Next Article in Journal
Modeling the Circular Economy Processes at the EU Level Using an Evaluation Algorithm Based on Shannon Entropy
Next Article in Special Issue
Theoretical Methodology of a High-Flux Coal-Direct Chemical Looping Combustion System
Previous Article in Journal / Special Issue
Calculation Model and Rapid Estimation Method for Coal Seam Gas Content
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Energy Consumption and Economic Analyses of a Supercritical Water Oxidation System with Oxygen Recovery

1
Guangzhou Institutes of Advanced Technology, Chinese Academy of Sciences, Guangzhou 511458, China
2
Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
3
National Engineering Laboratory for Coal-fired Pollutants Emission Reduction, Shandong University, Jinan 250061, China
*
Author to whom correspondence should be addressed.
Processes 2018, 6(11), 224; https://doi.org/10.3390/pr6110224
Submission received: 15 October 2018 / Revised: 8 November 2018 / Accepted: 14 November 2018 / Published: 16 November 2018
(This article belongs to the Special Issue Gas Capture Processes)

Abstract

:
Oxygen consumption is one of the factors that contributes to the high treatment cost of a supercritical water oxidation (SCWO) system. In this work, we proposed an oxygen recovery (OR) process for an SCWO system based on the solubility difference between oxygen and CO2 in high-pressure water. A two-stage gas–liquid separation process was established using Aspen Plus software to obtain the optimized separation parameters. Accordingly, energy consumption and economic analyses were conducted for the SCWO process with and without OR. Electricity, depreciation, and oxygen costs contribute to the major cost of the SCWO system without OR, accounting for 46.18, 30.24, and 18.01 $·t−1, respectively. When OR was introduced, the total treatment cost decreased from 56.80 $·t−1 to 46.17 $·t−1, with a reduction of 18.82%. Operating cost can be significantly reduced at higher values of the stoichiometric oxygen excess for the SCWO system with OR. Moreover, the treatment cost for the SCWO system with OR decreases with increasing feed concentration for more reaction heat and oxygen recovery.

1. Introduction

Supercritical water (SCW) (P > 22.1 MPa, T > 374 °C) has unique thermo-physical characteristics [1], which can dissolve organic compounds and gases to form a homogeneous mixture without mass transfer resistance [2,3]. SCW has been widely used to treat organic waste by supercritical water oxidation (SCWO) or supercritical water gasification (SCWG) for high efficiency and low residence time [3,4,5]. In the SCWO process, no SO2 or NOX by-products during organic waste degradation emit [6,7,8]. Although SCWO has many unique advantages in treating wastewater, some technical problems, such as corrosion and salt plugging, have hindered its development for years [9,10]. Inorganic acids (e.g., HCl and H2SO4), combined with high temperature and high oxygen concentration, can cause severe corrosion of the reactor and other devices [11]. Inorganic salt is hardly soluble in SCW, which leads to the plugging of the reactor, as well as the preheating and cooling sections [12]. At present, an effective solution for corrosion and salt plugging is the use of a transpiring wall reactor (TWR). A TWR typically consists of a dual shell with an outer pressure-resistant vessel and an inner porous tube. Transpiring water at subcritical temperatures passes through the porous pipe to form a protective film on its inner surface. This water film can prevent reactants from spreading to the porous wall and dissolve inorganic salt. Numerous studies have proven that TWR plays an effective role in preventing corrosion and salt plugging [13,14,15].
A high treatment cost, which is due to material input (such as oxidants and additives) and energy consumption during the pressurization and heating steps, is another obstacle that hinders the SCWO application. Treatment cost is determined according to the adopted equipment, treatment capacity, concentrations, and types of organic matter, operating conditions, and staff costs. At present, the treatment cost for an SCWO system with 1000 kg/h wet organic waste and an organic matter content of 10 wt% typically ranges from tens to hundreds of dollars [16]. Energy recovery is the leading method for reducing energy consumption and operating cost. An autothermal operation with a certain feed concentration (>2 wt%) can be achieved under ideal conditions [17,18,19]. Power generation is another potential application that uses high-pressure and high-temperature reactor effluent [20,21,22]. However, the reactor effluent in an SCWO system with TWR is cooled to subcritical temperature (<360 °C) for transpiring water injection at a low temperature to avoid salt plugging [13]. Accordingly, feedstock preheating and hot water/steam production may be more realistic and effective choices [23,24].
Oxygen, the most popular oxidant in SCWO systems, is another major source of cost. Results have indicated that a stoichiometric oxygen excess (R) of 1.05 may be sufficient for complete oxidation of organic wastewater [16]. However, a higher amount of oxygen is required in the pilot or industrial plant, which is mainly due to the local heterogeneous state in the reactor. Thus, twice the value of R (or even higher) is obtained, which leads to oxygen loss. Xu et al. [25] conducted an economic analysis of urban sludge via SCWO using a 2.5 t/day demonstration device. The operating cost was approximately 83.1 $·t−1, with oxygen cost accounting for 25% of the total amount. Zhang et al. [26] analyzed a 100 t/day SCWO system for high-concentration printing and dyeing wastewater; the operating cost of the system was 10.3 $·t−1, with oxygen cost accounting for 37% of the total amount. Shen et al. [27] conducted an economic analysis of an SCWO system with TWR. The feed was 300 m3/day, with an initial concentration of 40,000 mg/L chemical oxygen demand; the cost was 4.99 $·t−1, with oxygen cost accounting for 71.8% of the total amount. Thus, oxygen consumption control will be an important solution for reducing operating cost.
In addition, CO2 is another primary gas in reactor effluent. However, it is low in purity due to excess oxygen consumption, which is the main obstacle that inhibits CO2 recovery and utilization. Thus, recovering CO2 with high purity may be another solution for reducing the operating cost of SCWO systems. The low operating cost calculated by Shen [27] is mainly attributed to the benefit of CO2 recovery. Abeln [28] reported that the operating cost of a 100 kg/h SCWO–TWR plant is approximately 659 €/t, and by-product income, such as surplus heat energy and CO2, must be ensured to obtain a comparably low operating cost.
Species recovery can considerably reduce operating cost for less input and additional income. However, only a few studies have focused on this issue, and a simple operation process with low energy consumption is urgently required for species recovery. In the current work, a species recovery process based on high-pressure water absorption was proposed to separate and recover oxygen and CO2. A two-stage gas–liquid separation process was established using Aspen Plus V8.0. Reasonable thermodynamic models for high-pressure separation were evaluated to identify the optimized separation parameters. Accordingly, SCWO processes with and without oxygen recovery (OR) were simulated, and energy consumption and economic analyses were conducted.

2. Proposal of OR for SCWO Systems

Baranenko et al. [29] tested the solubility of oxygen and CO2 in high-pressure water at temperatures ranging from 0 °C to 360 °C and pressures from 1 MPa to 20 MPa. The solubility of oxygen (Figure 1a) and CO2 (Figure 1b) increases with increasing pressure, but the effect of temperature on solubility does not exhibit a distinct trend. At low pressures, an evident reduction in solubility is observed as temperature increases. At high pressures, solubility initially decreases, then increases, and finally decreases with increasing temperature. Thus, two solubility extremes occur in the wave curve of the high-pressure zone. Moreover, the solubility of CO2 is nearly one order of magnitude higher than that of oxygen under the same conditions. Given that reactor effluent is mostly composed of oxygen, CO2, and water, the ratio of oxygen to CO2 in the gaseous phase under different conditions is calculated using the typical effluent composition in our previous pilot plant.
Over 80% of oxygen cannot be dissolved in high-pressure water and occurs in gaseous phase at P < 9 MPa and 20 °C < T < 360 °C, as shown in Figure 2a. In addition, Figure 2b shows that CO2 can be dissolved completely in water under certain conditions. Moreover, low temperatures are conducive to dissolving CO2 in water. CO2 can dissolve completely in water at temperatures below 20 °C when P = 2 MPa; however, temperature can be increased to 280 °C when P = 10 MPa. Thus, the temperatures for completely dissolving CO2 in water can be increased at high pressures. Figure 2c shows the releasing ratio difference in gaseous phase between oxygen and CO2. The temperature zone gradually widens with increasing pressure to obtain a high releasing ratio, but the releasing ratio difference slowly decreases. The temperature zone between 20 °C and 60 °C can reach a releasing ratio difference of 80% at 2 MPa. However, when pressure is increased to 8 MPa, the temperature zone can be widened to a range of 20 °C to 240 °C. These results have motivated us to develop a solution for separating oxygen and CO2 by adjusting reactor effluent parameters. Thus, a new process for improving oxygen utilization rate in SCWO systems [30] is proposed, as shown in Figure 3.
In the proposed SCWO process, excess oxygen and preheated organic waste are injected from the top of the TWR, which initiates the oxidation reaction. Simultaneously, two branches of transpiring water with different temperatures are injected from the side of the TWR to protect the reactor. The reactor effluent first enters a high-pressure gas–liquid separator after heat exchange and depressurization. Most of the oxygen is released in gaseous phase, whereas most of the CO2 is dissolved in aqueous phase for the solubility difference between oxygen and CO2 in water, thereby achieving the separation of oxygen and CO2. Subsequently, oxygen is reused through the oxygen circulation pump. The aqueous fluid from the high-pressure gas–liquid separator is adjusted further and injected into a low-pressure separator, whereas CO2 is released and collected. Therefore, oxygen and CO2 are separated and recovered.

