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Exergy analysis and performance study for sour water stripper units, amine regenerator units and a Sulphur recovery unit of a refining plant

Abstract

A refining column in the middle east that started its official production in 2020 provides its sour wastewater from all refinery plants to two sour water units (SWS1 and SWS2) to strip H2S and NH3. Sour gas from the refinery uses a lean amine solution for gas sweetening to absorb H2S in different absorbers. Rich amine with H2S is then stripped in two amine regeneration units (ARU1 and ARU2). The overhead of SWS and ARU units provide the acid gas feed to the sulphur recovery unit (SRU) to produce sulphur and prevent any acidic emissions against environmental regulations. First, the SWS1 unit is simulated using Aspen HYSYS V.11. A complete exergy study is conducted in the unit. Exergy destruction, exergy efficiency and percentage share in the destruction are calculated for all equipment. The highest exergy destruction rate was in the stripper with 5028.58 kW and a percentage share of 81.94% of the total destruction. A comparison was conducted between the exergy results of this study with two other exergy studies performed in the same refinery plant. The columns in the three studies showed the highest destruction rates exceeding 78% of the total destruction of each unit. The air coolers showed the second-highest destruction rates in their units with a percentage share exceeding 7% of the total destruction. The pumps showed the lowest destruction rates with values of less than 1% of the total destruction of each unit. Then, an individual simulation is conducted for stripper1 of SWS1, stripper2 for SWS2, regenerator1 of ARU1 and regenerator2 of ARU2. The individual simulations are combined in one simulation named combined simulation to compute the composition of acid gas from SWS and ARU units feeding SRU. Then, the SRU unit is simulated via a special package in HYSYS V.11 named SULSIM. The computed composition from SWS and ARU is exported to excel where it is linked with SRU simulation to calculate sulphur production. For the first time in any article in the world, all data feeding SWS, ARU, and SRU units are connected to a live system named Process Historian Database (PHD) to gather live data from the plant and perform plant optimization.

Introduction

Hydrogen sulphide is a hazardous toxic, corrosive pollutant produced from refinery industry. It produces acid rain causing severe damages to equipment and also for human health [1, 2]. Hydrogen sulphide is used as feed to sulphur recovery plants (SRU) to produce elemental sulphur [3, 4]. The main purpose of SRU plants is to prevent H2S emissions against environmental regulations in the world [5,6,7,8]. The modified Claus process is the most used one to produce sulphur [9, 10].

Processed sour water produced from refinery plants contains some hazardous contaminants. H2S and ammonia are considered as the main pollutants in sour water [11,12,13]. Strippers are designed to remove H2S and NH3 from sour water [14,15,16].

The sweetening of sour gas that contains acid gas like H2S is performed in amine treating units. The gas is contacted with a lean amine solution that absorbs H2S, then the H2S is stripped from the rich amine in a regenerator [17, 18]. The diethanolamine (DEA) and methyl diethanolamine (MDEA) amines are widely used to do this role [2, 19,20,21]. When acidic gas contains CO2 and H2S, MDEA is used for its high selectivity to H2S rather than CO2 [22,23,24].

The world’s fastest expanding population leads to a dramatic increase in energy consumption [25, 26]. Optimum energy consumption is substantial for community development. Presently, from an energy point of view, optimum energy consumption is an essential indicator of the community development level. Therefore, energy optimization and preventing its losses in various industries are very important. Higher energy consumption in chemical processes increases both operation and production cost and also decreases system efficiency [27].

While energy is conserved in any chemical processes, exergy is destroyed irreversibly. Exergy is the work or power that we can use from an energy amount with respect to the natural environment. The total exergy components are potential, kinetic, chemical and physical exergy. Actually, potential and kinetic exergy is neglected due to their lower values if compared with physical and chemical exergy [10]. The chemical exergy is defined as the maximum amount of work obtained when the substance is got from an environmental state to a dead state. The process exchange of substances and heat transfer is only with the environment. The physical exergy definition is also considered as the maximum amount of work, but when the stream the substance is got from its initial state to the state of environment by physical processes. Physical exergy involves only a thermal interaction with the environment [28].

Rostami et al, Hashemi et al. and Zarei performed exergy studies on SRU plants considering the overall exergy of the SRU, the difference between individual sections and exergy study on individual equipment [10, 27, 29].

The literature study showed no remarkable study of energy and exergy analysis of amine scrubber units. Mohamadi-Baghmolaei et al. did an exergy study on different compositions of a mixture of DEA and MDEA [19]. Ibrahim et al. performed an exergy study for ARU No1 and ARU No2. As a result of system losses during start-up, the DEA concentration dropped from 25 to 20%. Exergy studies were carried out on both concentrations to determine the changes that occurred in the various exergy calculations [30, 31]. Also, they conducted an exergy study for an MDEA scrubber unit of an SRU plant. As a result of system losses during start-up, the DEA concentration dropped from 45 to 22%. Exergy studies were carried out on both concentrations to determine the changes that occurred in the various exergy calculations [32].

