78 62.19

0 0 0 0 0 0 0 26.15 26.15 26.15

19.6 0.2278 0.65 67.41 12.51 0.2747 8.11 – 108.78 116.61

43.99 1.811 100 86.25 19.19 1.385 32.53 – 55.02 56.89

$ h

$ h

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Table 6 Values of the objective function at points A, B, and C. Point

ΔTPP (°C)

P3 (kPa)

P4 (kPa)

T10 (°C)

ZTm

ηII,tot (%)

Ctot ($/h)

A B C

153.7 235 248.2

3815 3767 1026

30.3 30.5 49.8

1362.5 1130 1005

1.39 0.22 0.21

22.3 17.22 10.84

216.9 184.3 163.2

Fig. 16. Scatter distribution of the influencing parameters.

12

(

t MWh

1.88 2.38 3.83

)

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Optimum solution points from exergy/exergoeconomic viewpoints are ascertained and the best solution point—balance between exergy and exergoeconomic factors—is found. The other central inferences of the current investigation can be abridged as:

•

• Results of the parametric study indicate that model (b) demonstrates • •

important advantages over the model (a), e.g., has higher exergetic efficiency, higher power output, lower total product cost, and lower CO2 emission. The energy, exergy, and exergoeconomic analyses disclose that the gasification chamber causes the most irreversibility through the systems. Results of the MCO reveal that, at the optimum plausible point, the

exergetic efficiency and total cost rate of the proposed system reach 17.22% and 184.3 $/h, correspondingly. The inference from the scatter distribution of the key influencing parameters is that the figure of merit and TEG inlet pressure are the utmost sensitive parameters which need to be set at their lowest level.

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.

Appendix A

Table A.1 Exergy balance equations for the equipment of the WTE section. Component

Exergy destruction rate

Gasifier

ED, G = E5 + E6

Combustion chamber

ED, CC = E8 + E9

Pump

ED, Pm = WPm

Steam turbine

ED, ST = (E3

Steam generator

ED, SG = E2 + E10

Condenser

ED, CO = E12 + E14 + E4

TEG unit

ED, TEG = WTEG + E12 + E14 + E4

E7

Exergy efficiency

E8

G

E10

(E2

E1)

E4 )

WST E3

E11 E1

E13

E15

E1

E13

E15

E8 E5 + E6

=

E7

CC

=

E10 E8 + E9

Pm

=

E2 E1 WPm

ST

=

WST E3 E4

SG

=

E3 E10

CO

=

TEG

=

E2 E11 E4 E1 E12) + (E15

(E13

(E4 (E13

E14 )

E1) + WTEG E12) + (E15 E14 )

Table A.2 Purchase cost expressions of the components of the proposed systems [27,28,39] Section

Zk ($)

Gasifier

ZG = c0 (mMSW ,daf )0.67c0 = 1600$/(kg /h )0.67

Combustion chamber

Zcc = c1 mair (1 + exp (c2 Tout

Pump

c3 ))

1 0.995

Pout c1 Pin

= 48.64$/(kg /s ) , c2 = 0.018K 1, c3 = 26.4

ZPm = c4 (WPm )0.71c4 = 3540$/(kW )0.71

Steam turbine

ZST = c5 (WST )0.7c5 = 6000$/(kW )0.7

Steam generator

ZSG = C6

Condenser TEG unit

Qec TLMTD, ec

0.8

+

Qev TLMTD, ev

0.8

+ C7 mwater + C8 (msyngas )1.2c6 = 6570$/(kW / K )0.8 , c 7 = 21276$/(kg / s) , c8 = 1184.4$/(kg /s )1.2

ZCO = c9 mwater c9 = 1773$/(kg / s)

ZTEG = c10 WTEG c10 = 1500$/ kW

Table A.3 Cost balance and auxiliary statements for all equipment. Section

Equations

Gasifier

C5 + C6 + ZG = C7 + C8

Combustion chamber Pump Steam Turbine Steam Generator Condenser TEG unit

C8 + C9 + ZC . C = C10 C1 + CW ,Pm + ZPm = C2 cW,Pm = cW,ST

C3 + ZST = C4 + CW , ST c3 = c4

C2 + C10 + ZSG = C11 + C3 c11 = c10

C4 + C12 + C14 + ZCO = C15 + C13 + C1c4 = c1

C4 + C12 + C14 + ZTEG = C15 + C13 + C1 + CW , TEG c4 = c1, cW,TEG = cW,ST

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