3. High-Pressure Separation for Reactor Effluent

3.1. High-Pressure Separation Process

To identify optimized parameters for OR, a simulation flow of a two-step separation process for reactor effluent based on high-pressure water absorption was first established using Aspen Plus V8.0 (Figure 4). High- and low-pressure gas–liquid separators were introduced to separate and recover oxygen and CO2.

3.2. Definition of Process Parameters

The OR ratio (γO2) is defined as the oxygen in the gaseous phase of the high-pressure separator divided by the oxygen in the reactor effluent:
γ O 2 = F O 2 , g F O 2 , g + F O 2 , l  
where F O 2 , g and F O 2 , l are the oxygen mass flows in the gaseous and aqueous phases, respectively, of the high-pressure separator.
Oxygen purity (βO2) is defined as the oxygen ratio in the gaseous phase of the high-pressure separator, which can be calculated as follows:
β O 2 = F O 2 , g F O 2 , g + F CO 2 , g + F H 2 O , g  
where F CO 2 , g and F H 2 O , g are the mass flows of CO2 and water in the gaseous phase, respectively. Water can be typically disregarded when its content is small.
Similarly, the CO2 recovery ratio (γCO2) is defined as the CO2 in the gaseous phase of the low-pressure separator divided by the CO2 in the reactor effluent:
γ CO 2 = F CO 2 , g F CO 2 , g + F CO 2 , l  
where F CO 2 , g is the CO2 mass flow in the gaseous phase of the low-pressure separator, and F CO 2 , l is the CO2 mass flow in the aqueous phase of the high-pressure separator.
CO2 purity (βCO2) is defined as the CO2 ratio in the gaseous phase of the low-pressure separator, which can be calculated as follows:
β CO 2 = F CO 2 , g F O 2 , g + F CO 2 , g + F H 2 O , g  
where F O 2 , g and F H 2 O , g are the mass flows of oxygen and water, respectively, in the gaseous phase of the low-pressure separator, and water can be typically disregarded when its content is small.
The mass flow rate of oxygen is calculated using a constant R [18], which is defined as follows:
R = F O 2 1.5 F f ω  
where F O 2 (kg/h) and Ff (kg/h) are the mass flow rates of oxygen and the feed, respectively; and ω (wt%) is the methanol concentration in the feed.

3.3. Thermodynamic Property Models

The selection of an appropriate model for estimating the thermodynamic properties of reactor effluent is one of the most important steps that can affect the simulation results. To date, no model has been adopted for all the components and processes. Moreover, the same model cannot be used under all operating conditions, especially at wide ranges of pressure (0.1–23 MPa) and temperature (20–360 °C). Therefore, an appropriate method for estimating the separation process should be carefully selected. Aspen Plus includes a large databank of thermodynamic properties and transport models with the corresponding mixing rules for estimating mixture properties. Several potential thermodynamic models recommended by Aspen Plus were selected and tested (as listed in Table 1) based on the composition of our reactor effluent (i.e., water, CO2, and oxygen) and the range of the operating conditions. The selected models were simulated with default interaction parameters for the preliminary assessment due to the lack of component interaction coefficients within a large range. The γO2 and γCO2 values at different pressure and temperature values with 10 recommended thermodynamic models were plotted in Figure 5. Additionally, the ideal results calculated from the experimental solubility data of Baranenko et al. [29] were also plotted for the comparison and verification of the thermodynamic models. In the ideal results calculation, the reactor effluent was assumed to conduct an ideal separation in the high-pressure and low-pressure separators, and the interaction between O2 and CO2 has been ignored.
Identifying an accurate thermodynamic model that can fulfill the standard for CO2 and oxygen within a wide range of temperature and pressure values is difficult, as shown in Figure 5. The γO2 (Figure 5a,c,e,g,i,k) calculated using the BWR-LS, PR-BM, SR-POLAR, SRK, PSRK, RKS-BM, and LK-Plock models agree well with the ideal results calculated from the experimental solubility data (red curves) of Baranenko et al. [29]. By contrast, the comparison of γCO2 between the thermodynamic models and the ideal results present more complex information. At 0.1 MPa (Figure 5b), all the models can accurately predict γCO2. At 2 MPa (Figure 5d) and 4 MPa (Figure 5f), only the PSRK, RKS-BM, and RKS-MHV2 models exhibit accurate prediction performance in terms of trend and value. At higher pressures (i.e., 6, 8, and 10 MPa), only the PSRK model (magenta curves) can achieve good prediction performance, with a maximal deviation of less than 20% (Figure 5h,j,l). Thus, PSRK is selected as the thermodynamic model for the high-pressure separation process in this study under the comprehensive consideration of γO2 and γCO2. A detailed model expression for PSRK is available in the literature [31].

3.4. Effects of Operating Parameters

3.4.1. Stoichiometric Oxygen Excess

The interaction between the high- and low-pressure separators typically results in different recovery ratio and purity values for oxygen and CO2. For convenience, the separation parameters of the low-pressure separator are set under ambient conditions (P = 0.1 MPa, T = 20 °C) and, thus, we focus only on the separation parameters of the high-pressure separator.
Figure 6(a1–a4,b1–b4) show that a temperature increase or a pressure decrease is favorable for increasing γO2 but unfavorable for increasing βO2. R = 1.5 is used as an example. γO2 is 89.3% at P = 8 MPa and T = 20 °C, and it increased to 92.8% when pressure decreased to 5 MPa. γO2 increased further to 96.4% when pressure and temperature were modified to 5 MPa and 90 °C, respectively (Figure 6(a1)). Similarly, βO2 is 78.5% at P = 8 MPa and T = 20 °C. It decreased to 70.1% when pressure was reduced to 5 MPa and to 56.5% when pressure and temperature were adjusted to 5 MPa and 90 °C, respectively (Figure 6(b1)).
The input of the low-pressure separator came from the aqueous mixture of the high-pressure separator. Thus, γCO2 and βCO2 in the low-pressure separator are dependent on the separation parameters of the high-pressure separator. A standard for the high-pressure separator is first defined with high values of γO2 (>80%) and βO2 (>70%) to narrow down the parameter range. The separating pressure and temperature values that can fulfill the standard can then be obtained. Subsequently, γCO2 and βCO2 are analyzed based on the high-pressure separation results. Figure 6(c1–c4) show that a temperature increase or a pressure decrease in the high-pressure separator decreases γCO2, which is contrary to the effects of pressure and temperature on γO2. R = 1.5 is used as an example. γCO2 is 78.9% at 8 MPa and 30 °C, and it decreased to 42.1% at 5 MPa and 90 °C (Figure 6(c1)). Moreover, Figure 6(d1–d4) show that a decrease in temperature and pressure are beneficial for βCO2. βCO2 is 83.3% at 8 MPa and 90 °C, and it increased to 86.7% when pressure decreased to 5 MPa. Moreover, βCO2 increased further to 88.7% when pressure and temperature were decreased to 5 MPa and 30 °C, respectively (Figure 6(d1)).
Figure 6 shows that an increase in R contributes to an increase in γO2 and βO2, but decreases the values of γCO2 and βCO2. γO2, βO2, γCO2, and βCO2 at P = 5 MPa and T = 90 °C are 92.8%, 56.5%, 42.1%, and 88.9%, respectively, at R = 1.5. γO2 and βO2 increased to 98.2% and 78.5%, respectively, whereas γCO2 and βCO2 decreased to 15.7% and 75%, respectively, when R increased to 3. An increase in R increases the amount of oxygen in reactor effluent, whereas the amount of CO2 remains constant (constant (Table 2(A1−A4))). An increase in R is conducive to OR, but reduces CO2 recovery and purity. The optimized parameters are provided in Table 2(A1−A4). pressure range of 6 MPa to 7 MPa and a temperature range of 30 °C to 40 °C are appropriate for the high-pressure separator.