The current SWS No.1 study results were compared with ARU No.1 results and MDEA scrubber unit results to conclude the relationships between similar equipment. The literature survey showed that no remarkable studies were performed on the exergy of SWS units or ARU units, and also, no studies were done before considering the interactions between SWS, ARU and SRU units. Ibrahim et al. carried out an energy optimization analysis on the same refinery plant to conserve steam from the SWS1, SWS2, ARU1 and ARU2 units. The research saved $1,537,206.38/year [33].

An SRU unit of a refinery plant that started its official production in 2020 receives an acid gas feed from four units, sour water stripping unit1 (SWS1), sour water stripping unit2 (SWS2), amine regenerated unit1 (ARU1) and amine regenerated unit2 (ARU2). The sour water stripping units will process the sour water coming from all refining plants.

The function of the SWS is to remove hydrogen sulphide and ammonia from the sour water streams. The amine regeneration units are capable to strip hydrogen sulphide (H2S) from “rich” amine solution to provide “lean” amine solution. LA is used to treat sour gas of all refinery plants in different absorbers. RA saturated by absorbed H2S from different units is then treated in ARU units to provide LA. The sulphur recovery unit (SRU) is designed to recover sulphur from amine acid gas and sour water stripper acid gas. Sulphur product purity shall be 99.9% on a dry basis and produced as solid sulphur.

A complicated simulation is performed by the HYSYS software V.11. The simulation is validated with plant data to check its ability for study accuracy. The SWS1 was completely simulated, and a complete exergy study is done on the process equipment to see the exergy of streams, the exergy destruction in equipment, the percentage share of destruction and the overall destruction efficiency. These current exergy research from around the world will help to reduce exergy losses in process systems and will be an effective strategy for energy optimization.

Another combined simulation is performed for stripper1 of SWS1 unit, stripper2 of SWS2 unit, regenerator1 of ARU1 and regenerator2 of ARU2. The overhead acid gas of the 4 towers represents the feed to the SRU plant. The combined simulation computes the composition inlet to SRU from SWS and ARU units. An AAG analyser exists in the SRU plant, but it seems to give a wrong composition. While the estimated composition is around 90% AAG, it gives 60% mole fraction reading. No analyser exists to measure the SWSAG composition. The simulation was mandatory to compute the actual sulphur production.

The calculated composition is exported to Excel. The SRU plant was also simulated with HYSYS V.11 by a special sulphur package named SULSIM. The calculated composition in Excel is exported to the SRU simulation to compute sulphur production and to test other parameters. Feed rates to the combined simulation and the SRU plant receive live data from a system named Process Historian Database (PHD) that gathered all plant data instantly. Literature survey did not find any research about connecting a PHD live system with Excel, HYSYS and other different simulations because this type of simulation is complicated and require a live system in the companies that can connect the live plant data to Excel and then data are transferred from Excel to HYSYS. This system does not exist in all companies. The integration of simulations with PHD systems is a powerful tool for plant optimization.

Methods

Simulation step

The software used in the simulation is HYSYS V.11. The simulation is a complicated one composed of a series of simulations connected together. The feed characteristics of strippers1 and stripper2 are presented in Table 1. The main components of sour water to stripper1 and stripper2 are water, ammonia and hydrogen sulphide.

Table 1 Sour water feed characteristics to stripper1 and stripper2

The feed characteristics of regenerator1 and regenerator2 are presented in Table 2. The main components of the RA solution feed to regenerator1 and regenerator2 are diethanolamine, water and hydrogen sulphide. No ammonia exists in the RA feed.

Table 2 Sour water feed characteristics to regenerator1 and regenerator2

Simulation sections

Simulation and process description of SWS1

This simulation is the simulation of the SWS1 whole plant. The output from the simulation is presented in Fig. 1 and can be considered as a PFD for SWS1 plant. The SWS1 and SWS2 units are designed to treat process water contaminated with hydrogen sulphide (H2S) and ammonia (NH3). The sour water is generated from all the refinery process units. Sour water is heated in E-1, and then H2S and NH3 are stripped from the water in the stripper. The stripped water is cooled in E-1, then in an air cooler and divided into two streams: wash water stream used in refining units and wastewater stream. A detailed exergy study is conducted on this one.

Fig. 1
figure 1

Sour water stripper1 plant

Simulation criteria of SWS1

The package selected for the plant is Peng Robinson, a wrong selection for the package deviates totally the results. The stripper is selected as a distillation tower with some modifications in the column environment, a pump around is selected to cool the overhead of the tower instead of the condenser to meet the design of the tower. Exchanger 1 and exchanger 2 are selected as normal heat exchangers, and the air cooler is selected from HYSYS to simulate the air cooler.

Simulation and process description of combined towers

This simulation actually is composed of five simulations; the first four simulations for 4 different towers are built up separately, stipper1 for SWS1, stripper2 for SWS2, regenerator1 for ARU1 and regenerator2 for ARU2. The fifth simulation combines the four towers together.