3.4.2. Feed Concentration

The effects of pressure and temperature at different feed concentrations on species recovery and purity (Figure 7(a1−a5,b1−b5,c1−c5,d1−d5)) are similar to those discussed in the previous section. The values of γCO2 and βO2 will be lower at higher feed concentrations, but the values of γO2 and βCO2 will be higher. Although an increase in feed concentration will increase the amounts of oxygen and CO2 in the reactor effluent with the same proportion, the solubility difference between oxygen and CO2 in the water achieves the following results. The γO2, βO2, γCO2, and βCO2 at P = 5 MPa and T = 90 °C are 88.9%, 80.0%, 50.0%, and 66.7% at ω = 2 wt%, respectively (Figure 7(a1,b1,c1,d1)). When ω increased to 10 wt%, γO2 and βCO2 increased to 98.2% and 85.7%, respectively, but βO2 and γCO2 decreased to 68.2% and 19.3%, respectively (Figure 7(a5,b5,c5,d5)).
Therefore, an increase in feed concentration is also conducive to OR, but oxygen purity will be lower. Moreover, an increase in feed concentration is unfavorable for CO2 recovery, but high CO2 purity will be obtained. The optimized parameters at different feed concentrations are provided in (B1−B4) in Table 2. A pressure range of 5 MPa to 7 MPa and a temperature range of 30 °C to 70 °C are appropriate for the high-pressure separator.

4. Aspen Model for SCWO System Simulation with Energy and Species Recovery

In this section, our pilot plant was amplified similar to an SCWO industrial plant with a treatment capacity of 1000 kg/h based on the optimized parameters for energy and species recovery. The simulation process can be established without considering the complex equipment structure in Aspen Plus, which is a 1D simulation software based on mass and energy conservation.

4.1. TWR

A TWR is the most important equipment of an SCWO system, and Figure 8a shows the diagram of the TWR in our pilot plant [13]. Five streams were introduced into the reactor. The oxygen and the feed were injected into the reactor via a coaxial nozzle from the top of the reactor, with oxygen in the central tube and the feed in the outer tube. The transpiring tube is divided into three zones using two retaining rings to ensure that the transpiring streams can pass through the porous tube at different temperatures and flow rates. The transpiring water (tw) is divided into three branches, namely, the upper (tw1), middle (tw2), and lower (tw3) branches of transpiring water.
Considering the complicated flow, transpiring heat, and reaction characteristics, the reactor was separated into three sections for simplicity, namely, the mixing, adiabatic reacting, and cooling sections. A simplified model was proposed to simulate the TWR (Figure 8b) in Aspen Plus. The mixing section provides a sufficient mixing space for the reactants. Among the three branches of transpiring water, the upper branch is the only one that can directly influence the reaction [11]. For simplicity, the feed, oxygen, and upper branch of transpiring water will first flow into a mixer to fully mix the reactants. The adiabatic reacting section is simulated by a plug flow reactor (PLUG). When reaction is done, the product flows into the cooling section where the middle and lower branches of transpiring water are injected sequentially into the reactor, and the two mixers are used to simulate the mixing process. Finally, hot effluent flows out of the reactor.

4.2. Reaction

A desalinated water–methanol mixture is also used as artificial wastewater in Aspen Plus. Previous experimental results [13,32] have proven that CO is the major intermediate during the SCWO of methanol. Thus, a two-step mechanism based on Arrhenius law is created and implemented in the simulation, as shown in Equations (6) to (9):
CH 3 OH + O 2 = CO + H 2 O  
CO + 0.5 O 2 = CO 2  
r CH 3 OH = d [ CH 3 OH ] d t = 2 . 0 × 10 21 × exp ( 303 . 85   kJ / mol RT ) [ CH 3 OH ]  
r CO = d [ CO ] d t = 3.16 × 10 6 × exp ( 88 kJ / mol RT ) [ CO ]  
The kinetic data used in the present study were based on the literature [33,34,35,36], and the reaction order of oxygen was assumed zero because of the large excess amount.

4.3. Process Flow

The simulation process, including energy recovery and OR, was developed and presented in Figure 9. After the feed is pressurized by pump 1 (P1), it first flows into heat exchanger 1 (HE1) to be heated by one branch of the final products (FINAL), and then it flows into electric heater 1 (EH1) for further heating. Simultaneously, oxygen is pressurized by the air compressor (AC), and then flows into mixer 1 (M1) to fully mix with the feed and tw1. After transpiring water is pressurized by pump 2 (P2), it splits into three branches (tw1, tw2, and tw3). Before tw1 reaches M1, it first flows into heat exchanger 2 (HE2) to be preheated, and then flows to electric heater 2 (EH2) for further heating. tw2 is preheated by heat exchanger 3 (HE3), and then it mixes with the effluent in mixer 2 (M2). tw3 mixes with the effluent in mixer 3 (M3) to form the final products (FINAL). Oxygen and tw3 are injected into the reactor at room temperature.
FINAL is split into two branches in split 2, and these branches are treated as hot streams to preheat the feed and tw1. The two branches of FINAL then reunite in mixer 4 (M4) and are cooled down in heat exchanger 3 (HE3). Moreover, the effluent was further cooled in heat exchangers 4 (HE4) and 5 (HE5) by cooling water before gas–liquid separators 1 (S1) and 2 (S2), respectively. The recovered oxygen from S1 is pressurized by pump 3 (P3) and mixed with the supplement oxygen in mixer 5 (M5).

5. Energy and Economic Analysis

5.1. Equipment Investment Calculation

Several alternatives are available to estimate the cost of a major piece of equipment, such as obtaining a quotation from a suitable vendor, using the cost data of a previously purchased equipment of the same type, or utilizing available summary graphs for various types of common equipment. Considering that no similar SCWO industrial plant exists, the last option may be more accurate for our preliminary cost estimation. This methodology allows the estimation of equipment and installation costs according to certain base conditions (e.g., low pressure and construction materials with the lowest cost) and a particular year. Deviations from the base conditions are corrected by a factor that depends on working pressure and construction materials. The obtained cost is then translated into the current time by using an index that considers the time variation of equipment cost.
On the basis of the results obtained for the pilot plant under typical conditions (Table 3, B3, and D3), economic analyses for the 1000 kg/h SCWO plant with and without OR were performed. The investment costs for the TWR, high-pressure pumps, compressors, electric heaters, and gas–liquid separators can be calculated as follows [37]:
C PM = C ( B 1 + B 2 F M F P )  
lg C = K 1 + K 2 lgX + K 3 ( lg X ) 2  
lg F P = C 1 + C 2 lg P + C 3 ( lg P ) 2  
where C is the equipment investment that uses carbon steel under environmental conditions, and X is the design parameter (e.g., pump power and reactor volume). P is the design pressure, which is set as 30 MPa. K1, K2, K3, C1, C2, C3, B1, and B2 are constant for each piece of equipment. FP and FM are the pressure and material correction coefficients, respectively. Detailed data are provided in Table 4.
Directly estimating the cost of the TWR is difficult because no similar reactor is available for comparison. The cost of a plug flow reactor was first estimated with the same volume for sufficient residence time, and then the cost of the TWR was calculated based on our empirical relationship. The reactor was divided into three sections according to our previous TWR design [24]. The total required volume of the reactor is 570 L. Thus, the actual reactor volume is 695 L when a loading coefficient of 0.82 is considered [38].
Shell and tube heat exchangers were selected in the SCWO system, and the cost of the regular heat exchanger can be calculated as follows [39]:
C HE = 3.28 × 10 4 ( A 80 ) 0.68 δ M δ P δ T  
where A is the heat exchanger area. Considering that the heat exchanger was used in high-pressure and high-temperature conditions, δM, δP, and δT are the material, pressure, and temperature correction coefficients (Table 5), respectively, which were used to modify cost estimation.
The obtained cost is then translated into the present time by using an index that considers the time variation of equipment cost for the process industries, which was calculated using the following equation [37]:
C o s t 2016 = C o s t 2001 ( C E P C I 2016 C E P C I 2001 )  
Given the aforementioned considerations, the total equipment cost for the SCWO pilot plant with and without OR in 2016 was calculated as $2,592,096 and $2,522,654, respectively. Details on equipment sizing assumptions, construction materials, and estimated cost per piece of equipment are presented in Table 6.

5.2. Treatment Cost Calculation and Distribution

The treatment cost of an SCWO system includes investment and operating costs. The basic operating costs were determined using the procedure parameters in Table 3 (B3) and (D3), which were estimated under the assumption that the plant operates 330 days a year and 24 h a day. The operating cost includes energy consumption, raw material, labor, and capital-related costs [36]. Energy consumption cost includes the cost of electricity required to operate the process equipment and the plant. Raw material cost, which includes the costs of oxygen, cooling water, and transpiring water, was estimated from the amount of required raw materials. Labor cost includes the salaries of operation and supervisory employees. The depreciation time of the system is 10 years, and the maintenance cost is 3% of the equipment cost.
Figure 10 shows the treatment cost comparisons of the SCWO systems with and without OR. In the SCWO system without OR, electricity, depreciation, and oxygen contribute to the primary treatment cost, accounting for 46.18, 30.24, and 18.01 $·t−1, respectively, of the total cost. Although the heat of the reactor effluent has been recovered, energy (electricity) consumption remains high. This phenomenon is attributed to the low-grade heat of the reaction effluent (<370 °C) due to the injection of transpiring water at a low temperature to avoid salt plugging. Hot water, which comprises the major income of the system, was calculated as a negative value in the treatment cost and accounted for −56.72 $·t−1. Thus, the total treatment cost for the SCWO system without OR is 56.80 $·t−1, with electricity and oxygen cost accounting for 81.30% and 31.69% of the total treatment cost, respectively.
Electricity, depreciation, and oxygen still contribute to the primary treatment cost of the SCWO system with OR. Electricity consumption slight decreases from 46.18 $·t−1 to 45.88 $·t−1 due to OR, but oxygen cost significantly decreased from 18.01 $·t−1 to 9.77 $·t−1. Additionally, the additional income of CO2, which accounted for −5.65 $·t−1, was obtained due to OR. Treatment cost considerably decreased from 56.80 $·t−1 to 46.17 $·t−1, with a reduction rate of 18.82%. Thus, OR considerably contributes to reducing the treatment cost of an SCWO system.

5.3. Effect of Stoichiometric Oxygen Excess

On the basis of the previously designed system, this section investigates the effects of the operating parameters on energy consumption and treatment cost. Similar to the previous analysis, several episodes of actual oxygen consumption may be necessary for complete feed degradation. Thus, the effect of R on the treatment cost of the SCWO systems with and without OR is analyzed in this section, and the operating parameters and detailed results are listed in Table 3(A1–A4, C1–C4) and Table 7(A1–A4, C1–C4). Electricity consumption and hot water income increase slightly with an increase in R in both SCWO systems (Figure 11a,e). Oxygen consumption increases linearly with an increase in R in the SCWO system without OR. When R increased from 1.5 to 3, oxygen consumption considerably increased from 13.5 $·t−1 to 27 $·t−1 (Figure 11b). Furthermore, a slight increase in cooling water consumption (Figure 11d) occurs with an increase in R. An increase in R has minimal effect on depreciation, repair (Figure 11c), transpiring water consumption, manpower (Figure 11d), and CO2 income (Figure 11e). Thus, the treatment cost of the SCWO system without OR can increase from 53.89 $·t−1 to 65.25 $·t−1 (Figure 11f) when R increased from 1.5 to 3. In the SCWO system with OR, oxygen consumption in the start-up stage is equal to that of the SCWO system without OR. However, the supplemental oxygen content is gradually reduced to a value that is slightly higher than the actual oxygen consumption after attaining OR equilibrium (Table 3). Thus, an increase in R exerts minimal effect on oxygen consumption (Figure 11b). Moreover, high-purity CO2 can be recovered as an income due to OR (Figure 11e). In addition, equipment repairs and depreciation (Figure 11c), cooling water, transpiring water, and manpower consumption (Figure 11d) also exhibit minimal differences with varying R values. Figure 11f shows that the treatment cost of the SCWO system with OR slightly increased from 46.63 $·t−1 at R = 1.5 to 48.89 $·t−1 at R = 3, which motivates us to operate the SCWO system with a high R value for complete feed degradation.

5.4. Effect of the Feed Concentration

The treatment cost for feed concentration between 2 wt% and 8 wt% is tested in this section under operating conditions, and the detailed results are listed in Table 3(B1–B4, D1–D4) and Table 7(B1–B4, D1–D4). When feed concentration increases, oxygen and transpiring water flow rates will also increase for feed degradation and reactor protection, and consequently, the electricity consumption of the pumps will also increase. However, reaction heat linearly increases with increasing feed concentration, and more heat can be recovered from the reactor effluent. Moreover, the preheating temperature of the feed at the starting and steady states can be reduced at a high feed concentration [40]. Thus, the total electricity consumption of the systems with and without OR decreased from 49.51 $·t−1 and 49.80 $·t−1 to 44.35 $·t−1 and 43.91 $·t−1, respectively, when feed concentration was increased from 2 wt% to 8 wt% (Figure 12a).
Oxygen consumption significantly increased from 6.00 $·t−1 at ω = 2 wt% to 24.00 $·t−1 at ω = 8 wt% (Figure 12b), and hot water income considerably increased from 48.6 $·t−1 to 60.75 $·t−1 (Figure 12e) in the SCWO system without OR. Thus, treatment cost can increase from 54.82 $·t−1 at ω = 2 wt% to 57.93 $·t−1 at ω = 8 wt% (Figure 12f). In the SCWO system with OR, when feed concentration was increased from 2 wt% to 8 wt%, the supplemental oxygen content increased from 3.26 $·t−1 to 13.05 $·t−1, respectively (Figure 12b), and hot water and CO2 income increased from 47.25 $·t−1 and 1.57 $·t−1 to 58.05 $·t−1 and 7.22 $·t−1, respectively (Figure 12e). Figure 12f shows that the treatment cost of the SCWO system with OR decreased from 54.27 $·t−1 at ω = 2 wt% to 42.06 $·t−1 at ω = 8 wt%. Thus, an increase in feed concentration is conducive to reducing both the energy consumption and the treatment cost of the SCWO system with OR.

6. Conclusions

In this work, a species recovery process for an SCWO system with a TWR was first proposed based on the solubility difference between oxygen and CO2 in high-pressure water. Thus, oxygen and CO2 can be separated and recovered from the reactor effluent to reduce operating cost.
A two-step separation process was first established using Aspen Plus software to increase species recovery rate. Then, 10 potential thermodynamic models for high-pressure separation were evaluated and selected. The detailed recovery rates of oxygen and CO2 were compared with the ideal results calculated from the experimental solubility data. The PSRK model was proven to be an appropriate thermodynamic model for predicting the separation process of the reactor effluent under a wide range of conditions. Accordingly, the detailed optimized parameters for species separation were obtained.
The SCWO processes with and without OR were simulated and economic analyses were conducted. Electricity, depreciation, and oxygen costs contribute to the major treatment cost of the SCWO system without OR, accounting for 46.18, 30.24, and 18.01 $·t−1, respectively. When OR was introduced, oxygen cost decreased from 18.01 $·t−1 to 9.77 $·t−1, and additional CO2 income, which amounted to −5.65 $·t−1, was gained due to OR. The total treatment cost considerably decreased from 56.80 $·t−1 to 46.17 $·t−1, with a reduction rate of 18.82%. Thus, OR contributes to reducing the treatment cost of an SCWO system. In addition, R and feed concentration increased and contributed to reducing the operating cost of the SCWO system with OR.
As a preliminary study of new SCWO system with OR, more experiments are needed to obtain more accurate results based on the simulation results in the future.

Author Contributions

F.Z. and C.M. put forward the idea of this work, F.Z. wrote this paper, J.C. conducted the simulation and calculation, F.Z., J.C., and C.S. contributed to the results analysis and post-processing.

Funding

This work is supported by National Natural Science Foundation (no. 51706049), Youth Innovation Promotion Association CAS (no. 2017412), and Science research project of Guangzhou City (201707010407).

Conflicts of Interest

The authors declare no conflict of interest.