Sour water stripper is designed to produce stripped water with a normal sour water flow rate. Also, it minimizes H2O contents in sour gas from stripper overhead with a condenser system. The stripped water contains 3 wt. ppm H2S and 30 wt. ppm NH3. It has a pump around the system as a column condenser. The advantage of a pump-around system is to reduce overhead plugging and corrosion potential. The simulation of stipper1 represents its PFD and extracted from the column environment of the tower. Stripper1 simulation is shown in Fig. 2. The column environment of the strippers gives a clear view of the strippers’ equipment. The pump around the cooler does not appear in the main environment.

Fig. 2
figure 2

Stripper1

Stripper1 and stripper2 reboilers supply heat to the strippers to strip the hydrogen sulphide and ammonia from the sour water. The simulation of stipper2 is also extracted from the column environment and shown in Fig. 3. The pump around the coolers is the source of cooling at the top of the stripping towers.

Fig. 3
figure 3

Stripper2

Regenerator1 simulation is shown in Fig. 4. The hydrogen sulphide (H2S) is stripped off from the rich amine solution as it flows downward through the regenerator. Regenerator1 and regenerator2 reboilers supply the heat to the regenerators to strip H2S off from the rich amine solution. The condenser is the source of cooling of overhead acid gas to SRU.

Fig. 4
figure 4

Regenerator1

Regenerator2 is also simulated as regenerator1 and shown in Fig. 5. The design of regenerator2 is also similar to regenerator1 for the reboiler and condenser.

Fig. 5
figure 5

Regenerator2

All distillation towers in general need some information in the simulation to solve as the number of trays, the feed tray location, the top temperature and the bottom temperature. The columns also use some specifications: we select the following examples: the reflux rate, the top and the bottom product rates and the top or bottom component fractions. A pump around is added for stripper1 and stripper2, and some modifications are made in the column environment. Regenerator1 and regenerator2 are simulated as normal distillation towers.

Finally, the fifth simulation of the combined towers is shown in Fig. 6. This simulation is composed of four templates for the four towers in the addition to the main simulation. The combined tower simulation contains four templates for the four towers; the overheads from stripper1 and stripper2 (streams 111 and 211) are combined together as acid gas feed to SRU from the SWS units. The overheads from regenerator1 and regenerator2 are combined together (streams 153 and 223) as AAG feed to SRU. AAG drum and SWSAG drums are used to remove any condensates from the gas feed to SRU.

Fig. 6
figure 6

Combined towers

Simulation and process description of Sulphur recovery unit

The SRU simulation is done by HYSYS V.11 with the Sulphur Sulsim package prepared especially for sulphur units and shown in Fig. 7. The sulphur recovery facilities consist of Claus section, sulphur degassing, TGT section and incineration section. The Claus section consists of the thermal Claus section and the catalyst Claus section. The Claus process is used on acid gas streams containing essentially H2S and ammonia. The concept of the process is that one-third of the H2S contained in the acid gas feed is transformed into SO2 in the thermal Claus section. SO2 reacts with the remaining two-thirds of H2S to form sulphur in the catalyst Claus section. Tail gas treatment unit (TGTU) treats Claus tail gas to convert SO2 into H2S. The converted H2S is cooled and then absorbed by lean amine then recycled for reprocessing.

Fig. 7
figure 7

SRU simulation

The liquid sulphur produced in the SRU contains soluble H2S and H2Sx (hydrogen polysulphides). During sulphur conveyance and handling, the presence of H2S in the liquid could cause safety and environmental problems due to its toxicity and explosion hazards. Therefore, liquid sulphur is degassed in order to reduce the H2S content at the safety value of 10 ppm by weight. The incineration of the tail gas produced in the Claus and TGT units is necessary to transform all sulphured compounds present into SO2. The flue gas produced in the incineration is discharged to the atmosphere via a stack. A detailed description of the simulation with a case study is prepared in another article with the name Performance assessment and process optimization of a sulphur recovery unit: a real starting up plant. The amine regenerator section in the SRU is simulated in another article where a complete exergy study is conducted with actual case studies with the name (Exergy study of amine scrubber unit using MDEA in a refinery sulfur recovery unit: a real starting up plant).

Validation step

The simulated results are compared with plant data for validation. The validation streams concentrate on SWSAG to SRU and AAG to SRU streams as these are the combined streams from the towers. Low percentage deviation exists. The validation criteria required a comparison of the chosen simulated streams to plant data. The simulations’ success is dependent on the low percentage deviation between simulated streams and plant data.

Exergy calculations

The exergy analysis is done for SWS1 plant. The physical and chemical exergy are calculated based on the following equations:

Physical exergy = (H − H0) − T0(S − S0) (1)

Chemical exergy =  ∑ xiex0che + RT0 ∑ xi ln xi (2)

Destruction exergy =  ∑ miei −  ∑ meee (3)

where xi is the mole fraction of specie i in the mixture, and ex0che is the standard chemical exergy found directly from tables or calculated through methods [27].

The terms of H, T, S and R stands for enthalpy, temperature, entropy and global constant of gases, respectively. Term 0 represents the standard conditions of the species.