Nomenclature

Abbreviations
Aarea
ACair compressor
Ccapital
CODchemical oxygen demand
EHelectric heater
Fmass flow rate, kg·h−1
FINALFinal products
FPpressure correction coefficient
FMmaterial correction coefficient
HEheat exchanger
Mmixer
ORoxygen recovery
Ppressure/ pump
Rtranspiring intensity, universal gas constant
SSeparator
SCWsupercritical water
SCWGsupercritical water gasification
SCWOsupercritical water oxidation
rreaction rate
Rstoichiometric oxygen excess
ttime, s
Ttemperature, °C
tw1upper branch of transpiring water
tw2middle branch of transpiring water
tw3lower branch of transpiring water
TWRtranspiring wall reactor
TOCtotal organic carbon, ppm
XDesign parameter
Greek letters
βpurity
ρfluid density, kg·m−3
φtranspiring intensity
γrecovery ratio
δcorrection coefficient
ωfeed concentration, wt%
Subscripts
cwcooling water
ffeed
ggas
lliquid
mmaterial
susupplement
outoutlet
tottotal

References

  1. Akiya, N.; Savage, P.E. Roles of Water for Chemical Reactions in High Temperature Water. Chem. Rev. 2002, 33, 2725–2750. [Google Scholar] [CrossRef]
  2. Xu, D.H.; Huang, C.B.; Wang, S.Z.; Lin, G.K.; Guo, Y. Salt deposition problems in supercritical water oxidation. Chem. Eng. J. 2015, 279, 1010–1022. [Google Scholar] [CrossRef]
  3. Queiroz, J.P.S.; Bermejo, M.D.; Mato, F.; Cocero, M.J. Supercritical water oxidation with hydrothermal flame as internal heat source: Efficient and clean energy production from waste. J. Supercrit. Fluid 2015, 96, 103–113. [Google Scholar] [CrossRef]
  4. Molino, A.; Migliori, M.; Blasi, A.; Davoli, M.; Marino, T.; Chianese, S.; Catizzone, E.; Giordano, G. Municipal waste leachate conversion via catalytic supercritical water gasification process. Fuel 2017, 206, 155–161. [Google Scholar] [CrossRef]
  5. Fedyaeva, O.N.; Vostrikov, A.A.; Shishkin, A.V.; Dubov, D.Y. Conjugated processes of black liquor mineral and organic components conversion in supercritical water. J. Supercrit. Fluids 2019, 143, 191–197. [Google Scholar] [CrossRef]
  6. Vadillo, V.; Belén García-Jarana, M.B.; Sánchez-Oneto, J.; Portela, J.R.; de la Ossa, E.J.M. Simulation of Real Wastewater Supercritical Water Oxidation at High Concentration on a Pilot Plant Scale. Ind. Eng. Chem. Res. 2011, 50, 2512–2520. [Google Scholar] [CrossRef]
  7. Zhang, F.M.; Chen, S.Y.; Xu, C.Y.; Chen, G.F.; Ma, C.Y. Energy consumption analysis of a transpiring-wall supercritical water oxidation pilot plant based on energy recovery. Desalin. Water Treat. 2013, 51, 7341–7352. [Google Scholar] [CrossRef]
  8. Fourcault, A.; García-Jarana, B.; Sánchez-Oneto, J.; Marias, F.; Portela, J.R. Supercritical water oxidation of phenol with air. Experimental results and modelling. Chem. Eng. J. 2009, 152, 227–233. [Google Scholar] [CrossRef]
  9. Marrone, P.A. Supercritical water oxidation-Current status of full-scale commercial activity for waste destruction. J. Supercrit. Fluid 2013, 79, 283–288. [Google Scholar] [CrossRef]
  10. Vadillo, V.; Sánchez-Oneto, J.; Portela, J.R.; de la Ossa, E.J.M. Problems in Supercritical Water Oxidation Process and Proposed Solutions. Ind. Eng. Chem. Res. 2013, 52, 7617–7629. [Google Scholar] [CrossRef]
  11. Kritzer, P. Corrosion in high-temperature and supercritical water and aqueous solutions: A review. J. Supercrit. Fluid 2004, 29, 1–29. [Google Scholar] [CrossRef]
  12. Hodes, M.; Marrone, P.A.; Hong, G.T.; Smith, K.A.; Tester, J.W. Salt precipitation and scale control in supercritical water oxidation–Part A: Fundamentals and research. J. Supercrit. Fluids 2004, 29, 265–288. [Google Scholar] [CrossRef]
  13. Zhang, F.M.; Chen, S.Y.; Xu, C.Y.; Chen, G.F.; Zhang, J.M.; Ma, C.Y. Experimental study on the effects of operating parameters on the performance of a transpiring-wall supercritical water oxidation reactor. Desalination 2012, 294, 60–66. [Google Scholar] [CrossRef]
  14. Bermejo, M.D.; Cocero, M.J. Supercritical water oxidation: A technical review. AIChE J. 2006, 52, 3933–3951. [Google Scholar] [CrossRef]
  15. Xu, D.H.; Wang, S.Z.; Huang, C.B.; Tang, X.Y.; Guo, Y. Transpiring wall reactor in supercritical water oxidation. Chem. Eng. Res. Des. 2014, 92, 2626–2639. [Google Scholar] [CrossRef]
  16. Kritzer, P.; Dinjus, E. An assessment of supercritical water oxidation (SCWO)-Existing problems, possible solutions and new reactor concepts. Chem. Eng. J. 2001, 83, 207–214. [Google Scholar] [CrossRef]
  17. Kodra, D.; Balakotaiah, V. Autothermal oxidation of dilute aqueous wastes under supercritical conditions. Ind. Eng. Chem. Res. 1994, 33, 575–580. [Google Scholar] [CrossRef]
  18. Lavric, E.D.; Weyten, H.; Ruyck, J.D.; Plesu, V.; Lavric, V. Delocalized organic pollutant destruction through a self-sustaining supercritical water oxidation process. Energy Convers. Manag. 2005, 46, 1345–1364. [Google Scholar] [CrossRef]
  19. Cocero, M.J.; Alonso, E.; Sanz, M.T.; Fdz-Polanco, F. Supercritical water oxidation process under energetically self-sufficient operation. J. Supercrit. Fluids 2002, 24, 37–46. [Google Scholar] [CrossRef]
  20. Bermejo, M.D.; Cocero, M.J.; Ferna´ndez-Polanco, F. A process for generating power from the oxidation of coal in supercritical water. Fuel 2004, 83, 195–204. [Google Scholar] [CrossRef]
  21. Marias, F.; Mancini, F.; Cansell, F.; Mercadier, J. Energy recovery in supercritical water oxidation process. Environ. Eng. Sci. 2008, 25, 123–130. [Google Scholar] [CrossRef]
  22. Lavric, E.D.; Weyten, H.; De Ruyck, J.; Plesu, V.; Lavric, V. Supercritical water oxidation improvements through chemical reactors energy integration. Appl. Therm. Eng. 2006, 26, 1385–1392. [Google Scholar] [CrossRef]
  23. Jimenez-Espadafor, F.; Portela, J.R.; Vadillo, V.; Sánchez-Oneto, J.; Becerra Villanueva, J.A.; Torres García, M.; Martínez de la Ossa, E.J. Supercritical water oxidation of oily wastes at pilot plant: Simulation for energy recovery. Ind. Eng. Chem. Res. 2011, 50, 775–784. [Google Scholar] [CrossRef]
  24. Zhang, F.M.; Shen, B.Y.; Su, C.J.; Xu, C.Y.; Ma, J.N.; Xiong, Y.; Ma, C.Y. Energy consumption and exergy analyses of a supercritical water oxidation system with a transpiring wall reactor. Energy Convers. Manag. 2017, 145, 82–92. [Google Scholar] [CrossRef]
  25. Xu, D.H.; Wang, S.Z.; Gong, Y.M.; Guo, Y.; Tang, X.Y.; Ma, H.H. A demonstration plant for treating sewage sludge by supercritical water oxidation and its economic analysis. Mod. Chem. Ind. 2009, 29, 55–59. [Google Scholar]
  26. Zhang, J.; Wang, S.Z.; Lu, J.L.; Chen, S.L.; Li, Y.H.; Ren, M.M. A system for treating high concentration textile wastewater and sludge by supercritical water oxidation and its economic analysis. Mod. Chem. Ind. 2016, 36, 154–158. [Google Scholar]
  27. Shen, X.F.; Ma, C.Y.; Wang, Z.Q.; Chen, G.F.; Chen, S.Y.; Zhang, J.M.; Yi, B.K. Economic analysis of organic waste liquid treatment through supercritical water oxidation system. Environ. Eng. 2010, 28, 47–51. [Google Scholar]
  28. Abeln, J.; Kluth, M.; Pagel, M. Results and rough costestimation for SCWO of painting effluents using a transpiring wall and a pipe reactor. J. Adv. Oxid. Technol. 2007, 10, 169–176. [Google Scholar]
  29. Baranenko, V.I.; Fal’kovskii, L.N.; Kirov, V.S.; Kurnyk, L.N.; Musienko, A.N.; Piontkovskii, A.I. Solubility of oxygen and carbon dioxide in water. At. Energy 1990, 68, 342–346. [Google Scholar] [CrossRef]
  30. Ma, C.Y.; Zhang, F.M.; Chen, S.Y.; Chen, G.F.; Zhang, J.M. A Method of Improving Oxygen Utilization Rate in Supercritical Water Oxidation System. Chinese Patent ZL 201010174846.9, 18 May 2010. [Google Scholar]
  31. Holderbaum, T.; Gmehling, J. PSRK: A group contribution equation of state based on UNIFAC. Fluid Phase Equilib. 1991, 70, 251–265. [Google Scholar] [CrossRef]
  32. Zhang, F.M.; Xu, C.Y.; Zhang, Y.; Chen, S.Y.; Chen, G.; Ma, C.Y. Experimental study on the operating characteristics of an inner preheating transpiring wall reactor for supercritical water oxidation: Temperature profiles and product properties. Energy 2014, 66, 577–587. [Google Scholar] [CrossRef]
  33. Li, L.; Chen, P.; Gloyna, E.F. Generalized kinetic model for wet oxidation of organic compounds. AIChE J. 1991, 37, 1687–1697. [Google Scholar] [CrossRef]
  34. Vogel, F.; Blanchard, J.L.D.; Marrone, P.A.; Rice, S.F.; Webley, P.A.; Peters, W.A.; Smith, K.A.; Tester, J.W. Critical review of kinetic data for the oxidation of methanol in supercritical water. J. Supercrit. Fluid 2005, 34, 249–286. [Google Scholar] [CrossRef]
  35. Dagaut, P.; Cathonnet, M.; Boettner, J. Chemical Kinetic Modeling of the Supercritical-Water Oxidation of Methanol. J. Supercrit. Fluids 1996, 98, 33–42. [Google Scholar] [CrossRef]
  36. Tester, J.W.; Webley, P.A.; Holgate, H.R. Revised global kinetic measurements of methanol oxidation in supercritical water. Ind. Eng. Chem. Res. 1993, 32, 236–239. [Google Scholar] [CrossRef]
  37. Turton, R.; Bailie, R.C.; Whiting, W.B.; Bhattacharyya, D. Analysis, Synthesis and Design of Chemical Processes; Prentice Hall: Upper Saddle River, NJ, USA, 2012. [Google Scholar]
  38. Shen, X.F. Design and Technical Economic Analysis on Heat Supply System by Supercritical Water Oxidation Energy Conversion. Master’s Thesis, Shandong University, Jinan, China, 2009. [Google Scholar]
  39. Wildi-Tremblay, P.; Gosselin, L. Minimizing shell-and-tube heat exchanger cost with genetic algorithms and considering maintenance. Int. J. Energy Res. 2007, 31, 867–888. [Google Scholar] [CrossRef]
  40. Zhang, F.M.; Zhang, Y.; Xu, C.Y.; Chen, S.Y.; Chen, G.F.; Ma, C.Y. Experimental study on the ignition and extinction characteristics of the hydrothermal flame. Chem. Eng. Technol. 2015, 38, 2054–2066. [Google Scholar] [CrossRef]
Figure 1. The solubility of oxygen (a) and carbon dioxide (b) in the high-pressure water.
Figure 1. The solubility of oxygen (a) and carbon dioxide (b) in the high-pressure water.
Processes 06 00224 g001
Figure 2. The releasing ratio difference between oxygen and carbon dioxide at different pressures and temperatures based on our previous experimental results, in the reactor effluent, water flow: 46.044 kg/h, oxygen flow: 0.448 kg/h, carbon dioxide flow: 0.836 kg/h, (a) O2 ratio in the gas, (b) CO2 ratio in the gas, (c) the ratio difference between O2 and CO2.
Figure 2. The releasing ratio difference between oxygen and carbon dioxide at different pressures and temperatures based on our previous experimental results, in the reactor effluent, water flow: 46.044 kg/h, oxygen flow: 0.448 kg/h, carbon dioxide flow: 0.836 kg/h, (a) O2 ratio in the gas, (b) CO2 ratio in the gas, (c) the ratio difference between O2 and CO2.
Processes 06 00224 g002
Figure 3. The simplified diagram of a SCWO system to increase the oxygen utilization rate.
Figure 3. The simplified diagram of a SCWO system to increase the oxygen utilization rate.
Processes 06 00224 g003
Figure 4. The simulation flow of the high-pressure water absorption for oxygen recovery.
Figure 4. The simulation flow of the high-pressure water absorption for oxygen recovery.
Processes 06 00224 g004
Figure 5. Comparisons of the ideal results calculated from the experimental solubility data and simulation results at different pressures and temperatures, (a) γO2 at P = 0.1 MPa, (b) γCO2 at P = 0.1 MPa, (c) γO2 at P = 2 MPa, (d) γCO2 at P = 2 MPa, (e) γO2 at P = 4 MPa, (f) γCO2 at P = 4 MPa, (g) γO2 at P = 6 MPa, (h) γCO2 at P = 6 MPa, (i) γO2 at P = 8 MPa, (j) γCO2 at P = 8 MPa, (k) γO2 at P = 10 MPa, (l) γCO2 at P = 10 MPa.
Figure 5. Comparisons of the ideal results calculated from the experimental solubility data and simulation results at different pressures and temperatures, (a) γO2 at P = 0.1 MPa, (b) γCO2 at P = 0.1 MPa, (c) γO2 at P = 2 MPa, (d) γCO2 at P = 2 MPa, (e) γO2 at P = 4 MPa, (f) γCO2 at P = 4 MPa, (g) γO2 at P = 6 MPa, (h) γCO2 at P = 6 MPa, (i) γO2 at P = 8 MPa, (j) γCO2 at P = 8 MPa, (k) γO2 at P = 10 MPa, (l) γCO2 at P = 10 MPa.
Processes 06 00224 g005
Figure 6. The effect of R on the performance of the high-pressure and low-pressure separators, (a1) γO2 at R = 1.5, (a2) γO2 at R = 2, (a3) γO2 at R = 2.5, (a4) γO2 at R = 3, (b1) βO2 at R = 1.5, (b2) βO2 at R = 2, (b3) βO2 at R = 2.5, (b4) βO2 at R = 3, (c1) γCO2 at R = 1.5, (c2) γCO2 at R = 2, (c3) γCO2 at R = 2.5, (c4) γCO2 at R = 3, (d1) βCO2 at R = 1.5, (d2) βCO2 at R = 2, (d3) βCO2 at R = 2.5, and (d4) βCO2 at R = 3.
Figure 6. The effect of R on the performance of the high-pressure and low-pressure separators, (a1) γO2 at R = 1.5, (a2) γO2 at R = 2, (a3) γO2 at R = 2.5, (a4) γO2 at R = 3, (b1) βO2 at R = 1.5, (b2) βO2 at R = 2, (b3) βO2 at R = 2.5, (b4) βO2 at R = 3, (c1) γCO2 at R = 1.5, (c2) γCO2 at R = 2, (c3) γCO2 at R = 2.5, (c4) γCO2 at R = 3, (d1) βCO2 at R = 1.5, (d2) βCO2 at R = 2, (d3) βCO2 at R = 2.5, and (d4) βCO2 at R = 3.
Processes 06 00224 g006
Figure 7. The effect of feed concentration on the performance of the high-pressure and low-pressure separator, (a1) γO2 at ω = 2 wt%, (a2) γO2 at ω = 4 wt%, (a3) γO2 at ω = 6 wt%, (a4) γO2 at ω = 8 wt%, (a5) γO2 at ω = 10 wt%, (b1) βO2 at ω = 2 wt%, (b2) βO2 at ω = 4 wt%, (b3) βO2 at ω = 6 wt%, (b4) βO2 at ω = 8 wt%, (b5) βO2 at ω = 10 wt%, (c1) γCO2 at ω = 2 wt%, (c2) γCO2 at ω = 4 wt%, (c3) γCO2 at ω = 6 wt%, (c4) γCO2 at ω = 8 wt%, (cd) γCO2 at ω = 10 wt%, (d1) βCO2 at ω = 2 wt%, (d2) βCO2 at ω = 4 wt%, (d3) βCO2 at ω = 6 wt%, (d4) βCO2 at ω = 8 wt%, and (d5) βCO2 at ω = 10 wt%.