We did not neglect chemical exergy due to its higher value in comparison with physical exergy.

Eph = m ˙ eph (4)

Ech = m ˙ ech (5)

The sum of the physical and chemical exergy of each stream represents the total exergy of the stream.

E = Eph + Ech (6)

A term in exergy is called exergy efficiency of the system. It is defined as the ratio between the value of the outlet exergy to the value of the inlet exergy, while the exergy efficiency of the whole system is the percentage of inlet exergy that is converted to outlet 1 in the system [10, 27,28,29].

Exergy destruction calculation for equipment of SWS1 unit

The exergy destruction calculations are performed based on the equations in Table 3.

Table 3 Exergy destruction for SWS1 equipment

Composition calculations for SRU feed streams

The SRU feed is composed of SWS acid gas and ARU acid gas; both composition streams are calculated from the combined simulation shown in Fig. 6.

Calculation of the SRU production capacity

The output calculated composition from the combined towers simulation is exported to Excel, then Excel export the calculated composition to SRU simulation to calculate the SRU sulphur production capacity. We can explain the calculation from the beginning: the feed to all towers is first exported from a PHD system to export live data to an Excel file, then the live data are exported to combined tower simulation from Excel to calculate the composition of streams inlet to SRU plant. The feed to the SRU plant is imported from the PHD live system to calculate the capacity.

Steps for linkage excel with HYSYS

From the Aspen Simulation Workbook inside Excel, select enable (to enable the connection between Excel and HYSYS), then select the “add button” and search your HYSYS case from the PC, so the name of the HYSYS case will appear on the bar beside the add button. Select “connect” and wait until the connection ends, and the simulation connection will appear. Click “visible”, the HYSYS simulation will open from Excel, and no need to open the case from HYSYS. Now, we need to add any variable from HYSYS to Excel, and after that, any changes in Excel will reflect in HYSYS. From HYSYS, select the value of any variable and copy it (for example, the inlet temperature of a feed stream). Go to Excel and select organizer (the glass shape from Aspen Simulation Workbook). Select model variable and just paste it in the model variable. The temperature will appear inside the model variable. Right-click the temperature and select “create table”. Select a cell in the Excel sheet to show your temperature variable inside excel. The value of the temperature will appear in Excel in the form of a table. Change the temperature now inside Excel; it will be changed in HYSYS automatically. If you have a system like PHD talks the data life of the plant, you can make the temperature cell gathering the data directly and this will reflect in HYSYS.

Steps of using the simulation with actual live plant process data

The simulations are validated first by comparing them to plant PFD data. Following the success of the simulation, the Process Historian Data (PHD) system is linked to Excel with actual plant units, such as m3/h instead of kg/h as the unit measurement, and then Excel is linked to HYSYS simulation as described with the actual plant units.

Example 1: Using SWS dynamic units

The feed tag numbers are written in the Excel file used to enter the feed data of the SWS units as stored in the PHD system, as shown in Table 4.

Table 4 SWS tag names in the PHD system

The new dynamic feed is linked to the validated simulation, as given in ‘Composition calculations for SRU feed streams’ and the combined simulation computes the composition out from the SWS and ARU units to the SRU, as specified in ‘Exergy Calculations’.

Example 2: Using SRU dynamic units

The feed tags numbers are entered as saved in the PHD system with actual units Nm3/h in the Excel file used to enter the feed data from the SWS units and the ARU units to the SRU, as illustrated in Table 5. The actual dynamic live data is linked to the HYSYS SRU validated model, and the new feed values with Nm3/h reset the validated feed values with kg/h, and the SRU simulation computes the sulphur production in kg/h.

Table 5 Actual SRU dynamic units

Results and discussion

Validation results

The validation concentrates on two main streams (the SWS AG inlet to SRU, and the AAG inlet to SRU) because these streams reflect the accuracy for all the simulations of the combined model. The validation results are shown in Table 6.

Table 6 Validation results

Exergy calculations

Physical and chemical exergy calculations for streams

The physical and chemical exergy calculations for streams are calculated based on the equations of ‘Simulation and process description of Sulphur recovery unit; HYSYS calculated molar flow rates, mass flow rates and mass exergy for streams are presented in Table 7.

Table 7 HYSYS calculations for streams

The physical exergy, chemical exergy and total exergy for the streams were calculated using the equations in ‘Simulation and process description of Sulphur recovery unit’ and listed in Table 8.

Table 8 Streams exergies

The total exergy of some streams is higher than other streams. For example, Etot for stream 111 is 15,173.82 kW while Etot for stream 125 is 870.03 kW. The purpose is described in the following: The total exergy was the summation of the physical and chemical exergy values. Usually, the chemical exergy value is extremely higher than the physical exergy values, so it is the main influencer of Etot values. The composition of the components had the main effect on the Ech value calculated using the equation ∑ xiex0che + RT0xi ln xi. The ex0che values of components are the main influencer of the Ech value. Stream 111 is composed of 0.501 wt.-Fr. H2S, 0.231 NH3 and the remaining is water. Stream 125 is approximately 100% water. The H2S standard chemical exergy and the NH3 standard chemical exergies were much higher than that of water. The ex0che values for H2S, NH3 and H2OL are 812.00 kJ/mol, 337.90 and 0.90 kJ/kmol, respectively. Consequently, the chemical exergy at stream 111 was much higher than that of stream 225; consequently, Etot for stream 111 is higher than Etot for stream 125.

The values for Q_P, Q_Reboiler and Q_Cooler were 31.8, 10,560 and 3839 kW, respectively. These values were used in the destruction calculations for the equipment, as listed in Table 3. Usually, the chemical exergy magnitude is higher than that for the physical exergy in most streams as shown in Table 8.

Exergy destruction and exergy efficiency of equipment

Exergy destruction calculations of equipment are calculated based on the equations in Table 3; exergy efficiencies of equipment and percentage share of destruction are calculated based on Section 2.4 and presented in Table 9.

Table 9 Exergy destruction and exergy efficiency results

The highest destruction rate is observed in stripper with a value of 5028.58 kW and a percentage share of 81.06% of the total destruction, then air cooler with a value of 627.98 kW and a percentage share of 10.12% of the total destruction. The percentage share of destruction is shown in Fig. 8. The overall efficiency of exergy is 89.71%.

Fig. 8
figure 8

Percentage share of equipment

Table 10 represents the standard chemical exergy values for the components used in the study. The H2S has the highest value of 812.00 kJ/mol, then NH3 with a value of 337.90 kJ/mol. It is important to know that the standard chemical exergy value of H2O(L) is different from H2O(V). It is mandatory to check the actual status of water to select the proper value of ex0che.

Table 10 Standard chemical exergy values for the components used in the study

Standard chemical exergy values for the components were used in the study [29].

Exergy results comparison with ARU1 and MDEA scrubber study

Ibrahim et al. performed an exergy study of the amine scrubber unit of the SRU plant on different equipment. MDEA is used in this unit. The study was conducted on two different concentrations (45% and 22%) by weight.

Also, they performed an exergy study of one of the two ARU units of the plant. DEA is regenerated in this unit. The DEA concentration decreased from the design concentration 25 to 20% wt.% due to system losses. The design concentration value of the amine is set by the licensor of the process to guarantee that the amine will perform efficiently for H2S gas sweetening. The decrease in this concentration due to any purposes may lead also to other severe problems.

System losses in general for amine may happen due to many purposes explained in ‘Purposes of amines losses’. The study was conducted on two different concentrations (25% and 20%) by weight. A comparison was conducted between the similar equipment of the current study and the previous two studies to conclude the similar relationships between equipment [30, 31].

Columns comparison

It was observed that the main highest exergy destruction in the three units was in the columns (regenerators and stripper). Table 11 shows the tower values in the three units and the percentage share of these values in total unit destructions.

Table 11 Comparison between columns destructions in three units

It was observed that the columns in the three units have the highest destruction rate. All destruction rate values of the columns exceed 78% of the total destruction of the units [29, 30].

Air coolers comparison

The air coolers exist in ARU and SWS. The air coolers in their units have the second-highest destruction rates and percentage shares in destruction as shown in Table 12. The destruction values exceed 7% in the two units [30, 32].

Table 12 Comparison between air coolers destructions in two units

Pumps comparison

The pumps in the three units have the lowest percentage share in the destruction of the units. Table 13 shows the comparison between pump destructions in three units. The pumps have a contribution low than 1% in three units [30, 32].

Table 13 Comparison between pumps destructions in three units

Purposes of amine losses

The decrease in amine concentration in plants is due to process losses. The concentration of the amine can decrease during the start-up phase for three reasons: amine degradation, foaming and flooding. Amines are converted into undesirable products during the degradation process, which is not recoverable by normal regeneration. Amines may be degraded for a variety of reasons. The make-up water used to prepare the Amine solution is one of these purposes. Suspended solids, nonvolatile substances, lower and higher molecular weight hydrocarbon, additives and antifoaming agents, corrosion inhibitor, make-up water and water impurities, and inorganic and organic acids are some of the other purposes. Flushing and cleaning procedures, such as degreasing, must be performed before the start-up of any plant. In a lot of instances, it is not done correctly. Unwanted compounds are present, particularly during start-up if there is a problem with the unit’s cleaning. As a result, a large number of these pollutants are present in the system, causing amine degradation. One of the concerns about amine degradation is foaming. Foaming allows a portion of the amine to escape from the top of the tower rather than the bottom, resulting in MDEA loss and a decline in concentration. Other degradation issues include reduction solution capability and plant efficiency, corrosion effect of degradation products, capital/material issues, the environmental effect of degradation products and the fouling effect of degradation products. The flooding phenomenon, which occurs at high sour gas feed flow rates and causes a portion of the DEA or MDEA to exit with the sweet gas from the top, is the third explanation for the decrease in concentration. Foaming and flooding phenomena in the plant absorbers were observed many times during the start-up process [30, 34].

Sulphur production calculation results

Sulphur production is calculated from the SRU simulation. The calculated composition for SWSAG to SRU, and AAG to SRU from the combined simulation is exported to Excel, then they are connected to HYSYS as explained in ‘Composition calculations for SRU feed streams’. Table 14 shows the computed SWS AG and AAG compositions.

Table 14 Computed SWS AG and AAG mole fraction from the combined model

It was observed that the upsets in temperature upstream the amine drain drum strongly affects the sulphur production. Table 15 shows the sulphur production at different temperatures. The normal temperature is 55 °C, while the purpose of deviations in temperatures is process upsets.

Table 15 Sulphur production versus AAG to amine drum stream temperature

The production is affected due to the vaporization of more water in the top of the stream decrease the mole fraction of H2S which is the source of sulphur product. Table 16 presents this variation.

Table 16 AAG composition at different inlet temperatures to SRU

Conclusions

A refinery plant in the Middle East that started its official production in 2020 has an SRU plant to recover sulphur from H2S with 99.9% SRE. The acid gas feed containing mainly H2S and NH3 to the SRU plant is provided from SWS1, SWS2, ARU1 and ARU2 units. First, a complete exergy study was conducted on SWS1.

The destruction rate of all equipment was calculated. It was observed that the highest destruction rate was in the stripper with a destruction rate of 5028.58 kW and a percentage share of 81.06% of the total destruction. The stripper exergy efficiency was 81.94%. The air cooler showed the second-highest one with a destruction rate of 627.98 kW and a percentage share of 10.12% of the total destruction. The exergy efficiency of the air cooler was 76.18%.

We must evaluate the exergy from two points of view: the first one is the destruction rate, and the second one is the exergy efficiency. Although the destruction rate of the stripper is higher than the air cooler, its exergy efficiency is higher. The overall exergy efficiency of the SWS1 process is 89.75%.

The SWS1 exergy study results were compared by the study of two other units in the same refinery plant (the amine scrubber unit of SRU and an amine regenerator unit). It was observed that the main highest exergy destruction in the three units was in the columns (regenerators and stripper) with a percentage share values exceeding 78% of the total destruction of each unit. The air coolers existing in SWS and ARU units slowest the second-highest destruction rates with values exceeding 7% of the total destruction of their units. The pumps in the three units have the lowest percentage share in the destruction of the units with a contribution low than 1% of the total destruction in the three units. These recent exergy studies from around the world will help to reduce exergy losses in process systems.

Four columns are simulated individually and combined in one simulation (stripper1, stripper2, regenerator1 and regenerator2) for SWS1, SWS2, ARU1 and ARU2, respectively. The computed composition for SWS acid gas feeding the SRU in normal operation was 0.36 mole fraction H2O, 0.37 mole fraction NH3 and 0.27 mole fraction H2S. While the computed composition for ARU acid gas feeding the SRU in normal operation was: 0.09 mole fraction H2O and 0.91 mole fraction H2S and 0 mole fraction NH3. The sulphur production in normal conditions was 253.56 tons/day. During upsets, the sulphur production is strongly affected by variation of AAG temperature inlet to SRU plant.

Nomenclature

e:

specific exergy

E:

exergy rate

ε:

exergy efficiency

H:

enthalpy

m˙:

mass rate

S:

entropy

T:

temperature

R:

Gas constant

Subscripts

che:

chemical

e:

exit

i:

Inlet, specie in a mixture

0:

Standard conditions

Superscripts

ch:

chemical

ph:

physical

0:

Standard conditions

Availability of data and materials

All the data required are included in the manuscript.

Abbreviations

AAG:

Amine acid gas

AG:

Acid gas

ARU:

Amine regeneration unit

CW:

Cooling water

DEA:

Diethanolamine

E:

Exchanger

Eq:

Equation

LA:

Lean amine

MDEA:

Methyl diethanolamine

P:

Pump

PC:

Personal computer

PFD:

Process flow diagram

PHD:

Process Historian Database

RA:

Rich amine

SRE:

Sulphur recovery efficiency

SRU:

Sulphur recovery unit

SWS:

Sour water stripping

SWSAG:

Sour water stripping acid gas

TG:

Tail gas

TGTU:

Tail gas treatment unit

wt.:

Weight

References

  1. Khatami A, Heidari Y, Safadoost A, Aleghafouri A, Davoudi M (2016) The activity loss modeling of catalytic reactor of sulfur recovery unit in south pars gas complex (SPGC) 3rd refinery based on percolation theory. Journal of Natural Gas Science and Engineering 28:723–736. https://doi.org/10.1016/j.jngse.2015.08.059

    Article  Google Scholar 

  2. Abdolahi-Mansoorkhani H, Seddighi S (2019) H2S and CO2 capture from gaseous fuels using nanoparticle membrane. Energy 168:847–857. https://doi.org/10.1016/j.energy.2018.11.117

    Article  Google Scholar 

  3. Mahmoodi B, Hosseini SH, Ahmadi G, Raj A (2017) CFD simulation of reactor furnace of sulfur recovery units by considering kinetics of acid gas (H2S and CO2) destruction. Appl. Therm. Eng. 123:699–710. https://doi.org/10.1016/j.applthermaleng.2017.05.148

    Article  Google Scholar 

  4. Abdoli P, Hosseini SA, Mujeebu MA (2019) Effect of preheating inlet air and acid gas on the performance of sulfur recovery unit—CFD simulation and validation. Forsch. Ingenieurwes. 83(1):81–89. https://doi.org/10.1007/s10010-019-00299-9

    Article  Google Scholar 

  5. Lavery CB, Marrugo-Hernandez JJ, Sui R, Dowling NI, Marriott RA (2019) The effect of methanol in the first catalytic converter of the Claus sulfur recovery unit. Fuel 238:385–393. https://doi.org/10.1016/j.fuel.2018.10.128

    Article  Google Scholar 

  6. Sui R, Lavery CB, Li D, Deering CE, Chou N, Dowling NI, Marriott RA (2019) Improving low-temperature CS2 conversion for the Claus process by using La (III)-doped nanofibrous TiO2 xerogel. Appl. Catal. B Environ. 241:217–226. https://doi.org/10.1016/j.apcatb.2018.09.027

    Article  Google Scholar 

  7. Ibrahim S, Rahman RK, Raj A (2017) Effects of H2O in the feed of sulfur recovery unit on sulfur production and aromatics emission from Claus furnace. Ind. Eng. Chem. Res. 56(41):11713–11725. https://doi.org/10.1021/acs.iecr.7b02553

    Article  Google Scholar 

  8. Ibrahim A, Y. (2021) Performance assessment of a Sulphur recovery unit. Petroleum and Petrochemical Engineering Journal. 5(1)

  9. Ibrahim A, Y. (2021) Performance monitoring of a Sulphur recovery unit: a real startup plant. Petroleum and Petrochemical Engineering Journal. 5(1)

  10. Rostami A, Tavan Y (2019) A survey on exergy, energy and environmental analysis of sulfur recovery unit in case of five intensified configurations. Chem. Pap. 73(6):1529–1539. https://doi.org/10.1007/s11696-019-00705-0

    Article  Google Scholar 

  11. Minier-Matar J, Janson A, Hussain A, Adham S (2017) Application of membrane contactors to remove hydrogen sulfide from sour. J. Membr. Sci. 541:378–385. https://doi.org/10.1016/j.memsci.2017.07.025

    Article  Google Scholar 

  12. Gai H, Chen S, Lin K, Zhang X, Wang C, Xiao M, Huang T, Song H (2020) Conceptual design of energy-saving stripping process for industrial sour water. Chin. J. Chem. Eng. 28(5):1277–1284. https://doi.org/10.1016/j.cjche.2019.12.020

    Article  Google Scholar 

  13. Dardor D, Janson A, AlShamari E, Adham S, Minier-Matar J (2019) The effect of hydrogen sulfide oxidation with ultraviolet light and aeration. Sep. Purif. Technol. 236:116262

    Article  Google Scholar 

  14. Zahid Z (2019) Techno-economic evaluation and design development of sour water stripping system in the refineries. J. Clean. Prod. 236:117633. https://doi.org/10.1016/j.jclepro.2019.117633

    Article  Google Scholar 

  15. Zhu M, Sun L, Ou G, Wang K, Wang K, Sun Y (2016) Erosion corrosion failure analysis of the elbow in sour water stripper overhead condensing reflux system. Eng. Fail. Anal. 62:93–102. https://doi.org/10.1016/j.engfailanal.2016.01.002

    Article  Google Scholar 

  16. Hassan-Beck H, Firmansyah T, Suleiman MI, Matsumoto T, AL-Musharfy M, Chaudry A, Abdur-Rakiba M (2019) Failure analysis of an oil refinery sour water stripper overhead piping loop: assessment and mitigation of erosion problems. Eng. Fail. Anal. 96:88–99. https://doi.org/10.1016/j.engfailanal.2018.09.035

    Article  Google Scholar 

  17. Amini J, Davoodi A, Jafari H (2018) Analysis of internal cracks in type 304 austenitic stainless steel cladding wall of regenerator column in amine treating unit. Eng. Fail. Anal. 90:440–450. https://doi.org/10.1016/j.engfailanal.2018.04.028

    Article  Google Scholar 

  18. Wang M, Hariharan S, Shaw R, A. & Hatton, T., A. (2019) Energetics of electrochemically mediated amine regeneration process for flue gas CO2 capture. International Journal of Greenhouse Gas Control 82:48–58. https://doi.org/10.1016/j.ijggc.2018.12.028

    Article  Google Scholar 

  19. Mohamadi-Baghmoleaei M, Hajizadeh A, Zahedizadeh P, Azin R, Zendehboudi S (2020) Evaluation of hybridized performance of amine scrubbing plant based on exergy energy, environmental, and economic prospects: a gas sweetening plant case study. Energy 31:118715

    Google Scholar 

  20. Pashaei H, Ghaemi A (2020) CO2 absorption into aqueous diethanolamine solution with nano heavy metal oxide particles using stirrer bubble column: hydrodynamics and mass transfer. Journal of Environmental Chemical Engineering 8(5):104110. https://doi.org/10.1016/j.jece.2020.104110

    Article  Google Scholar 

  21. Aghel B, Sahraie S, Heidaryan E (2019) Carbon dioxide desorption from aqueous solutions of monoethanolamine and diethanolamine in a microchannel reactor. Sep. Purif. Technol. 237:116390

    Article  Google Scholar 

  22. Concepción EI, Moreau A, Martín MC, Vega-Maza D, Segovia JJ (2020) Density and viscosity of aqueous solutions of methyldiethanolamine (MDEA) + diethanolamine (DEA) at high pressures. J. Chem. Thermodyn. 148:106141. https://doi.org/10.1016/j.jct.2020.106141

    Article  Google Scholar 

  23. Shunji K, Xizhou S, Wenze Y (2020) Investigation of CO2 desorption kinetics in MDEA and MDEA+DEA rich amine solutions with thermo-gravimetric analysis method. International Journal of Greenhouse Gas Control 95:102947. https://doi.org/10.1016/j.ijggc.2019.102947

    Article  Google Scholar 

  24. Pal P, AbuKashabeh A, Al-Asheh S, Banat F (2015) Role of aqueous methyldiethanolamine (MDEA) as solvent in natural gas sweetening unit and process contaminants with probable reaction pathway. Journal of Natural Gas Science and Engineering 24:124–131. https://doi.org/10.1016/j.jngse.2015.03.007

    Article  Google Scholar 

  25. Mores P, Scenna N, Mussati S (2012) CO2 capture using monoethanolamine (MEA) aqueous solution: modeling and optimization of the solvent regeneration and CO2 desorption process. Energy 45(1):1042–1058. https://doi.org/10.1016/j.energy.2012.06.038

    Article  Google Scholar 

  26. Yang H, Xu Z, Fan M, Gupta R, Slimane RB, Bland AE, Wright I (2008) Progress in carbon dioxide separation and capture: a review. J. Environ. Sci. 20(1):14–27. https://doi.org/10.1016/S1001-0742(08)60002-9

    Article  Google Scholar 

  27. Hashemi M, Pourfayaz, F.& Mehrpooya, M. (2019) Energy, exergy, exergoeconomic and sensitivity analyses of modified Claus process in a gas refinery sulfur recovery unit. J. Clean. Prod. 220:1071–1087. https://doi.org/10.1016/j.jclepro.2019.02.213

    Article  Google Scholar 

  28. Kotas, T., J (1985) The exergy method of thermal plant analysis, Butterworths.

  29. Zarei S (2019) Exergetic, energetic and life cycle assessments of the modified Claus process. Energy 191:116584

    Article  Google Scholar 

  30. Ibrahim AY, Ashour FH, Gadallah MA (2021) Exergy study of amine regeneration unit using diethanolamine in a refinery plant: a real start-up plant. Heliyon 7:2

    Google Scholar 

  31. Ibrahim, A. Y., Ashour, F. H., Gadallah, M. A. (2021). Exergy study of amine regeneration unit for diethanolamine used in refining gas sweetening: a real start-up plant. Alexandria Engineering Journal.

    Google Scholar 

  32. Ibrahim, A. Y., Ashour, F. H., Gadallah, M. A. (2021). Exergy study of amine scrubber unit of a sulphur recovery plant using methyl diethanolamine: a real starting up plant, petroleum and coal, 63(1): 155-165.

  33. Ibrahim AY, Ashour FH, Gadallah M (2021) Refining plant energy optimization. Alexandria Engineering Journal 60:4593–4606

    Article  Google Scholar 

  34. Islam MS, Yusoff R, Ali B, S. (2010) Degradation studies of amines and alkanolamines during CO2 absorption and stripping system. Engineering e-Transaction 5:97–109

    Google Scholar 

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Acknowledgements

The authors would like to thank all refinery company team and process engineering team for the support by data availability and shared ideas.

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A.Y.I, F.H.A and M.A.G have made substantial contributions to the conception design of the work; the acquisition, analysis and interpretation of the data and the creation of new software used in the work; have drafted the work or substantively revised it; have approved the submitted version (and any substantially modified version that involves the author’s contribution to the study); have agreed both to be personally accountable for the author’s own contributions; and have ensured that questions related to the accuracy or integrity of any part of the work, even ones in which the author was not personally involved, are appropriately investigated and resolved, and the resolution documented in the literature. All authors have read and approved the final manuscript and ensure that this is the case.

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Ibrahim, A.Y., Ashour, F.H. & Gadalla, M.A. Exergy analysis and performance study for sour water stripper units, amine regenerator units and a Sulphur recovery unit of a refining plant. J. Eng. Appl. Sci. 68, 6 (2021). https://doi.org/10.1186/s44147-021-00006-y

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