Figure 7. The effect of feed concentration on the performance of the high-pressure and low-pressure separator, (a1) γO2 at ω = 2 wt%, (a2) γO2 at ω = 4 wt%, (a3) γO2 at ω = 6 wt%, (a4) γO2 at ω = 8 wt%, (a5) γO2 at ω = 10 wt%, (b1) βO2 at ω = 2 wt%, (b2) βO2 at ω = 4 wt%, (b3) βO2 at ω = 6 wt%, (b4) βO2 at ω = 8 wt%, (b5) βO2 at ω = 10 wt%, (c1) γCO2 at ω = 2 wt%, (c2) γCO2 at ω = 4 wt%, (c3) γCO2 at ω = 6 wt%, (c4) γCO2 at ω = 8 wt%, (cd) γCO2 at ω = 10 wt%, (d1) βCO2 at ω = 2 wt%, (d2) βCO2 at ω = 4 wt%, (d3) βCO2 at ω = 6 wt%, (d4) βCO2 at ω = 8 wt%, and (d5) βCO2 at ω = 10 wt%.
Processes 06 00224 g007
Figure 8. (a) The experimental diagram of the TWR and (b) the simplified model for the TWR in Aspen plus.
Figure 8. (a) The experimental diagram of the TWR and (b) the simplified model for the TWR in Aspen plus.
Processes 06 00224 g008
Figure 9. The Aspen Plus diagram of supercritical water oxidation system with oxygen recovery (lines and equipment with red color are specially for OR).
Figure 9. The Aspen Plus diagram of supercritical water oxidation system with oxygen recovery (lines and equipment with red color are specially for OR).
Processes 06 00224 g009
Figure 10. The treatment cost comparisons for SCWO systems with and without OR, the prices for electricity, oxygen, transpiring water and cooling water, are 0.079 $/kW·h, 100 $·t−1, 0.8 $·t−1, and 0.24 $·t−1, respectively; the manpower is 6000 $/man·year; the income for hot water and CO2 are 2.7 $·t−1 and 71.4 $·t−1, respectively.
Figure 10. The treatment cost comparisons for SCWO systems with and without OR, the prices for electricity, oxygen, transpiring water and cooling water, are 0.079 $/kW·h, 100 $·t−1, 0.8 $·t−1, and 0.24 $·t−1, respectively; the manpower is 6000 $/man·year; the income for hot water and CO2 are 2.7 $·t−1 and 71.4 $·t−1, respectively.
Processes 06 00224 g010
Figure 11. The effect of R on the treatment cost for the SCWO system with and without OR, (a) electricity consumption, (b) oxygen consumption, (c) equipment repairs and depreciation, (d) cooling water, transpiring water, and manpower consumption, (e) CO2 and hot water income, and (f) total treatment cost.
Figure 11. The effect of R on the treatment cost for the SCWO system with and without OR, (a) electricity consumption, (b) oxygen consumption, (c) equipment repairs and depreciation, (d) cooling water, transpiring water, and manpower consumption, (e) CO2 and hot water income, and (f) total treatment cost.
Processes 06 00224 g011
Figure 12. The effect of feed concentration on the treatment cost for a SCWO system with and without OR, (a) electricity consumption, (b) oxygen consumption, (c) equipment repairs and depreciation, (d) cooling water, transpiring water, and manpower consumption, (e) CO2 and hot water income, and (f) total treatment cost.
Figure 12. The effect of feed concentration on the treatment cost for a SCWO system with and without OR, (a) electricity consumption, (b) oxygen consumption, (c) equipment repairs and depreciation, (d) cooling water, transpiring water, and manpower consumption, (e) CO2 and hot water income, and (f) total treatment cost.
Processes 06 00224 g012
Table 1. Potential thermodynamic property models in Aspen Plus for the process.
Table 1. Potential thermodynamic property models in Aspen Plus for the process.
Aspen Plus Property ModelModel Name
BWR-LSBenedict-Webb-Rubin-Lee-Starling
PR-BMPeng-Robinson-Boston-Mathias
SR-POLARSchwarzentruber-Renon-POLAR
SRKSoave-Redlich-Kwong
PSRKPredictive Redlich-Kwong-Soave
RKS-BM Redlich-Kwong-Soave-Boston-Mathias
LK-PlockLee-Kesler-Plock
RK-SWSRedlich-Kwong-Soave-Wong-Sandler
PR-MHV2Peng-Robinson-MHV2
PR-WSPeng-Robinson-Wong-Sandler
RKS-MHV2Redlich-Kwong-Soave-MHV2
Table 2. Detailed parameters of the high-pressure and low-pressure parameters.
Table 2. Detailed parameters of the high-pressure and low-pressure parameters.
R αω β
(wt%)
FO2
(kg·h−1)
FCO2γ
(kg·h−1)
FH2Oδ
(kg·h−1)
P
/MPa
T
(°C)
FO2,g
(kg·h−1)
FCO2,g
(kg·h−1)
FH2O,g
(kg·h−1)
γO2
(%)
βO2
(%)
P’’
/MPa
T’’
(°C)
FCO2,l
(kg·h−1)
FO2,l
(kg·h−1)
F’’O2,g
(kg·h−1)
F’’CO2,g
(kg·h−1)
γCO2
(%)
βCO2
(%)
A11.560.4500.82537.8206–730–400.353–0.3850.122–0.21<0.01878.6–85.770.6–78.60.1200.616–0.7040.064–0.0960.064–0.0960.572–0.61668.42–73.6882.4–87.5
A2 ε2.060.9000.82539.2936–730–400.803–0.8350.254–0.340<0.01889.3–92.8676.5–80.60.1200.484–0.5720.064–0.0960.064–0.0960.44–0.52852.63–63.1680–84.62
A32.561.3500.82540.7666–730–401.252–1.2830.342–0.430<0.01892.86–95.2480–83.10.1200.396–0.4840.064–0.0960.064–0.0960.35–0.44242.10–53.6376–81.1
A43.061.8000.82542.2396–730–401.699–1.7300.386–0.474<0.01894.6–96.4383.1–85.50.1200.352–0.440.064–0.0960.064–0.0960.308–0.39636.84–47.3673–80
B12.020.3000.27534.916560–700.234–0.2660.054–0.098<0.01878–8982–860.1200.176–0.220.032–0.0640.0320.132–0.17650.00–66.6775–80
B22.040.6000.55037.105630–400.5400.112–0.156<0.01889.581–840.1200.396–0.440.0640.0640.352–0.39664.58–69.2380–82
B32.060.9000.82539.2936–730–400.800–0.8320.254–0.340<0.01889.3–92.8676.5–80.60.1200.484–0.5720.064–0.0960.064–0.0960.44–0.52852.63–63.1680–84.62
B42.081.2001.10041.4826–830–401.107–1.1420.396–0.528<0.01892.1–94.775–800.1200.572–0.7040.064–0.0960.064–0.0960.528–0.6648.00–60.0081.25–86.7
B52.0101.5001.37543.6706–830–401.408–1.4200.582–0.758<0.01893.62–95.773–77.20.1200.616–0.7920.064–0.0960.064–0.0960.572–0.74841.93–54.8482.4–88.2
α The stoichiometric oxygen excess at the reactor inlet. β the feed concentration at the reactor inlet, and corresponding feed flow Ff is 10 kg·h−1. γ the oxygen (FO2) and carbon dioxide (FCO2) flows at the reactor outlet were calculated from the completed oxidation of methanol based on the parameters of the reactor inlet. δ the water flow (FH2O) at the reactor outlet was originated from the injection of transpiring water with a transpiring intensity of 0.06 [13] and methanol oxidation product. ε A2 = B3.
Table 3. The operating parameters for the SCWO systems with and without oxygen recovery.
Table 3. The operating parameters for the SCWO systems with and without oxygen recovery.
NORω
(wt%)
Ff
(kg·h−1)
Ftw1a
(kg·h−1)
Ftw2
(kg·h−1)
Ftw3
(kg·h−1)
Fcwb
(kg·h−1)
FFinal
(kg·h−1)
Fsp2-1c
(kg·h−1)
Fsp2-2
(kg·h−1)
FO2,tot
(kg·h−1)
FO2,re
(kg·h−1)
FO2,su
(kg·h−1)
FCO2,re
(kg·h−1)
TEH1d
(°C)
TEH2
(°C)
TEH3
(°C)
Tf
(°C)
Ttw1
(°C)
Ttw2
(°C)
TM1
(°C)
Tout
(°C)
Tsp2-1
(°C)
Tsp2-2
(°C)
TM4
(°C)
COout
(%)
TOCout
/ppm
γO2
(%)
γCO2
(%)
βO2
(%)
βCO2
(%)
With
oxygen
recovery
A11.5610001857620123619,70049272956197013535.899.279.23013011813803501603603331912232040079.5673.773.8986.78
A2e2610001931644128720,00051213072204818082.197.979.23003001793803501593573311882202010091.2258.477.8982.13
A32.5610002005668133620,250530831852123225124.8100.274.82992991793813501583553301892212020092.4447.481.5678.89
A43610002078693138520,500550033002200270169.95100.0574.82982981783823501613523281902212030094.4242.184.3974.56
B12210001735578115617,5004551273118206020.6139.3922.12962961553903501503683161611831700079.268.9185.8980.21
B22410001832611122218,50048332900193312053.6466.3648.42982981653853501553633241752041870089.462.1482.3681.34
B32610001931644128720,00051213073204818082.197.979.23003001793803501593573311882202010091.2258.477.8982.13
B42810002029676135321,500539932392160240113.64126.36101.23033021943763501673523351982362140094.752.176.2084.36
Without
oxygen
recovery
C11.5610001857620123620,200484829081939135---30130118238035016136133419222420500----
C22610001931644128721,000504230252016180---30030018138035016036033319022320400----
C32.5610002005668133621,200523431402093225---29929918038135015935633018922120200----
C43610002078693138521,500542632552170270---29829818038235016135433019022220300----
D12210001735578115618,00045292717181260---29729615639035015036831616118317000----
D22410001832611122219,500478528711914120---29929816738535015536432517520418700----
D32610001931644128721,000504230252017180---30030018138035016036033319022320400----
D42810002029676135322,500529831792119240---30230219537635016835433719923721500----
aFtw1, Ftw2, and Ftw3 are the mass flows for tw1, tw2, and tw3, respectively. Fcw, and FFinal are the mass flows for cooling water and the effluent from the reactor outlet, respectively. FO2,tot, and FO2,su are the mass flows for total oxygen and supplemental oxygen, respectively. FO2,re, and FCO2,re are the mass flows recovered from the S1, respectively. b The outlet temperature of the cooling water is set as 60 °C by adjusting flow for hot water production. c The FSP2-1/FSP2-2 is kept at 1.5 for energy recovery optimization [24]. d TEH1, TEH2, and TEH3 are the outlet temperatures of feed, tw1, and tw2 in EH1, EH2, and EH3, respectively. Ttw1, Tf, and Ttw2 are the reactor inlet temperatures for tw1, feed, and tw2, respectively. Tout is the temperatures of the reactor effluent. TSP2-1, and T SP2-2 are the temperatures of the reactor effluent after cooling by HE2 and HE1, respectively. TM1, and TM4 are the mixing temperatures after M1 and M4, respectively. e A2 = B3, C2 = D3. f The Tw for reaction initiation is usually higher (380–420 °C) than that of the steady state for reaction heat releasing.
Table 4. The coefficient for each equipment.
Table 4. The coefficient for each equipment.
EquipmentK1K2K3C1C2C3B1B2FPFM
Reactor4.71160.44790.0004------4
Pump3.86960.31610.1220−0.39350.3957−0.00231.891.352.2-
Electric heater1.19791.4782−0.0958−0.016350.05687−0.00876---1.4
Compressor2.28971.3604−0.1027000--2.2-
Gas-liquid separator3.49740.44850.1074---1.491.52-1.25
Table 5. The coefficients for heat exchanger.
Table 5. The coefficients for heat exchanger.
EquipmentTemperature (°C)Pressure (MPa)MaterialδMδPδT
Heat exchanger 150030Stainless steel 316L2.91.92.1
Heat exchanger 250030Stainless steel 316L2.91.92.1
Heat exchanger 350030Stainless steel 316L2.91.92.1
Heat exchanger 430030Stainless steel 316L2.91.91.6
Table 6. Equipment investment.
Table 6. Equipment investment.
NOEquipmentParameterSCWO System with Oxygen RecoverySCWO without Oxygen Recovery
Theoretical ValueSafety Factor aDesign ValueCost ($)Theoretical ValueSafety Factor aDesign ValueCost ($)
1Heat exchanger 1Area/m25.771.2772,4125.761.2772,412
2Heat exchanger 2Area/m212.261.215121,58612.241.215121,586
3Heat exchanger 3Area/m21.1461.21.525,4031.141.21.525,403
4Heat exchanger 4Area/m219.731.224127,52222.51.227143,166
5Heat exchanger 5Area/m23.781.24.525,533--------
6Waste water pumpPower/kW11.281.214155,45211.281.214155,452
7Compressor bPower/kW36.881.660132,84036.881.660132,840
8Transpiring water pumpPower/kW41.321.250145,80041.321.250145,800
9Oxygen circulation pumpPower/kW4.592.19.521,034--------
10Transpiring wall reactorVolume/m30.69532.1531,7980.69532.1531,798
11High-pressure separatorVolume/m30.18930.67142--------
12Low-pressure separatorVolume/m30.1861.50.335700.1891.50.33570
13Electric heater 1Power/kW306.811.237031,365306.811.237031,365
14Electric heater 2Power/kW190.561.222819,380190.561.222819,380
15Total equipment cost/1996$1,420,8371,382,772
16Total equipment cost/2016$2,253,9972,193,612
17Installation cost c$338,099329,042
18Total investment cost/2016$2,592,0962,522,654
a obtained from reference [38]. b based on the power consumption in the system startup. c set as 15% of the equipment cost.
Table 7. Electricity consumption for the SCWO system.
Table 7. Electricity consumption for the SCWO system.
Rω(wt%)P1(kW) PAC(kW)P2(kW)P3(kW)PEH1(kW)PEH2(kW)Total(kW)
With oxygen recoveryA11.5611.2825.641.312.23306.81190.56577.79
A22611.2824.5342.954.59306.81190.56580.08
A32.5611.2826.1244.596.67312.89193.38594.93
A43611.2826.0546.228.99316.87196.47605.88
B12211.1811.8938.051.56361.4206.32630.4
B22411.2316.7139.702.82331.45198.15600.06
B32611.2824.5342.954.59306.81190.56580.08
B42811.3430.6643.976.45281.64182.82556.88
Without Oxygen recoveryC11.5611.2827.6641.31-302.11190.01572.37
C22611.2836.8842.95-304.24189.26583.97
C32.5611.2846.1044.59-310.19191.98604.14
C43611.2855.3246.22-315.77195.17623.76
D12211.1812.2938.05-360.40204.82626.74
D22411.2324.5939.70-329.34197.61602.47
D32611.2836.8842.95-304.24189.26583.97
D42811.3449.1843.97-277.14180.82562.45

Share and Cite

MDPI and ACS Style

Zhang, F.; Chen, J.; Su, C.; Ma, C. Energy Consumption and Economic Analyses of a Supercritical Water Oxidation System with Oxygen Recovery. Processes 2018, 6, 224. https://doi.org/10.3390/pr6110224

AMA Style

Zhang F, Chen J, Su C, Ma C. Energy Consumption and Economic Analyses of a Supercritical Water Oxidation System with Oxygen Recovery. Processes. 2018; 6(11):224. https://doi.org/10.3390/pr6110224

Chicago/Turabian Style

Zhang, Fengming, Jiulin Chen, Chuangjian Su, and Chunyuan Ma. 2018. "Energy Consumption and Economic Analyses of a Supercritical Water Oxidation System with Oxygen Recovery" Processes 6, no. 11: 224. https://doi.org/10.3390/pr6110224

APA Style

Zhang, F., Chen, J., Su, C., & Ma, C. (2018). Energy Consumption and Economic Analyses of a Supercritical Water Oxidation System with Oxygen Recovery. Processes, 6(11), 224. https://doi.org/10.3390/pr6110224

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop