Optimization of Power-Intensive Energy Systems with Carbon Capture

ARTICLE pubs.acs.org/IECR

Optimization of Power-Intensive Energy Systems with Carbon Capture Xuesong Zheng†,§ and Jin-Kuk Kim*,‡ †

Centre for Process Integration, School of Chemical Engineering Analytical Science, The University of Manchester, Oxford Road, Manchester, M13 9PL, U.K. ‡ Department of Chemical Engineering, Hanyang University, 17, Haengdang-dong, Seongdong-gu, Seoul, Republic of Korea, 133-791 ABSTRACT: A systematic methodology for the synthesis of power systems has been developed, which explores the interactions among the equipment as well as the processes in power and utility systems. Also, the optimization is able to study the integration of CO2 capture processes with power systems for minimizing site-wide fuel consumption. Typical operating conditions for precombustion as well as postcombustion CO2 capture have been applied to estimate energy demand within the CO2 capture process. The power system is designed not only to meet the electricity and shaft power demand from the background process but also to satisfy the additional energy requirement incurred by CO2 removal. With the energy integration for the overall systems, the fuel consumption could be reduced, and operating cost, minimized. A case study is presented to demonstrate the usefulness and effectiveness of the proposed methodology for the design of energy and power systems in liquid natural gas (LNG) plants, under a carbon-constrained business environment.

1. INTRODUCTION 1.1. Power Systems Design. A power system is necessary to support the operation of refrigeration systems in low temperature processes, for example, air separation and natural gas liquefaction, as these power-intensive processes consume a considerable amount of mechanical power to drive large refrigeration compressors for recirculating refrigerants to a high pressure level. Moreover, electricity generation is required to meet electrical power demands for the operation of motors, pumps, as well as other auxiliary equipment. Hence, a power system should be designed to make sufficient supply of both mechanical and electrical power for the background process. Various commercialized gas turbine models are available for power generation in the market, and it is not straightforward to select most appropriate gas turbines and design them in a costeffective manner. This is mainly because each gas turbine has a unique characteristic of performance as illustrated in the Appendix as well as gas turbines commercially available in the market have discrete sizes. Design activities become more complicated, when a couple of mechanical demands are considered, as such a system is inevitably to have a large number of matching options between compressors and drive shafts. When considerable process heating is involved, steam systems will also need to be introduced. There are many elements to be simultaneously considered for the design of power systems, in which a large number of design configurations should be screened, as well as design interactions should be systematically investigated. For example, decision on the number, model, and size of drivers, shaft arrangement, and the selection of power plants will have strong influence on fuel consumption, carbon emissions and capital cost for power systems, and this decision is heavily related to how the overall energy infrastructure of the site is to be configured and operated. r 2011 American Chemical Society

Due to combinatorial nature in the selection of drivers, the analysis of potential solutions and the evaluation of its performance is not a trivial task. Therefore, a robust and systematic approach is essential to screen all potential candidates and provide optimal configuration (i.e., structural decisions) and operating conditions. During the last three decades, a considerable number of studies have been made to address the synthesis and design of power systems. A mixed-integer linear programming approach was introduced to optimize the structure of process systems, including power systems by Papoulias and Grossmann.1 The multiperiod design methodology was also presented to account for the variations of process steam and electricity demands.24 However, in these mathematical models, the discrete nature of the gas turbine has not been reflected, which results in inaccurate evaluation of systems performance. Consideration of impacts associated with the discrete size of gas turbines had been studied by Marechal and Kalitventzeff,5 but the selection and design of gas turbines was not made in the context of drivers selection in which a large number of combinatorial selections and their integration is required. Moreover, most of the previous studies in energy systems have focused on the provision of heat (steam) and electricity, rather than that of (mechanical) power. The significance of power elements in the design of energy systems has been fully acknowledged by the Centre for Process Integration (CPI), The University of Manchester, at which systematic design methodology for power systems has been studied. The first contribution made by CPI was to introduce a mathematical programming approach which synthesizes power Received: April 19, 2011 Accepted: August 11, 2011 Revised: June 23, 2011 Published: September 07, 2011 11201

dx.doi.org/10.1021/ie200839k | Ind. Eng. Chem. Res. 2011, 50, 11201–11225

Industrial & Engineering Chemistry Research systems for power-dominated processes, like a liquid natural gas (LNG) plant.6 The proposed model is able to describe the power system more accurately by selecting gas turbine based equipment from a predefined list of available equipment models, of which the discrete nature has been fully addressed, rather than treating them with continuous variation in size. Although complex design and its combinatorial feature in the analysis had been systematically dealt with, heat integration potentials were not fully envisaged, due to the assumption of single level steam production, although some previous works clearly indicated the benefit of producing multiple steam levels in steam generation and its cogeneration.7,8 Most of those works carried out for the design of utility systems based on multiple steam levels have not fully appreciated the importance of driver selections from the viewpoint of providing mechanical power to the site. Thus, in this research, great efforts have been made to improve the heat recovery strategy among process streams. On the one hand, heat recovery steam generators (HRSGs) are allowed to raise multiple pressure levels of steam to achieve maximum heat recovery from gas turbine exhaust. On the other hand, energy recovery and interactions between the power systems and CO2 capture processes are rigorously investigated. The heat recovery strategy proposed in this research is able to identify synergetic benefits for the heat recovery from multiple-level steam production and systemwide heat integration. 1.2. CO2 Capture Technologies. Power systems generate mechanical and electrical power, demanded from refrigeration systems, by consuming fuel. Traditionally, the resulting CO2 emission during fuel combustion is released directly into the atmosphere without any treatment. However, strong emphasis has been recently placed on carbon capture and sequestration, due to increasing concerns on greenhouse gas emissions. Currently, there are three main pathways for CO2 capture, including postcombustion, precombustion decarbonisation, and oxy-fuel combustion.9 In the postcombustion route, CO2 content is removed from the system after fuel combustion. The amine absorption process is a proven technology for removing CO2 from acid gases. And, it was developed for acid gas removal from a natural gas stream in 1920.10 This technology takes advantage of the reversible reaction between the amine solvent and the acid component in flue gases. Lean amine solvent takes CO2 away from the flue gas through countercurrent contact in an absorber at temperatures around 4080 °C and then becomes CO2 rich. The rich solvent then will be heated and regenerated in a stripper, where CO2 is released from the solvent and sent for compression. The regenerated CO2 lean solvent will be sent back to the absorber and will treat more flue gas. In the precombustion decarbonization route, CO2 capture takes place before fuel combustion. The whole process can be divided into two parts, syngas production and CO2 separation. During syngas production, the original fuel, typically natural gas, reacts with steam at temperatures of about 8001000 °C in the steam methane reformer and produces a mixture mainly composed of hydrogen, carbon monoxide, and carbon dioxide. In order to turn more carbon monoxide into carbon dioxide for final removal and enhance the hydrogen production, water shift reactors are normally applied after the steam methane reforming. After water shift reactions, CO2 in the mixture can be separated by various separation technologies, such as amine absorption, physical absorption, cryogenic separation, and membrane technology. The resulting hydrogen-rich fuel after CO2 removal is

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sent to firing machines, such as gas turbines, boilers, and heat recovery steam generators (HRSGs). As the CO2 content in the flue gas produced from hydrogen-rich fuel is very low, there is no need for further flue gas treatment in the precombustion decarbonisation route. In the oxy-fuel combustion route, nitrogen, as the component of highest concentration in the air, is separated from oxygen by, typically, a cryogenic distillation unit before fuel combustion. Hence, the consequent combustion will produce a flue gas ready for further sequestration, mainly containing water and carbon dioxide. Although the above three CO2 capture technologies have their own mechanism and process features to remove CO2 from the system, a common feature among them is that each process requires extra energy input to implement CO2 capture. Such energy demand incurred by CO2 capture may have different forms, such as, process heating, compression shaftpower, or electricity. So, it is very important that when a CO2 capture process is considered for power and energy systems to remove the CO2 content, additional energy demand should be integrated during the power system design. Many papers have discussed the performance of various CO2 capture technologies, particularly for power plants, and analyzed implications caused by CO2 removal.1114 For power plants employing, typically, a large gas turbine electricity generator, energy demand incurred by the introduction of postcombustion CO2 capture processes causes a considerable penalty on system efficiency but does not affect the fundamental system configuration of electricity generation too much. However, for powerdominated processes, for example, LNG plants, when additional energy is required for CO2 capture, the design of power systems should accommodate the increased energy demand and, consequently, will be heavily influenced by coupling power systems together with CO2 capture processes. Especially, for a retrofit scenario, increased energy demand associated with decarbonisation results in structural modifications in power systems, for example, adjusting equipment size or adding new equipment. Decoupled and nonintegrated design of power systems without considering decarbonization certainly overlooks the opportunities for energy integration between two systems. Therefore, in this research, a holistic approach is taken for power system design, in which the performance of CO2 capture processes is considered, and interactions between these two systems are fully investigated.

2. INTEGRATED DESIGN OF POWER SYSTEMS AND CO2 CAPTURE A systematic design methodology for power systems has been proposed with the aid of a mathematical programming approach which enables integrated design of both power systems and CO2 capture processes. A significantly improved model of power systems has been developed to evaluate the performance of available driver options, power plants, as well as steam generators. Equipment selection has been implemented through discrete decision-making with the application of superstructure approach. The main features of CO2 capture processes are extracted and represented by performance parameters, such as heating and shaft power demand for unit CO2 removal. Heat exchange between these two subsystems has been modeled in a heat recovery module, which is able to maximize the benefit of recovering heat from gas turbine exhaust. As the design 11202

dx.doi.org/10.1021/ie200839k |Ind. Eng. Chem. Res. 2011, 50, 11201–11225

Industrial & Engineering Chemistry Research

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Figure 1. Superstructure of power systems.

Figure 2. Network for steam generation, distribution, and consumption.

methodology is able to exploit the interactions between power systems and CO2 capture processes, the overall system efficiency can be improved and the energy penalty resulted from decarbonisation can be minimized. A superstructure, which includes all possible structural options, is established for the design and optimization of power systems, as shown in Figure 1. Compared with the superstructure defined by Del Nogal,15 it includes more options for power generation, steam turbine drivers, and steam turbine generators.

This new feature becomes available due to the design of a steam system for steam generation and detailed heat recovery. In the new superstructure, potential driver options include direct drive gas turbines, electric motors, and steam turbine drivers. Starters for gas turbines are allowed to operate continuously after startup and run as a motor or generator to balance the power on gas turbine shafts. Commercial power plant packages, including simple cycle power plants (SCPP) and combined cycle power plants, are also considered as electricity 11203


Industrial & Engineering Chemistry Research generation devices. A simple power plant produces electricity (or power) by coupling a gas turbine with a power generator unit. The combined cycle refers to a system which combines a gas turbine, a steam turbine, and a heat recovery steam generator, in which the exhaust gas from the gas turbine is utilized to generate steam and to produce electricity (power) by expanding steam in the steam turbine. A steam turbine generator is another option for electricity generation, if steam systems are present on site. Equipment based on gas turbines is available in the market with discrete capacity, and therefore discrete decision is accordingly employed when the model is selected from a prespecified list. The maximum number of each type of equipment needs to be specified for building the superstructure. This constraint has a strong impact on solution space and computational time for optimization and, therefore, needs to be carefully selected. Another important aspect to be determined in power system design is machine allocation. For a given set of compressors and compression stages, there are a large number of potential arrangements possible for the allocation of drive shafts to compressor stages. These large numbers of combinatorial possibilities are to be systematically screened and evaluated from the optimization, which identifies matching between drive shafts and the compressor stages in a most cost-effective manner. Besides the provision of shaft power and electricity, steam production and its usage is another important design issue, particularly when CO2 capture is introduced in power systems. When CO2 capture processes, for example, amine-based absorption processes, require a considerable amount of low pressure steam as a heating source, it is inevitable to extend pure power systems to steam-based energy systems. The site configuration for steam generation, distribution, and usage is illustrated in Figure 2. In this steam network, boilers consume fuel and produce steam for steam mains. From mass and energy balances across fuel-fired equipment involved in Figures 1 and 2, a performance indicator, for example, total fuel consumption, can be obtained. In order to reduce overall fuel consumption, exhaust gas from a gas turbine can be utilized in heat recovery steam generators, in which waste heat in gas turbine exhaust is recovered for steam production. Equipment selection for gas turbine drivers and power plants has a great impact on the amount of steam production and its quality. A new mathematical model has been developed for HRSGs to allow for multiple pressure level steam production. Fully supplementary firing can be an option to increase steam production or to produce very-high pressure steam. Feasible heat recovery from the exhaust is ensured through the feasibility check which is performed at kink points along grand composite curves. Compared with the previous HRSG model proposed by Del Nogel15 in which steam is only produced at a single level, the proposed model in this research is able to achieve maximum heat recovery and facilitate high pressure steam production, wherever possible. As a result, the overall fuel consumption can be significantly reduced. In Figure 2, the main steam generation devices include boilers and heat recovery steam generators. Three types of HRSGs are considered in the superstructure to consider different sources of further heat recovery, including direct drive gas turbines (DDGT), simple cycle power plants (SCPP), and CO2 capture processes (CCP). For the first two types of HRSGs, the available energy of the exhaust from gas turbines is recovered to produce multiple pressure level steam. As the ability of generating high pressure steam is limited for DDGT and SCPP models with

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exhaust temperatures below 500 °C, additional fuel consumption is allowed to fully accommodate supplementary firing in the associated HRSGs and boost the pressure level of steam. Moreover, another advantage of supplementary firing in HRSGs is to increase high pressure steam production with relatively low fuel consumption. The existence of the third type of HRSG (CCP HRSG) totally depends on the selection of CO2 capture technologies. When a precombustion decarbonisation route is chosen for CO2 capture, then the HRSG for CO2 capture processes will be a possible choice for the heat recovery among process streams and steam production. A systematic heat recovery module has been developed to carry out maximum heat recovery among process streams for steam generation. However, if the other two CO2 capture options are selected, the CCP HRSG will not be activated because there is no available heat source in the CO2 capture processes. Besides these main steam generation devices, steam generation from background processes can also be taken into account as one of the sources for steam supply in the superstructure. Steam turbines can serve as either mechanical drivers or electricity generators. In this work, multiple-stage steam turbines are employed, in which pressurized steam is extracted at intermediate pressure levels. Multistage steam turbines are decomposed into a series of single stage steam turbines, and the overall output is estimated as the sum of contributions made at each expansion stage. Steam is also sent to downstream processes for heating purposes, including the reboiler duty of amine solvent regeneration. If a precombustion decarbonization route is selected for CO2 removal, steam is also consumed in the reformer during syngas production. Overall systemwide fuel consumption is taken as the main objective for minimization. However, if preferred, other performance indicators, such as total annualized cost or total operating cost can also be selected as the main objective. The overall fuel consumption can be obtained through performance estimation of fuel-fired equipment involved in Figures 1 and 2. The detailed model for equipment performance estimation is presented in the subsequent sections, which is mainly represented by linear equations, according to the mass and energy balances for individual equipment as well as the overall system. It should be noted that all the gas turbine based equipment has been assumed to operate at full load in this study. Since overall fuel consumption has been selected as the main objective, capital cost calculations have not been implemented in this study, although in principle the modeling and optimization frameworks presented in this paper can be readily extended to perform economic trade-off by adding capital costing of the equipment. However, many new components in the power systems are introduced in this work, as a steam system is included during the design, and interactions between power systems and CO2 capture processes are exploited. These new features will be illustrated in detail in following sections. 2.1. Modeling of Power Systems. Mechanical Drivers. The mechanical drivers are responsible for the generation of mechanical power in the power systems, supporting the operation of compressors connected to drive shafts. Potential mechanical driver options include direct drive gas turbines, electric motors, and steam turbine drivers as shown in Figure 1. After the maximum number of each equipment type is specified to define the size of superstructure, the number of potential drive shafts for each driver option is determined. 11204



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Figure 3. Decomposition of multistage steam turbines.

On each DDGT drive shaft, a set of binary variables, YDDGTop, is introduced to represent the selection status of all available DDGT models. Since, only one DDGT model is allowed to be selected on each drive shaft, a logic constraint given in eq 1 is employed. As gas turbines are assumed to operate at full load, the performance parameters for all DDGT models have already been known according to the predefined model list, such as output and heat rate. The mechanical power generated by the selected DDGT on each DDGT shaft is calculated in eq 2. And the corresponding fuel consumption is formulated in eq 3.

∑

DDGTop

YDDGTopDDGT, DDGTop e 1

∑

WDDGTDDGT ¼

DDGTop

ð1Þ

∑

ðWDDGTopDDGTop

3 HRDDGTopDDGTop 3 YDDGTopDDGT, DDGTop Þ

ð3Þ

As mentioned before, starters used for gas turbine startup can operate continuously either in motor mode or generator mode after the startup period. The actual output of starters for the use after the startup can be different from the startup requirements. However, it should have an upper bound related to the output, as formulated in eqs 4 and 5 for motor mode and generator mode, respectively. A set of binary variables, YHM, are introduced to account for the mode selection for starters in eqs 6 and 7. When the starter operates as a helper motor, the electricity demand is calculated with eq 8, while shaft power requirement at helper generator mode is calculated with eq 9. WHMDDGT e

∑

DDGTop

ðYDDGTopDDGT, DDGTop 3 WHMGUBDDGTop Þ

ð4Þ PowHGDDGT e

∑

DDGTop

ðYDDGTopDDGT, DDGTop 3 WHMGUBDDGTop Þ

ð5Þ

PowHGDDGT e ð1 YHMDDGT Þ 3 MaxHMGUB

ð7Þ

WHMDDGT HMEff

PowHGDDGT ¼ WHGDDGT 3 HGEff

ð8Þ ð9Þ

The performance of electric motors is defined by the energy conversion efficiency from electrical power to mechanical power. The electricity consumption is calculated with eq 10, and an upper limit for electric motor size is imposed in eq 11.

ðWDDGTopDDGTop 3 YDDGTopDDGT, DDGTop Þ

DDGTop

ð6Þ

PowHMDDGT ¼

WEMEM EMEff

ð10Þ

WEMEM e MaxWEM

ð11Þ

PowEMEM ¼

ð2Þ QDDGTDDGT ¼

WHMDDGT e YHMDDGT 3 MaxHMGUB

For steam turbine drivers, a multistage model is employed to allow for potential steam extraction at all the available intermediate or low pressure steam mains. The number of stages for the turbine is governed by the steam headers considered in the steam network. For example, for the turbine operated by VHP (very high pressure) steam, the steam can be extracted at HP (high pressure), MP (medium pressure), and LP (low pressure) steam mains to meet the process steam demand. The unused steam after steam extraction will be further expanded and sent to the condensing main for mechanical power generation. As shown in Figure 3, such a multistage steam turbine can be conceptually decomposed into several single stage steam turbines. With the inlet steam flow rate of each decomposed single stage Cond VHP , the mechanical power steam turbine, DFstLV Lv+1 = ∑i=Lv+1 Fsti generated in each stage can be estimated by eq 12, in which a linear relationship is applied to simplify the evaluation of steam turbine performance.12 And then, the overall output can be calculated by summing up all the contribution made at each individual stage, as formulated in eq 13. Equation 14 is formulated to identify whether the VHP steam turbine is active or not. Other steam turbines fed by HP, MP, and LP steam are formulated in a similar way. The maximum number of steam turbine drivers can be specified to control the steam system 11205



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complexity, which is enforced with eq 15. Lv WDSTDLv Lv þ 1 ¼ ΔhExpLv þ 1 Lv 3 DFstSTDLv þ 1

WSTDVHP ¼

LP

∑ WDSTDLvLv þ 1 Lv ¼ VHP

WSTDVHP YSTDVHP 3 MaxWSTD e 0 LP

∑

YSTDLv e MaxNoSTD

ð12Þ ð13Þ ð14Þ ð15Þ

VHP

Formulation so far has been for modeling for the supply of mechanical power in power systems design. However, driver selection as well as equipment sizing heavily relies on the actual mechanical power demand for compressor stages. Binary variables are employed to address the compressor stage allocation strategy on each drive shaft, as formulated in eqs 1618 for DDGT, motor, and steam turbine shafts, respectively. Logic constraint, eq 19, is introduced to ensure that only one mechanical driver will be allocated to drive a specific compressor stage. WDDGTSDDDGT ¼

of electrical devices, such as motors, pumps, fans, etc., on-site power generation is likely to be an economic solution, rather importing electricity. For some cases, importing electricity is not feasible or very limited and then on-site power generation becomes essential. There are three potential electricity generation devices as mentioned before, simple cycle power plants, combined cycle power plants, and steam turbine generators. As the first two options only have commercial packages with discrete sizes, binary variables have to be introduced to reflect the discrete nature of production capacity of power plant models. Equation 23 states the amount of electrical power generated from the selected power plant, and eq 24 calculates the fuel consumption according to given power plant performance data. Equation 25 ensures that only one power plant model, either simple cycle or combined cycle, is selected for each available power plant place in the superstructure. PowPPPP ¼ QPPPP ¼

WSTDSDSTD ¼

∑

YDDGTCSDDGT, CS þ

ð18Þ

∑ YEMCSEM, CS

EM

DDGT

þ

ðYSTDCSSTD, CS 3 WCSCS Þ ∑ CS

ð17Þ

∑

YSTDCSSTD, CS ¼ 1

ð19Þ

STD

ðPowPPopPPop 3 YPPopPP, PPop Þ

∑

PPop

ðPowPPopPPop 3 HRPPopPPop 3 YPPopPP, PPop Þ

YPPopPP, PPop e 1

Lv PowDSTGLv Lv þ 1 ¼ ΔhExpLv þ 1 Lv 3 DFstSTGLv þ 1

PowSTGVHP ¼

LP

PowDSTGLv ∑ Lv þ 1 Lv ¼ VHP

PowSTGVHP YSTGVHP 3 MaxWSTG e 0 ð20Þ

WEMEM ð1 MLossÞ ¼ WEMSDEM

ð21Þ

WSTDSTD 3 ð1 MLossÞ ¼ WSTDSDSTD

ð22Þ

It should be noted that if CO2 capture process is integrated in the power system design, the mechanical power consumers consists of not only the compressors from the background process, but also other mechanical power demand associated with CO2 removal. Electricity Generation. When there is a considerable electricity demand from the background process due to operation

ð25Þ

The mathematical model of multistage steam turbine generators is quite similar to that of steam turbine drivers. The only difference is that the energy output for generators is electricity, instead of shaft power. The decomposition technique is applied as well to estimate the overall output for multistage steam turbine generators. The formulations for VHP steam generator are shown as eqs 2628. Other steam turbine generators fed by HP, MP, and LP steam are formulated in the similar way. Equation 29 is employed to guarantee the actual number of steam turbine generators does not exceed the specified maximum value.

With the above formulations for mechanical power demand, power balance on each drive shaft can be carried out to make sure that mechanical power supply is equal to the demand, although a fraction of loss is defined to account for the mechanical power loss during transmission. Equations 20, 21, and 22 state the power balance on DDGT, motor, and steam turbine shafts, respectively. ðWDDGTDDGT þ WHMDDGT Þ 3 ð1 MLossÞ ¼ WDDGTSDDDGT þ WHGDDGT

ð23Þ

ð24Þ

ðYDDGTCSDDGT, CS 3 WCSCS Þ ∑ CS

ðYEMCSEM, CS 3 WCSCS Þ ∑ CS

∑

PPop

ð16Þ WEMSDEM ¼

∑

PPop

LP

∑ YSTGLv e MaxNoSTG Lv ¼ VHP

ð26Þ ð27Þ ð28Þ ð29Þ

In order to make sure that the amount of electricity generated by on-site equipment is not less than the demand for the background process, electricity balance is carried out in eq 30. As assumed in this equation, surplus electricity generated on-site can be exported to the external power grid. And on the other hand, electricity import is allowed to meet the process demand in case of insufficient on-site power generation. For cases where electricity import is not feasible, for example, floating production of liquefied natural gas in offshore, on-site energy demand should be met by on-site energy 11206



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Figure 4. Grand composite curves for multilevel steam production in HRSGs for gas turbine based equipment.

generation systems.

∑ PowEMEM þ DDGT ∑ PowHMDDGT þ EExp

BED þ

EM

¼ð þ

∑ PP

∑

PowPPPP þ

DDGT

LP

∑

STG ¼ VHP

PowSTGSTG

PowHGDDGT Þ 3 ð1 ELossÞ þ EImp

ð30Þ

Steam Production. When steam turbine based equipment is selected for mechanical or electrical power generation, high pressure steam production is essential to ensure the supply of pressurized steam. Potential steam production devices include boilers and heat recovery steam generators (HRSGs). In the superstructure shown in Figure 2, boilers raise steam for any required pressure levels, if there is an insufficient steam supply from HRSGs. The fuel consumption of the boiler is formulated in eq 31, in which prespecified boiler efficiency is used to evaluate the boiler performance. QBLv ¼

ΔhSTMLv MstBoilerLv BoilerEff 3

below the exhaust grand composite, then feasible heat transfer for HRSGs can be guaranteed. At the first checking point (1), the steam grand composite has the superheated temperature for VHP steam, which is assumed at 500 °C (after a 10 °C temperature shift) for the case study in this work. And the exhaust grand composite is at the exhaust outlet temperature from gas turbines, which is ranging from 450600 °C for available DDGT and SCPP models. Obviously, exhaust from gas turbine models with temperature below 510 °C could not be used to produce VHP steam, and on this occasion, HP steam will be the highest pressure level. However, in order to enhance the steam quality in this case, fully supplementary firing can be introduced to increase the exhaust temperature to 850 °C, which is high enough to raise VHP steam. Checking points 25 are featured by the physical nature of water vaporization. A big slope change can be observed at these kink points, which implies if these points meet the feasible heat transfer condition, then the local points close to them will not violate it. Feasibility check at the last point (6) ensures that the actual stack temperature of gas turbine exhaust is not lower than the boiler feedwater temperature plus ΔTmin. A feasibility check at checking point 1 is straightforward, which can be implemented by directly comparing the exhaust temperature from the selected model with conditions of VHP steam. Equations 32 and 33 formulate the feasibility check for DDGT HRSG and SCPP HRSG, respectively. In these equations, binary variables YVHP and YSF are introduced to account for the existence of VHP steam production and fully supplementary firing, respectively. Only when HRSGs produce VHP steam and operate in the nonsupplementary firing mode (YVHP = 1, YSF = 0) will these equations take effect and perform the heat transfer feasibility check. For other HRSG operating modes, the feasibility condition will be met automatically. The fuel consumption for fully supplementary firing is calculated in eq 34.

∑

DDGTop

g ðT VHP Sup þ ΔT min Þ 3 ðYVHPDDGT YSFDDGT Þ

ð31Þ

The steam production in HRSGs strongly depends on the type of energy sources they are attached to. As mentioned before, three different energy sources are involved in this superstructure, including direct drive gas turbines, simple cycle power plants, and CO2 capture processes, if applicable. The mathematical model for the first two cases is addressed in this section. However, the heat recovery model for CO2 capture processes will be presented in the next section to highlight particular features of the CO2 capture process. For HRSGs attached to the gas turbine based equipment, they produce steam by reusing the available thermal energy in gas turbine exhaust. Heat exchange takes place between the feedwater stream and the gas turbine exhaust until water is evaporated and superheated to the desired temperature. Typical grand composite curves for a multilevel HRSG are illustrated in Figure 4, which allows steam production at four pressure levels. In order to make sure that the heat transfer in the HRSG can be successfully implemented, the exhaust grand composite should not have any part below the steam grand composite. By observing the steam grand composite, it can be seen that if the six kink points marked with small circles in Figure 4 are located on or

ðTExhDDGTopDDGTop 3 YDDGTopDDGT, DDGTop Þ

∑

SCPPop

ð32Þ

ðTExhSCPPopSCPPop 3 YPPopPP, SCPPop Þ

g ðT VHP Sup þ ΔT min Þ 3 ðYVHPPP YSFPP Þ QSFHRSG ¼

ð33Þ

ðMExhHRSGSF ∑ ∑ DDGT, DDGTop DDGT DDGTop

3 CPExhDDGTop 3 ðTSF TExhDDGTopDDGTop ÞÞ Cmb

þ

∑PP SCPPop ∑ ðMExhHRSGSFPP, SCPPop 3 CPExhCmb SCPPop

3 ðTSF TExhSCPPopSCPPop ÞÞ

ð34Þ

Feasibility checks at checking points 25 strongly depend on the shape of both exhaust and water stream grand composites. The exhaust grand composite is determined by two factors, the exhaust temperature and mass flow rate, which are affected by the choice of gas turbine model as well as the HRSG’s operating 11207



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mode. The exhaust temperature defines the starting point of the composite, and the mass flow rate defines the slope. Equations 35 and 36 state the heat flow calculation of temperature at checking points for DDGT HRSG and SCPP HRSG, respectively, under nonsupplementary firing mode. Equations 37 and 38 are for the heat flow calculation of HRSGs operated under a fully supplementary firing mode. In these equations, ΔTmin is added on to the checking point temperature to ensure feasible heat transfer. As all HRSGs can only operate under one operating mode, nonsupplementary firing or fully supplementary firing, logic constraints eqs 39 to 42 are included. HFDDGTExhNoSF DDGT, CKPnt ¼

∑

DDGTop

ðMExhHRSGNoSF DDGT, DDGTop

the evaporation section of the steam grand composite, the temperature is constant and vapor fraction needs to be specified to identify the physical state of steam. Function HFSteam(MstHRSG, T, y) is defined to calculate the heat flow at the specified points along the steam grand composite. When the temperature level T and vapor fraction y are defined, the corresponding point can be identified along the composite, and function HFSteam(MstHRSG, T, y) becomes a linear formulation of steam mass flow rate, MstHRSG. The heat flow for checking points 25 are calculated in eqs 43 and 44 for DDGT and SCPP HRSGs, respectively, where checking points are defined by the physical state, saturated liquid (y = 0), at all steam pressure levels. HFDDGTStmDDGT, CKPnt ¼ HFSteamðMstHRSGDDGT, Lv , T CKPnt , 0Þ

3 CPExh 3 ðTExhDDGTopDDGTop ðT CKPmt þ ΔT min ÞÞÞ

ð43Þ

ð35Þ HFSCPPExhNoSF PP, CKPnt

¼

HFSCPPStmPP, CKPnt ¼ HFSteamðMstHRSGPP, Lv , T CKPnt , 0Þ

∑

SCPPop

ð44Þ

ðMExhHRSGNoSF PP, SCPPop

3 CPExh 3 ðTExhSCPPopSCPPop ðT CKPnt þ ΔT min ÞÞÞ ð36Þ HFDDGTExhSF DDGT, CKPnt ¼

∑

DDGTop

ðMExhHRSGSF DDGT, DDGTop

3 CPExh 3 ðTSF ðT CKPmt þ ΔT min ÞÞÞ

HFSCPPExhSF PP, CKPnt ¼

∑

HFDDGTStmDDGT, CKPnt e HFDDGTExhNoSF DDGT, CKPnt

∑ ðMExhHRSGSFPP, SCPPop SCPPop

3 CPExh 3 ðTSF ðT CKPnt þ ΔT min ÞÞÞ

DDGTop

ð37Þ

A feasibility check for heat transfer at checking points 25 can be performed by comparing heat flow between the two composites, the exhaust grand composite and the steam (or water) grand composite. If, at the given temperature level, the heat flow on the exhaust grand composite is not less than the one on the steam grand composite, then heat exchange is feasible. This checking procedure implemented at each checking point is formulated in eqs 45 and 46.

MExhHRSGNoSF DDGT, DDGTop

þ HFDDGTExhSF DDGT, CKPnt

ð38Þ

HFSCPPStmSCPP, CKPnt e HFSCPPExhNoSF SCPP, CKPnt

e MaxMExh 3 ð1 YSFDDGT Þ

þ HFSCPPExhSF SCPP, CKPnt

ð39Þ

∑

DDGTop

MExhHRSGSF DDGT, DDGTop e MaxMExh 3 YSFDDGT ð40Þ

∑

SCPPop

MExhHRSGNoSF PP, SCPPop e MaxMExh 3 ð1 YSFPP Þ ð41Þ

∑

SCPPop

MExhHRSGSF PP, SCPPop e MaxMExh 3 YSFPP

ð42Þ

Moreover, the shape of the water stream grand composite can be determined when the amount of steam produced at each pressure level is specified, with given steam conditions. With steam property data, particularly steam enthalpy, the heat flow at any points along the steam grand composite, including checking points, can be formulated as linear functions of steam mass flow rate, MstHRSG. However, the checking points on the steam grand composite needs to be defined not only by temperature level, but also by vapor fraction. Because during

ð45Þ

ð46Þ

Heat transfer feasibility check at checking point 6 can be done similarly to checking points 25. However, the physical condition at this point is liquid, instead of saturated liquid. And, the temperature level at the checking point is given by the boiler feedwater, not by steam conditions. With the linear equations formulated above, the feasibility check for heat transfer can be implemented in HRSGs attached to gas turbine based equipment. Maximum flexibility is given to the selection of quality and quantity for steam production. The best steam production strategy will be identified through the optimization, including the pressure levels as well as the amount of steam produced. The mathematical modeling for steam production units and heat recovery equipment has been established above. It should be noted that steam balance is important to match steam supply with the steam demand in each steam main. For each steam main, potential sources of steam input include not only steam production units, such as boilers, HRSGs, and process steam generators, but also some steam consumers and distribution units, such as steam turbines and let-down valves. On the steam demand side, a considerable amount of steam is required for process heating, CO2 removal, and power generation through steam turbines. 11208



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Steam balance for the VHP steam main is formulated in eq 47 (Lv = 1, VHP), and eq 48 for other steam mains (Lv g 2). A constant fraction, SLoss, is specified to account for steam loss during distribution from steam production units to steam mains. ð1 SLossÞ 3 ðMstBoilerVHP þ þ

∑

MstHRSGDDGT, VHP

DDGT

∑PP MstHRSGPP, VHP þ MstCPPGenVHP Figure 5. Process flow diagram of amine absorption process.

þ MstProGenVHP Þ ¼ MstLetDownVHP þ

Cond

ðFstSTDVHP þ FstSTGVHP Þ ∑ i i i ¼ HP

þ MstProDemVHP þ MstCPPDemVHP ð1 SLossÞ 3 ðMstBoilerLv þ þ

∑PP MstHRSGPP, Lv

∑

ð47Þ

MstHRSGDDGT, Lv

DDGT

þ MstCPPGenLv

þ MstProGenLv Þ þ MstLetDownLv1 þ

Lv 1

∑

i ¼ VHP

ðFstSTDiLv þ FstSTGiLv Þ

¼ MstLetDownLv þ

Cond

ðFstSTDLv ∑ i i ¼ Lv þ 1

þFstSTGLv i Þ þ MstProDemLv þ MstCPPDemLv where, Lv g 2

ð48Þ

By summing up the fuel consumption in each individual piece of fuel-fired equipment, total system fuel consumption can be obtained, as formulated in eq 49, in which QCPP accounts for the amount of fuel consumed in the CO2 capture process if applied. In order to achieve a power system with maximum energy efficiency, the minimization of total fuel consumption is chosen to be the objective function in this work. FuelTotal ¼

∑

DDGT

þ

QDDGTDDGT þ

∑PP QPPPP

∑Lv QBLv þ QSFHRSG þ QCPP

ð49Þ

So far, the effect of introducing CO2 capture processes has not been analyzed in detail, particularly, the impact of additional energy demand. In the next section, mathematical models for integrated design with different CO2 capture processes are presented and a systematic approach is proposed to exploit design interactions between power systems and CO2 capture processes, so that the overall system efficiency can be maximized. 2.2. Modeling of CO2 Capture Performance for Different Technologies. Regardless of technologies implemented for CO2 capture, the energy required for CO2 removal can be classified into three basic demands: process heating, shaft power, and electricity. In this work, the detailed modeling for CO2 capture is not considered. But, performance characteristics for CO2 capture

are incorporated in the proposed design frameworks, which is a realistic and robust approach in the conceptual design stage. Postcombustion CO2 Capture. Amine absorption, as a typical postcombustion CO2 capture technology, is selected for the analysis. Major equipment involved as well as its process flow diagram is illustrated in Figure 5. The flue gas produced in firing machines is collected and sent to this amine absorption process for CO2 removal. Before entering the absorber, the flue gas is pressurized by a blower, which is necessary to overcome the pressure drop in the absorber. The blower is driven by either an electric motor or a mechanical driver. In the absorber, the flue gas contacts the amine solvent through a countercurrent flow and the amine solvent absorbs most of the CO2 contained the flue gas. The resulting CO2-rich solvent is sent to the stripper for regeneration. In the stripper, particularly the reboiler section, the absorbed CO2 is released from the solvent after being heated up by low pressure steam, and the lean solvent is recycled to the absorber. The CO2 content is eventually separated as the top product of the stripper. As typical operating pressure of stripper is around 12 bar(a), which is far below the requirement of CO2 transportation for sequestration; the removed CO2 needs to be further treated and compressed to, typically, 80120 bar(a). It should be noted that considerable amount of process heating is required in the amine absorption process to regenerate the amine solvent. This heating demand normally is satisfied by LP steam produced in the steam systems. The steam requirement mainly depends on the total amount of CO2 to be removed and the performance of the CO2 capture process, influenced by operating conditions, such as solvent type, solvent flow rate and concentration, pressure levels in the absorber and stripper, etc.16 Other energy consumers in the amine absorption process includes a blower (used for overcoming pressure drop in the absorber), and a CO2 compressor (used for CO2 compression). Shaft power demand for both devices is related to CO2 recovery as well as pressure ratio. At typical operating conditions for the amine absorption process, performance parameters, such as specific heating and shaft power demand for unit CO2 removal can be obtained, as formulated in eqs 50 and 51 for steam and mechanical power demand respectively. And these performance parameters are considered in the design of power systems. MstCPPDemLP ¼ MCO2 Rem 3 SHDemCPP=LPHeat ð50Þ WCPPCPP ¼ MCO2 Rem 3 SWDemCPP

ð51Þ

In eq 50, LPHeat is the available heat from unit LP steam supply, and specific heating demand for unit CO2 removal is defined as SHDemCPP. Specific shaft power demand for unit CO2 removal 11209



Figure 6. Iterative approach for systematic design of power systems and CO2 capture.

is also defined, as SWDemCPP in eq 51, in which the overall mechanical power demand for CO2 capture is calculated. The amount of CO2 removal, MCO2Rem, in above equations is determined by the total CO2 production from fuel combustion and the removal ratio. The removal ratio can be specified to set up the design requirement for CO2 capture. However, the total CO2 production is unknown at this stage, since the fuel consumption cannot be calculated without the power system being synthesized. In this work, an iterative approach, illustrated in Figure 6, is proposed to implement the systematic design of power systems and CO2 capture. First, a rough estimate needs to be made by the designer for the total fuel consumption of the overall system. For example, total fuel consumption can be assumed to be 20% more than the one for a stand-alone power system design without CO2 capture. Then the energy demand for process heating and shaft power in the CO2 capture process are estimated by eqs 50 and 51. By taking into account these additional energy requirements, power systems can be synthesized with the mathematical model presented in the previous section. From the optimization result, actual total fuel consumption can be obtained with eq 49. As there is no fuel-fired device involved in the amine absorption process, QCPP is equal to 0 for the postcombustion CO2 capture route. By comparing the difference between the actual total fuel consumption and the one assumed at the beginning, a decision is made whether the optimization is repeated with updated assumption of fuel consumption or the current optimal solution is taken as the final best design. If there is a big difference between the actual total fuel consumption and the assumption made before, then the system needs to be optimized again with updated total fuel consumption. This optimization loop continues until the difference between the assumption and calculated value reaches within the convergence criteria. The optimal solution obtained in the last iteration will be taken as the final best design. Precombustion Decarbonization. In the precombustion decarbonisation route of CO2 capture, the major concern is how to remove the CO2 content from the system before the fuel combustion takes place. There are two key technologies widely used for precombustion CO2 capture, steam methane reforming and partial oxidation reforming. The main difference between them is the method of heat supply for reforming reaction. For steam methane reforming, reaction heat is totally supplied by fuel combustion or an external heat source. For partial oxidation reforming, reaction heat comes from the partial oxidation of methane. In this research, steam methane reforming has been selected for analysis for illustration purposes. However, if the

ARTICLE

feature of partial oxidation reforming is considered, such analysis can be easily adapted to partial oxidation reforming. In the steam methane reforming process, natural gas reacts with steam in a steam methane reformer for the production of syngas, which is mainly composed of hydrogen, carbon dioxide, and carbon monoxide. Then, the watergas shift reaction follows to enhance the conversion from carbon monoxide to carbon dioxide and, at the same time, hydrogen production is increased. After the watergas shift reaction, CO2 content needs to be separated from other syngas components and the resulting hydrogen-rich fuel can be fed to firing machines for combustion. Available CO2 separation technologies are amine absorption, physical absorption, cryogenic separation, and membrane technology. Each separation technology has its own features of energy demand in terms of quantity and energy types. For illustrating purposes, the amine absorption process is selected to remove CO2 from syngas in this work, where process heating for solvent regeneration and shaft power for CO2 compression constitute the main energy consumers. Figure 7 illustrates a typical process flow diagram for precombustion CO2 capture through steam methane reforming. More information on stream conditions and process simulation is provided in Appendix B. Natural gas reacts with steam in the reformer to produce syngas. As the reforming reaction is highly endothermic, an external energy source is required. Typically, the required heat is supplied by combusting fuel in the reformer or recovering heat from gas turbine exhaust if available. The temperature of the reformer product is very high, normally ranging from 600 to 1000 °C depending on other reaction conditions, such as pressure and conversion rate. The syngas product needs to be cooled to around 350 °C to meet the inlet temperature requirement of a high-temperature watergas shift reaction. As the watergas shift reaction is exothermic, the syngas temperature will increase after the reaction. Then the syngas temperature needs to be decreased again to about 200 °C before entering the low-temperature watergas shift reactor, in which more carbon monoxide is converted to carbon dioxide. As temperature increases after low-temperature watergas shift, the syngas stream needs to be cooled to 35 °C for CO2 separation. As can be seen, there are many high quality heat sources in the steam methane reforming process. They need to be cooled to the operating temperature of the next processing unit. If this cooling can be recovered for steam generation, then steam of various qualities can be produced and sent to the power systems for power generation and process heating in other parts of the processes. Moreover, in order to reduce the hydrogen-rich fuel consumption in the steam methane reformer, the feed stream can be preheated to 450650 °C by available heat sources before entering the reformer. With feed preheating, the fuel required to raise the feed temperature from ambient to preheated levels is saved. Another effective way for saving fuel consumption is to use available gas turbine exhaust in the reformer for the preheating of feed stream. If this is adopted, feed stream preheating demand can be significantly reduced, as the temperature of gas turbine exhaust is much closer to the reforming requirement compared with that of air. In the cases in which gas turbine exhaust is unavailable or insufficient, air will be the alternative source of oxygen for combustion in the reformer. As modeled in the previous section, for precombustion CO2 capture, part of the gas turbine exhaust is allowed to be sent to CO2 capture processes. However, there should be an upper limit for this as stated in eqs 52 and 53 for the exhaust from DDGT and 11210



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Figure 7. Process flow diagram for precombustion CO2 capture through steam methane reforming.

the mixture of fuel, exhaust, and air should reach at least 940 °C after fuel combustion and leave the reformer at temperature not lower than 480 °C. An energy balance has been carried out across the combustion and the heat exchange units in the reformer to calculate the fuel consumption, as formulated in eqs 54 and 55. Figure 8. Decomposition of the process in combustion chamber.

MFuelRFM 3 Q FuelCmb =MW Fuel ¼ MFuelRFM SCPP gas turbines, respectively. When there are engineering constraints, for example, plant layout and piping limitation, etc., for facilitating heat recovery between the exhaust of gas turbines and an HRSG or reformer, the total mass flow rate of exhaust sent to both the HRSG and reformer from selected gas turbines does not exceed the maximum allowed or specified.

Cmb

3 CpFuel 3 CpAir þ

∑

∑

3 CpExhDDGTop 3 ðTMix BHX TExhDDGTopDDGTop ÞÞ Cmb

þ

þ MExhRFMDDGT, DDGTop e MExhDDGTDDGTop ð52Þ

∑PP SCPPop ∑ ðMExhRFMPP, SCPPop 3 CpExhCmb SCPPop

3 ðTMix BHX TExhSCPPopSCPPop ÞÞ

SF MExhHRSGNoSF PP, SCPPop þ MExhHRSGPP, SCPPop

ðMFuelRFM þ MAir þ

þ MExhRFMPP, SCPPop e MExhSCPPSCPPop 3 YPPopPP, SCPPop

3 ðTMix BHX TAirPreH Þ ðMExhRFMDDGT, DDGTop

DDGT DDGTop

SF MExhHRSGNoSF DDGT, DDGTop þ MExhHRSGDDGT, DDGTop

3 YDDGTopDDGT, DDGTop

Cmb

3 ðTMix BHX TFuelPreH Þ þ MAir

∑

∑

ð54Þ

MExhRFMDDGT, DDGTop

DDGT DDGTop

þ

ð53Þ

In order to obtain the fuel consumption in the reformer, a mathematical model needs to be established for the process taking place in the combustion chamber. Actually, this process that the mixture of fuel, GT exhaust, and air undergoes in the combustion chamber can be treated as two steps, combustion and heat exchange, as shown in Figure 8. The temperature before heat exchange, TMixBHX, is the highest temperature that the mixture can reach after combustion. The heat duty of the heat exchanger should be equal to the heating demand of the reforming reaction, QRFM. The mixture leaves the reformer at a lower temperature, TMixAHX, after exchanging heat with the reactants. When typical operating conditions are selected for the reformer, the fuel consumption will be mainly determined by the total flow rate of the air and exhaust mixture, and the temperature requirement for the reaction. If the reactant streams in the reformer have a temperature range from 450 to 870 °C during the reaction, and minimum temperature difference is specified as 30 °C at the low temperature end and 70 °C at the high temperature end to guarantee successful heat transfer,11 then

∑ ∑ MExhRFMPP, SCPPop Þ 3 CpMixHX PP SCPPop

3 ðTMix BHX TMix AHX Þ ¼ Q RFM

ð55Þ

Equation 54 states that the heat released from fuel combustion is picked up by the mixture to build up its thermal energy. As the outlet temperature of the combustion unit reaches 940 °C or above, the specific heat capacity of gas turbine exhaust during combustion, CPExhCmb is higher than the one used in HRSGs for steam production, CPExh, and should be separately estimated. These two equations are nonlinear due to the existence of variable TMixBHX, so approximation techniques are applied to linearize both equations, however, with a consequent minor penalty of accuracy loss. By inspecting typical simulation results, it can be noted that the overall molar mass flow rate of air and exhaust is about 13 times more than that of fuel, which implies that the removal of term MFuelRFM in eq 55 will not significantly affect the balance of the equation. Equation 56 is the approximated version of eq 55 in which nonlinear terms, (MAir + ∑MExhRFM) 3 TMixBHX, are 11211



ARTICLE

represented by a linear function of MAir and MExhRFM. ðMAir þ

∑

∑

MExhRFMDDGT, DDGTop

DDGT DDGTop

þ

∑PP SCPPop ∑ MExhRFMPP, SCPPop Þ 3 CpMixHX

3 ðTMix BHX TMix AHX Þ ¼ Q RFM

ð56Þ

Moreover, in eq 54, if an average specific heat capacity could be identified to replace the separate ones for air and exhaust, then the nonlinear terms associated with air and exhaust in eq 54 can be given by linear formulations. Actually, in the simulation results in ASPEN HYSYS, CpAirCmb varies from 1.1 to 1.23 kJ/(kg 3 °C), and CpExhCmb, from 1.16 to 1.2 kJ/(kg 3 °C) in the temperature range during combustion. And this indicates the introduction of an average specific heat capacity, CPMixAvg, is reasonable. With CpAirCmb and CpExhCmb substituted by CPMixAvg and reformulated with linear formulations, eq 57 represents the approximated version of eq 54.

With eq 58, the hydrogen-rich fuel consumption in the reformer can be estimated with an acceptable accuracy if the values of parameters, such as CPMixAvg and average TMixBHX, are properly chosen. Normally, the relative gap between the simulation result in ASPEN HYSYS and the approximation estimated by above method can be within 2%. With the fuel mass flow rate calculated in eq 58, the fuel consumption on LHV (low heating value) basis can be obtained by eq 59. Then eq 49 can be applied to calculate the total fuel consumption in the overall systems.

In order to have a common comparison basis, this fuel demand based on hydrogen-rich fuel LHV needs to be converted to the natural gas LHV basis. Equation 60 formulates this conversion with the mass conversion ratio, MNGFuel/MHRFuel, indicating the amount of natural gas fuel required to produce unit hydrogenrich fuel. And this conversion ratio can be obtained from process simulation when typical operating conditions are specified in the steam methane reforming process.

MFuelRFM 3 ðQ FuelCmb =MW Fuel CpFuelCmb 3 ðTMix BHX TFuelPreH ÞÞ ¼ 3 ðCpMix þ

Avg

CpMix Avg CpMix HX

3 TMix AHX CpAir

3 TAirPreH Þ

ðMExhRFMDDGT, DDGTop 3 ðCpMix Avg ∑ ∑ DDGT DDGTop

Cmb 3 TMix AHX CpExhDDGTop 3 TExhDDGTopDDGTop ÞÞ

þ

FuelTotalNGFuel ¼

3 Q RFM þ MAir Cmb

∑PP SCPPop ∑ ðMExhRFMPP, SCPPop 3 ðCpMixAvg 3 TMixAHX

CpExhCmb SCPPop 3 TExhSCPPopSCPPop ÞÞ

ð57Þ

In order to remove a nonlinear term in eq 57, MFuelRFM 3 TMixBHX, an average value of TMixBHX is selected for further linear approximation in eq 58. As the term with QFuelCmb is much bigger than the modified term with TMixBHX, the substitution with an average TMixBHX will not have a significant impact on the overall balance.

CpMix Avg

3 ðCpMix

Cmb 3 TMix AHX CpAir 3 TAirPreH Þ

þ

∑

Avg

∑

DDGT DDGTop

CpMix HX

∑PP SCPPop ∑

þ

3 Q RFM þ MAir

Q RFM CPMix HX 3 ðTMixLB BHX TMix AHX Þ

∑

∑

ð61Þ

MExhRFMDDGT, DDGTop

DDGT DDGTop

ðMExhRFMDDGT, DDGTop 3 ðCpMix Avg

3 TExhSCPPopSCPPop ÞÞ

MExhRFMDDGT, DDGTop

∑PP SCPPop ∑ MExhRFMPP, SCPPop

MFuelRFM þ MAir þ þ

∑PP SCPPop ∑ MExhRFMPP, SCPPop Q RFM

g CPMix

ðMExhRFMPP, SCPPop 3 ðCpMix Avg 3 TMix AHX

CpExhCmb SCPPop

∑

DDGT DDGTop

Cmb 3 TMix AHX CpExhDDGTop 3 TExhDDGTopDDGTop ÞÞ

þ

∑

MFuelRFM þ MAir þ

e

TFuelPreH ÞÞ ¼

MLHV NGFuel MNGFuel FuelTotalHRFuel MLHV HRFuel 3 MHRFuel 3 ð60Þ

Although the presence of variable TMixBHX has been removed from equations for estimating fuel consumption, the impact of TMixBHX during the reforming process cannot be ignored. When TMixBHX is too low and falls down below, typically, 940 °C, as mentioned before, the driving force for reforming reaction will not be guaranteed, resulting in low conversion rate. On the other hand, when TMixBHX is too high, for example, above 1000 °C, it will cause problems for the combustion chamber, if the construction material cannot tolerate such a high temperature. So there should be a lower and an upper bound for variable TMixBHX to ensure feasible operation for the reforming reaction and practical reliability for equipment construction materials. As TMixBHX can be represented by a function of MFuelRFM, MAir, and MExhRFM in eq 55, the feasibility constraints can also be formulated without an explicit expression of TMixBHX as shown in eqs 61 and 62.

MFuelRFM 3 ðQ FuelCmb =MW Fuel CpFuelCmb Avg 3 ðTMix BHX

ð59Þ

QCPP ¼ MFuelRFM 3 MLHV HRFuel

ð58Þ

HX

UB 3 ðTMixBHX TMixAHX Þ

ð62Þ

Besides fuel consumption calculations, another important issue in the steam methane reforming process is heat integration. Since there are many heat sources in the process, as well as some 11212



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Table 1. Process Streams for Heat Integration in Steam Methane Reforming

heat source

heat sink

ΔH (MW)

TSource (°C)

TTarget (°C)

syngas after reforming

870

350

syngas after HT shift reaction

434

200

26.2

syngas after LT shift reaction

241

35

48.5

exhaust after reforming

process streams

60.9

480

140

reformer NG feed for preheating

35

580

reformer STM feed for preheating

280

580

35

450

TBC

35 111

450 116

TBC 49.2

air for preheating hydrogen-rich fuel for preheating rich amine solvent to be regenerated

Figure 9. Grand composite curves for the high temperature part of energy system in steam methane reforming.

cold streams to be preheated, the heat recovery problem is much more complicated than the one for HRSGs. Table 1 lists all the process streams involved in the energy system during steam methane reforming, which are extracted from simulation results in ASPEN HYSYS. The source and target temperature of all the streams are selected according to typical operating conditions of the steam methane reforming process, and the enthalpy change for some of the streams has been obtained from process simulation, when the processing capacity is specified by natural gas LHV. The stream enthalpy change listed in Table 1 is based on the simulation for processing 484.57 MW of natural gas on a LHV basis. The detailed simulation results from ASPEN HYSYS of the steam methane reforming process are illustrated in Appendix B. The heating demand for solvent regeneration is estimated by a similar method formulated in eq 49 for postcombustion CO2 capture, however using a different value for specific heating demand. The enthalpy changes for other streams (denoted by TBC in Table 1) need to be calculated according to energy balance regardless of the processing capacity. In principle, they can be represented by linear formulations with MExhRFM, MAir, and MfuelRFM, which means that the linear nature of the overall model is kept. In order to encourage the high quality heat sources to generate high pressure steam, instead of directly exchanging heat with cold streams requiring low grade heat, the energy system is strategically divided into two subsystems at a split temperature. The high temperature subsystem comprises of hot streams or segments above 140 °C and cold streams or segments above 120 °C. And other streams or segments constitute the low temperature subsystem. Obviously, the high temperature subsystem is a large heating source, requiring external cooling, which can be satisfied

TBC 16.8 19.6

by producing steam at various pressure levels. On the other hand, the low temperature subsystem is a heat sink, requiring a large amount of process heating, which can be done by low pressure steam. By treating the overall energy system as two subsystems, the potential benefit of generating high pressure steam can be maximized through mechanical and power generation. In order to ensure the heat transfer feasibility between process streams and water stream in the high temperature subsystem, grand composite curves for process streams as well as the water stream need to be constructed. The process grand composite curve of this system is a combination of line segments with various slopes, not a simple straight line, which is different from the process grand composite curve for gas turbine HRSGs. Moreover, the shape of the grand composite curve strongly depends on the flow rate of air and GT exhaust sent to the reformer. Figure 9 illustrates typical grand composite curves of the process streams as well as water stream in the high temperature subsystem under no air input and full air input conditions. As illustrated in Figure 9, if gas turbine exhaust is available and is chosen to supply oxygen exclusively for combustion in the reformer, then the available heat for steam production is much more than that for the full air input condition, in which the oxygen is exclusively provided by air with ambient temperature. Because when gas turbine exhaust is used in the reformer, less process heating is required for feed stream preheating and the saved high quality heat can be utilized for extra steam production. However, as defined in the superstructure, there are potential designs, in which gas turbine exhaust is not available for the reforming process. For example, gas turbine based devices are not selected for power generation, and electric motors as well as combined power plants are selected for mechanical and electrical power generation. Another typical example is that all the available gas turbine exhaust is sent to local HRSGs for steam production, instead of the reforming process. In these cases, air will be the alternative to provide oxygen in the reformer. As shown in Figure 9, the resulting process grand composite is much steeper than the one when gas turbine exhaust is available. Consequently, less steam is produced. Another fact to be noted is that the grand composite curves create potential pinch points not only at the saturated liquid temperature, but also at the outlet temperature of the low temperature watergas shift reactor in this case. So the point at this particular temperature should be included for heat transfer feasibility check. Similar to the procedures made for HRSGs, the feasibility check for heat recovery in the reforming process can be performed by comparing heat flow between the process grand composite and that for the water stream. Although the function 11213



ARTICLE

In the steam methane reforming process, steam is not only required for process heating, but also essential for the reforming reaction. This steam demand is normally specified by a steam carbon ratio, as formulated in eq 65. The steam quality of the feed for reforming reaction depends on the reactor operating pressure. It can be LP steam when the reactor operates below 3 bar(a) or MP steam when operating around 15 bar(a). In eq 65, MP steam is selected. Figure 10. Grand composite curves for the low temperature part of energy system in steam methane reforming.

for calculating heat flow at specified points on the process grand composite is much more complicated than that for HRSGs, it still features a linear formulation of MFuelRFM, MAir, and MExhRFM. Since the process grand composite starts from a temperature much higher than the superheated temperature for VHP steam, the production of VHP steam is always feasible. The amount of steam produced at each pressure level is finally determined by the optimization. As production of high pressure steam is beneficial for power generation, the optimization is likely to prefer solutions with this feature as the best design. As to the low temperature part of the energy system in steam methane reforming, a large amount of process heating is required for feed stream preheating as well as regeneration of the rich amine solvent in the amine absorption process. As the temperature of all streams or segments is not higher than 120 °C, this heating demand could be satisfied by using low pressure steam, produced from gas turbine HRSGs or the heat recovery in steam methane reforming. The shape of the process grand composite is also affected by the amount of air input for the reformer, as illustrated in Figure 10. When gas turbine exhaust is unavailable, air is sent to the reformer for combustion. In this case, more LP steam is required to meet the heating demand, ΔHAllAir, which should be satisfy the air temperature before preheating. If gas turbine exhaust is sufficient and no air is used for combustion, then less LP steam is required for process heating, ΔHNoAir, which corresponds to the reboiler inlet temperature during rich amine regeneration. As formulations for calculating the LP steam consumption have to cover both situations, the LP steam heat load should not be lower than either ΔHAllAir, or ΔHNoAir, as shown in eqs 63 and 64. In these equations, LPHeat is specified to indicate the amount of heat supplied by unit LP steam consumption. And in order to simplify the expression, a function HFLTRFM(MFuelRFM, MAir, MExhRFM, T) is defined to calculate the heat flow at the specified point on the process grand composite. By minimizing overall fuel consumption, the optimizer will be able to identify the minimum LP steam demand for process heating in the CO2 capture process, which will be the bigger heat flow calculated at TInAirPreH and TInReb. MstCPPDemLP 3 LPHeat g HFLTRFMðMFuelRFM, MAir, MExhRFM, T Reb In Þ ð63Þ MstCPPDemLP 3 LPHeat Þ g HFLTRFMðMFuelRFM, MAir, MExhRFM, T AirPreH In ð64Þ

MstCPPDemMP ¼ MNGFeed 3 SCRatio

ð65Þ

When a precombustion decarbonization route is selected for CO2 capture, both steam production through heat recovery as well as steam consumption for process heating and the reforming reaction need to be collectively taken into account in the overall system design. And this will inevitably affect the steam balance in steam mains as formulated in eqs 47 and 48. The heat recovery model presented above is able to compute the amount of steam production in the CO2 capture process, as well as the steam demand incurred by CO2 removal. The interactions between the power system and the CO2 capture process, such as steam exchange, gas turbine exhaust, and fuel allocation, can be fully exploited. The best steam production and resource allocation strategy can be identified after optimization, achieving the maximum overall thermal efficiency. When the iterative approach is followed to carry out the optimization, the natural gas consumption for steam methane reforming is assumed first, and then other stream conditions can be determined by scaling the processing capacity of this process. The energy demand for amine absorption CO2 separation after syngas production is estimated by the same method as illustrated in the postcombustion section. However, different performance parameters might be applied. Oxy-fuel Combustion. In this CO2 capture technology, the additional energy demand incurred by nitrogen removal is mainly the shaft power required for air separation, in which a large air compressor is employed to increase the pressure level of the inlet air flow. It is quite straightforward to integrate this process with the power system design, if the iterative approach is adopted and the air compressor is considered as another shaft power consumer in the power systems. As it is much simpler than the other two CO2 capture routes, oxy-fuel combustion is not illustrated in the case study section. 2.3. Summary. On the basis of the improved power system design model, an iterative approach is proposed to initialize the energy demand for the CO2 capture process during power system design. Performance parameters of CO2 capture processes, specific energy demand for unit CO2 removal, are specified to estimate the additional energy demand incurred by CO2 removal. Although different CO2 capture technologies have their own mechanism and process features, the energy requirements for CO2 removal are classified into three basic demands: process heating, mechanical power, and electricity. With the initially assumed energy consumption in the CO2 capture process, the energy exchange between power systems and CO2 capture processes can be represented by linear equations. Hence, the overall integration problem is modeled with mixed integer linear programming. Particularly, for the precombustion CO2 capture process, a heat recovery module is developed to maximize the benefit of high pressure steam production, leading to high overall thermal efficiency through power and heat cogeneration. As the proposed model for the decarbonised power 11214



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Table 2. Energy Demand for an LNG Production Plant mechanical power compressor C3

MR

stage

demand (kW)

C3-1

2500

C3-2

6960

C3-3

12350

C3-4

32250

MR-1

57640

MR-2

18740

MR-3

27340 42648

electrical power demand (kW) VHP 85 bar(a), 490 °C

steam demand (kg/s)

0

HP 40 bar(a), 390 °C

0

MP 15 bar(a), 280 °C

9.5

LP 3 bar(a), 140 °C

7.3

Table 3. Other Power System Design Parameters parameters equipment

energy loss

Table 4. Performance Parameters for Different CO2 Capture Technologies11,12

maximum number of gas turbine drivers maximum number of steam turbine drivers

value 4 2

maximum number of electric motors

2

maximum number of power plants

2

maximum number of steam turbine generators

2

maximum size of electric motor

60 MW

maximum helper motor size

25% of GT

maximum helper generator size

25% of GT

shaft power required for gas turbine start-up electric motor efficiency

15% of GT 95%

helper generator efficiency

95%

fraction of mechanical transmission loss

1.5%

fraction of electricity distribution loss

2%

fraction of steam distribution loss

2%

system design is able to fully exploit the interactions between the power system and CO2 capture processes, an improved overall thermal efficiency can be achieved. The subsequent case study section is presented to demonstrate the effectiveness of the proposed design methodology and compare the performance of different CO2 capture technologies.

3. CASE STUDY In this section, the mathematical model proposed in this work is applied to the power system design with integration of different CO2 capture strategies, such as no CO2 capture, postcombustion amine absorption, and steam methane reforming followed by amine absorption. A decarbonized power system is designed to support the operation of a LNG production plant, where two refrigeration compressors are involved, each with several numbers of compression stages. The shaft power demand for each compression stage, lumped electricity demand, and the steam demand for process heating are listed in Table 2. Other design parameters are shown in Table 3, including the maximum number and size of equipment as well as the fractions of energy distribution loss.

CO2 removal ratio specific heating demand

postcombustion with

precombustion with

amine absorption

steam methane reforming

85% 4

85% 2.14

(GJ/ton CO2) specific power demand

0.67

0.33

(GJ/ton CO2)

The target of CO2 capture is to remove 85% CO2 emissions. The performance parameters for different CO2 capture technologies are listed in Table 4. Although these parameters may vary due to change of operating conditions in each CO2 capture process, typical values are cited from the literature.11,12 To remove the same amount of CO2, less process heating is required for rich amine solvent regeneration in the precombustion route, compared to the postcombustion route, as the concentration of CO2 in the syngas is above 15% (molar fraction), which is much higher than the one of flue gas around 3% (molar fraction).16 On the other hand, in the precombustion route, syngas for CO2 removal features a high pressure level around 15 bar(a), no blower is required to compress the syngas stream before absorption, contributing to a lower specific power demand compared with the postcombustion route. Thus, these important features of different CO2 capture technologies have been reflected by the performance parameters shown in Table 4. Various CO2 capture strategies have been considered for the synthesis of decarbonised power system, including no CO2 capture, postcombustion amine absorption, and precombustion steam methane reforming followed by amine absorption. Particularly, for CO2 capture with postcombustion amine absorption, different design options have been applied during power system synthesis, and comparisons are made between integrated CO2 capture design and add-on CO2 capture design, multilevel steam production design and single level steam production design. 3.1. Power System Synthesis without CO2 Capture. In this section, a power system is designed without the requirement of CO2 capture. The performance parameters for CO2 capture, such as specific heating demand and specific power demand, have been defined as zero in this case. By following the integrated design methodology, the best solution is obtained after optimization, as shown in Figure 11. In this configuration, four direct drive gas turbines are selected to drive refrigerant compressors. The steam demand for process heating is fully satisfied by heat recovery from gas turbine exhaust. And a steam turbine generator is employed to provide the major proportion of electricity for the background process. The total fuel consumption of this best design without CO2 capture is 415.1 MW on the natural gas LHV basis. There are two things to be discussed further when such a design without CO2 capture is obtained in the synthesis of decarbonised power systems in this study. First, it helps to make a rough estimation of the fuel consumption for decarbonized power systems, which is essential for the iterative design approach. Normally, the best design with CO2 capture consumes 1025% more fuel than the one without CO2 capture. So with the fuel consumption obtained in this case, 415.1 MW, the fuel consumption of a decarbonized power system can be assumed as, for example, 20% more which is 498 MW. 11215



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Figure 11. Best design for power system synthesis without CO2 capture.

Figure 12. Best design for add-on CO2 capture by amine absorption.

With the proposed iterative approach, the actual fuel consumption for decarbonised power systems will be identified after several optimization loops. Second, as an add-on CO2 capture design is to be synthesized in this section, a base case of power systems without CO2 capture is required. And the best design without CO2 capture will be taken as the design basis for add-on CO2 capture. 3.2. Postcombustion CO2 Capture by Amine Absorption. Integrated CO2 Capture Design vs Add-on CO2 Capture Design. Two different design options have been considered for the synthesis of power systems with amine absorption CO2 capture: (i) add-on design and (ii) integrated design. In the add-on design option, a power system is first designed to meet the energy demand for LNG production only. Then another supplementary power system is separately synthesized to satisfy the energy demand incurred by CO2 capture for both the main power systems and the added power systems. Iterations are required to ensure the CO2 produced in the added power

systems is taken into account for CO2 capture. Energy demand for CO2 capture is updated at the beginning of each optimization loop, until the fuel consumption for the added power system is converged. As the main power systems for LNG production has been obtained in the previous design without CO2 capture, only the added power systems need to be synthesized. After the synthesis for the added power systems, the best add-on CO2 capture design is obtained as shown in Figure 12. Besides the original equipment in the best design without CO2 capture, several new power generation devices are introduced to account for the additional energy demand incurred by CO2 capture. An electric motor is employed to satisfy the shaft power demand for the CO2 compressor, blower, and other mechanical power consumers in the amine absorption process. An extra power plant and a steam turbine generator are selected to generate additional electricity to meet the electricity demand for electric motor. Moreover, a boiler is employed to generate LP 11216



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steam, which is essential for rich amine solvent regeneration in the amine absorption process. This supplementary power system consumes 50.5 MW fuel on LP steam production in the boiler and 27.4 MW fuel on MP and LP steam generation by supplementary firing in the HRSG. The total fuel consumption for this added power system is 125.2 MW. So the overall fuel consumpTable 5. Results of Fuel Consumption for Optimization Iterations iterations

FuelAssumed (MW)

FuelActual (MW)

initial assumption at 500 MW 1

500

472.8

2

472.8

466.5

3

466.5

466.4

initial assumption at 415 MW 1

415

465.7

2

465.7

466.4

tion for both the main power system and the added power system is about 540.3 MW. Apparently, in the best add-on design, a great proportion of additional fuel is consumed on steam production without cogenerating power. This feature results in low thermal efficiency of this design. If the steam demand incurred by CO2 capture can be totally satisfied by heat recovery from the gas turbine exhaust with the utilization of heat and power cogeneration, then the overall system thermal efficiency will be considerably improved. For the integrated design option, the power system is synthesized with simultaneous consideration of CO2 capture. Following the proposed iterative approach, the minimum fuel consumption for the overall decarbonised power system is identified at 466.4 MW after several optimization iterations. No matter what initial assumption is made for the overall fuel consumption, higher or lower than 466.4 MW, the iterations of optimization always converge at this minimum fuel consumption. Table 5 shows the optimization results for all iterations when starting from the fuel consumption assumption at 500 and 415 MW. The monotonic behavior of the convergence process implies computational

Figure 13. Best design for integrated CO2 capture by amine absorption.

Figure 14. Best design for integrated CO2 capture by amine absorption (decoupled CO2 compressor allocation). 11217



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robustness and effectiveness of optimization approach proposed in this work. The configuration of the best design with integrated CO2 capture by amine absorption is shown in Figure 13. Compared with the best design without CO2 capture, larger power generation equipment is selected to account for additional energy demand for CO2 capture. The CO2 compressor is driven by a common direct drive gas turbine, together with some refrigerant compressor stages. And the LP steam demand for CO2 capture is about 40.6 kg/s, which is fully satisfied by heat recovery from gas turbine exhaust. About 28.7 MW of electricity is produced by steam turbine generators through heat and power cogeneration. As the interactions between the power system and the CO2 capture process have been fully investigated from systemwide process synthesis, compared with the best add-on design, the fuel consumption is significantly reduced by 13.6%. However, there are also structural drawbacks of this best design when reliability issues are taken into consideration. As the CO2 compressor is sharing the same gas turbine driver with other refrigerant compressors, when any operation problem arises in the CO2 capture process, CO2 compressor failure will directly affect the normal operation of the entire drive shaft, posing a high risk for LNG production. So, in order to improve system reliability of the design, the CO2 compressor is desired to be separately driven apart from refrigerant compressors. In such a decoupled structure, the conditions of CO2 compressor will not affect the operation of refrigerant compressors, thus, leading to enhanced overall system reliability. The best design with Table 6. Result Summary for Power System Synthesis with Amine Absorption design strategy

fuel consumption (MW)

net efficiency

no CO2 capture

415.1

57.03%

add-on CO2 capture

540.3 (32.5% increase)

43.81%

integrated CO2 capture

466.4 (12.36% increase)

50.76%

integrated CO2 capture

467.7 (12.67% increase)

50.62%

(decoupled CO2 compressor allocation)

decoupled CO2 compressor allocation strategy is shown in Figure 14. Different from previous integrated design, the CO2 compressor is separately driven by a steam turbine driver. And a power plant is chosen for the provision of electricity to the background process and helper motors. The total fuel consumption of this best decoupled design is 467.7 MW. Although the requirement of decoupled CO2 compressor allocation results in slight higher fuel consumption, the improved system reliability outweighs this penalty and makes it an attractive design option for real industrial practice. The optimization results for different design options have been summarized in Table 6, in which the overall net energy efficiency is defined by the ratio between useful energy for LNG production and overall fuel consumption. It should be noted that, in this case study, although performance parameters (i.e., 4 GJ process heating and 0.67 GJ shaft work per ton of CO2 removal) for the amine absorption process have been selected from the previous research,12 these case-specific parameters can be adjusted for other CO2 capture process operating scenarios. From Table 6, it can be seen that the CO2 removal causes a large energy penalty to power systems. The fuel consumption will be increased by 32.5% when a supplement power system is synthesized for an add-on CO2 capture process separately from the main one for LNG production. However, if the proposed systematic methodology is followed to exploit the interactions between power systems and CO2 capture processes, less energy penalty is incurred, and the overall net energy efficiency can be improved. With integrated CO2 capture for power system synthesis, the energy penalty for CO2 removal is reduced to 12.36%. Moreover, when decoupled CO2 compressor allocation is preferred to enhance system reliability, there is only a slight increase in fuel consumption. Multiple Levels vs Single Level for Steam Production in HRSGs. In order to investigate the benefit from multilevel steam production in HRSGs, a single level steam production scheme in the previous approach15 is also applied for the power system design with amine absorption CO2 capture. In this scheme, all the HRSGs are only allowed to produce the steam of a single pressure level through heat recovery from gas turbine exhaust,

Figure 15. Best design for integrated CO2 capture by amine absorption (single level steam production). 11218



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Figure 16. Best design for integrated CO2 capture by steam methane reforming.

Table 7. Performance Comparison between Multilevel Steam Production and Single Level Steam Production Designs steam production scheme fuel consumption (MW) net energy efficiency useful heat recovery ratio

single pressure level 487.4 48.6% 77.7%

Table 8. Optimization Results for Power Systems with Different CO2 Capture Technologies amine absorption

steam methane reforming

CO2 capture technology

postcombustion

precombustion

fuel consumption (MW) net energy efficiency

466.4 50.8%

484.7 (3.9% increase) 48.5%

multiple pressure levels 466.4 (4.3% reduction) 50.8% 97.8%

Figure 17. Grand composite curves for heat integration within the steam methane reforming process.

and its steam pressure for each HRSG is optimally selected by optimization. The best design obtained with single level steam production is shown in Figure 15. In the configuration, only HP steam is produced in HRSGs for power generation through steam turbines. However, this single-level steam production scheme results in a low heat recovery ratio from gas turbine exhaust. Actually, about 51 MW of useful heat was not recovered for MP and LP steam production. This waste of energy inevitably results in a comparatively low system thermal efficiency. Table 7 summarizes the key performance of both multilevel steam production design and single level steam production

design. As the multiple pressure level steam production significantly improves the heat recovery from gas turbine exhaust, with 97.8% of useful heat recovered for HP, MP, and LP steam production, the system efficiency is enhanced and, accordingly, fuel consumption is reduced by 4.3%. 3.3. Precombustion CO2 Capture by Steam Methane Reforming. The power system with CO2 capture through steam methane reforming is also synthesized with the proposed methodology. The reforming reactor operates at 15 bar(a) and produces a syngas product at 870 °C. Then, the syngas stream is cooled to 350 °C for high temperature watergas shift. As the reaction is exothermic, the temperature of the syngas stream increases to 434 °C at the reactor outlet. After cooled to 200 °C, the syngas stream enters the low temperature watergas shift reactor. The outlet temperature of the syngas stream is 241 °C after the reaction. Before being sent to the CO2 separation unit, the syngas stream is required to be cooled to 35 °C. The whole steam methane reforming process is simulated in ASPEN HYSYS to obtain thermodynamic data of process streams, such as enthalpy change and heat capacity of process streams, which are essential for the construction of the process grand composite curve. In the process simulation, both watergas shift reactors are assumed to be adiabatic and pressure drops along the process have been neglected. After syngas production by steam methane reforming, an amine absorption process is followed to separate CO2 content from other components. The CO2-rich stream to be treated has a molar CO2 concentration around 18% and a pressure around 15 bar(a), and therefore, the performance parameters for amine absorption are quite different from those for postcombustion 11219



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Table A1. List of Direct Drive Gas Turbine Models manufacturer

type

model

output [kW]

cost [k$]

heat rate [kJ/(kW 3 h)]

exhaust flow rate [kg/s]

exhaust temperature [°C]

GE

aeroderivative

LM1600PA

14320

6500

9750

46.7

488

GE

aeroderivative

LM2500PE

23270

7800

9587

69

523

GE

aeroderivative

LM6000

44740

12500

8460

127

456

GE

industrial

M3142J

11290

3345

13440

53

542

GE

industrial

MS5002D

32590

7900

11898

141.3

510

GE

industrial

M5261RA

19690

5200

13270

92

531

GE

industrial

M5382C

28340

6900

12310

126

515

GE GE

industrial industrial

M6511B M6581B

37810 38290

10200 10300

11120 11060

130.2 134

547 545

GE

industrial

M7111EA

81560

17300

11021

278.5

547

GE

industrial

M7121EA

86230

18400

10922

298.9

537

Rolls-Royce

aeroderivative

COBERRA6562

25930

7300

9472

94.5

492

Rolls-Royce

aeroderivative

COBERRA6761

32590

8300

8961

94.1

505

Rolls-Royce

aeroderivative

Trent

52549

12900

8349

152.13

444

exhaust flow rate [kg/s]

exhaust temperature [°C]

Table A2. List of Simple Cycle Power Plants manufacturer

type

model

output [kW]

cost [k$]

heat rate [kJ/kWh]

GE

aeroderivative

GE

aeroderivative

LM1600PA_g

13750

8000

10153

46.7

488

LM2000

18000

7950

9892

63

474

GE GE

aeroderivative aeroderivative

LM2500PE_g LM6000PC

22800 42665

11000 14100

9783 8779

69 126

523 451

GE

aeroderivative

LM6000PD

42227

15000

8698

125

449

GE

industrial

PG5371PA

26300

7680

12649

122.5

487

GE

industrial

PG6581B

42100

14500

11223

145.8

543

GE

industrial

PG6101FA

70140

22000

10529

198.2

597

GE

industrial

PG7121EA

85400

21000

10993

291.7

537

GE

industrial

PG7241FA

171700

41000

9873

445.8

604

GE GE


PG9171E PG9231EC

123400 169200

25600 34550

10656 10305

403.7 519.7

538 557

GE

industrial

PG9351FA

255600

49500

9757

643.9

608

Siemens

industrial

W251B1112

49500

13900

11024

175.1

514

Siemens

industrial

V643A

67000

20400

10371

191

589

Siemens

industrial

W501D5A

120500

25500

10381

385.1

525

Siemens

industrial

V942

157000

29890

10466

Siemens

industrial

W501F

186500

40000

9632

508.9

537

460

590

Siemens Siemens


V942A W501G

190000 253000

36100 47800

10227 9241

519.8 562.9

585 594

Siemens

industrial

V943A

265000

Rolls-Royce

aeroderivative

Trent

51190

51400

9347

655.9

584

15500

8662

159.21

427

CO2 capture, in which CO2 content has a very low concentration around 3%, as well as low partial pressure. In this case, the specific heating demand for solvent regeneration is chosen at 2.14 GJ/ton CO2.8 As no blower is required due to the high supply pressure, only 0.33 GJ/ton CO2 of shaft work will be required by the CO2 compressor.9 The heat recovery strategies developed in this research have been applied to fully utilize available heat from the gas turbine exhaust and to optimize QJ; the distribution of heat exchange between HRSGs and the reformer. The configuration of the best design with integrated CO2 capture by steam methane reforming is illustrated in Figure 16. In

this best design, the exhaust from gas turbines is not only used for heat recovery in HRSGs for steam production but also sent to the CO2 capture process for provision of oxygen during hydrogenrich fuel combustion in the steam methane reformer. And a considerable amount of steam has been produced by exploring heat integration opportunities between process streams in the steam methane reforming process and boiler feedwater. Grand composite curves for both process streams and steam have been shown in Figure 17, giving more detailed information on heat exchange between them. A large fraction of exhaust heat has been used for VHP steam production, and the rest of the available heat is recovered mainly for MP and LP steam production. 11220



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Table A3. List of Combined Cycle Power Plants manufacturer

type

model

output

cost

heat rate

[kW]

[k$]

[kJ/kWh]

GE

CCGT

S106B

64300

20700

7340

GE

CCGT

S106FA

107100

39100

6794

GE

CCGT

S107EA

130200

35000

7174

GE

CCGT

S206B

130700

37500

7227

GE

CCGT

S109E

189200

45000

6931

GE

CCGT

S206FA

217000

52650

6704

GE GE

CCGT CCGT

S107FA S207EA

262600 263600

57950 57875

6425 7068

Siemens

CCGT

GUD1S-643A

100000

36850

6868

Siemens

CCGT

GUD2643A

202000

48985

6815

Siemens

CCGT

GUD1-V942

232500

53200

6995

Siemens

CCGT

GUD1S843A

260000

56950

6309

Siemens

CCGT

GUD1S-942A

293500

57965

6520

Siemens

CCGT

1-W251B

71500

24600

7533

Siemens Siemens

CCGT CCGT

2-W251B 1-W501F

143500 273500

43600 56985

7501 6489

developed to exploit heat integration opportunities between the steam methane reforming process and power systems. Heat sources in the steam methane reforming process are encouraged to produce high pressure steam, creating opportunities for heat and power cogeneration. On the other hand, the gas turbine exhaust is considered as an alternative source for oxygen supply in the reformer during combustion, saving hydrogen-rich fuel. Such systematic investigation of design interactions between power systems and CO2 capture processes allows to identify better heat integration opportunities and to achieve significantly improved energy efficiency of the overall energy systems.

’ APPENDIX Appendix A: List of Gas Turbines and Power Plants. Tables A1, A2, and A3 list the direct drive gas turbine models, simple cycle power plants, and combined cycle power plants, respectively. Appendix B: Steam Methane Reforming Process. Figures B.1B.3 and Tables B1B7 give details of the steam methane reforming process.

’ AUTHOR INFORMATION Corresponding Author

The optimization results for both precombustion and postcombustion CO2 capture technologies are summarized in Table 8. It can be seen that power systems with steam methane reforming process requires more fuel. Although the specific energy demand for CO2 separation from the syngas product is comparatively low, the external heating requirement for the reforming reaction is so large that about 23.7% of the produced hydrogen-rich fuel is combusted in the reformer for the syngas production. As an overall effect, the fuel consumption of the best design with integrated CO2 capture by steam methane reforming is 3.9% more than that for the postcombustion design. All the above decarbonized power system designs were obtained by solving the models formulated in GAMS and solver CPLEX (v.7.0) has been selected for solving this MILP problem.17 The overall optimization normally took about 10 min for about 34 iterative optimization runs in 1.4 GHz Pentium 4 processor.

4. CONCLUSIONS The synthesis of power systems is a very complicated task, involving many design variables and combinatorial decision making on equipment selection. The problem becomes more complex when CO2 capture processes are to be integrated with power systems, as the overall energy demand is unknown at the design stage. In this research, a holistic approach has been presented to improve energy efficiency of decarbonised power systems, and an improved energy recovery has been implemented to maximize the heat recovery from gas turbine exhaust for multilevel steam production. From the case study, it has been clearly demonstrated that integration between power systems and CO2 capture processes is able to improve the overall system efficiency by reducing the energy penalty caused by CO2 capture. Introduction of multilevel steam production can create more opportunities for heat recovery, hence enhancing the overall system performance. Moreover, for precombustion CO2 capture with steam methane reforming, a systematic heat recovery module has been

*Tel.: +82 2 2220 2331. E-mail: [email protected]. Present Addresses §

Process Integration Limited, One Central Park, Central Park, Northampton Road, Manchester, M40 5BP, U.K.

’ NOMENCLATURE Indices

C = refrigeration compressor CKPnt = check points for heat transfer feasibility inspection in the HRSG CS = compressor stage T = time period DDGT = gas turbine shaft DDGTOP = gas turbine option (actual model) EM = electric motor shaft Lv = steam pressure level PP = power plant place PPOP = power plant option (actual model) SCPPOP = simple cycle power plant option (actual model) Abbreviation

SF = supplementary firing NoSF = no supplementary firing VHP = very high pressure (steam header) HP = high pressure (steam header) MP = medium pressure (steam header) LP = low pressure (steam header) Parameters

ΔhExp = specific enthalpy change during steam expansion (kJ/kg) ΔhSTM = specific enthalpy change during steam production (kJ/kg) ΔTmin = minimum temperature approach allowed (°C) λUB = maximum load ratio for power generation equipment λLB = minimum load ratio for power generation equipment AnnuFact = annualised factor (1/y) BED = basic electricity demand; electricity for helper or main electric motors is not included (kW) 11221



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Figure B.1. Process flow diagram of the steam methane reforming (reformer).

Figure B.2. Process flow diagram of the steam methane reforming (watergas shift).

Figure B.3. Process flow diagram of the steam methane reforming (water removal).

BoilerEff = steam boiler efficiency CDDGTOP = cost of gas turbine options (k$) CPExh = heat capacity of gas turbine exhaust (kJ/kg 3 °C) CPPOP = cost of power plant options (k$) CRC0 = reference cost of compressors (k$) CSSize = size of compressor stages (kW) ELoss = fraction of electricity loss in electrical power distribution EMCost0 = reference cost of electric motors (k$) EMEff = electric motor efficiency EMSize0 = reference size of electric motors (kW) HGEff = helper generator efficiency HMEff = helper motor efficiency

HMGCost0 = reference cost of helper motors and generators (k$) HMGSize0 = reference size of helper motors and generators (kW) HRDDGTop = heat rate of a specified gas turbine model (kJ/kW 3 h) HRPPop = heat rate of a specified power plant model (kJ/kW 3 h) IR = interest rate LIFE = plant life (y) LPHeat = available heat from unit LP steam supply (kJ/kg) MaxEExp = maximum electricity export (kW) MaxEFF = maximum amount of available end flash fuel (kW) MaxEImp = maximum electricity import (kW) MaxHMGUB = maximum shaft power output for helper motors for the gas turbine shaft (kW) 11222



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Table B1. Natural Gas Composition component

Table B5. Syngas Composition after WaterGas Shift molar fraction

molar fraction

CH4

0.93

C2H6

0.05

C3H8

0.015

H2O

0.2197

0.186

0.005

CH4

0.0225

0.0225

H2

0.5952

0.6289

CO

0.0386

0.0049

CO2

0.1238

0.1575

C2H6

0.00017

0.00017

C3H8

0.00005

0.00005

C4H10

0.00002

0.00002

C4H10

component high temperature shift product low temperature shift product

Table B2. Stream Conditions in the Steam Methane Reforming Process (Reformer) flow rate (kg/s)

stream name natural gas fuel

T (°C)

9.77

preheated NG

P (bara)

35

15

9.77

580

15

MP steam from power system

30.25

280

15

preheated MP steam

30.25

580

15

syngas from reformer

40.02

870

15

reaction heat (MW)

145

Table B6. Stream Conditions in the Steam Methane Reforming Process (Water Removal) stream name

flow rate (kg/s)

T (°C)

P (bara)

syngas for water removal

40.02

35

15

syngas for CO2 removal

29.07

35

15

Table B3. Syngas Composition after Steam Methane Reforming component

Table B7. Syngas Composition after Water Removal

molar fraction

component

molar fraction

H2O

0.2923

CH4

0.0225

H2O

0.0041

H2

0.5225

CO

0.1112

CH4 H2

0.0276 0.7695

CO2

0.0512

CO

0.006

0.00017

CO2

0.1925

0.00005

C2H6

0.0002

0.00002

C3H8

0.00006

C4H10

0.00002

C2H6 C3H8 C4H10

Table B4. Stream Conditions in the Steam Methane Reforming Process (WaterGas Shift) flow rate (kg/s)

T (°C)

P (bara)

HT shift feed

40.02

350

15

HT shift product

40.02

434

15

LT shift feed LT shift product

40.02 40.02

200 241

15 15

stream name

MaxMExh = maximum exhaust flow rate of all gas turbine models (kg/s) MaxNoSTD = maximum number of steam turbine drivers MaxNoSTG = maximum number of steam turbine generators MaxWEM = maximum size of electric motors (kW) MaxWSTD = maximum output of steam turbine drivers (kW) MaxWSTG = maximum output of steam turbine generators (kW) MExhDDGT = exhaust flow rate of a specified DDGT model (kg/s) MExhSCPP = exhaust flow rate of a specified SCPP model (kg/s) MLHV = mass lower heating value (kJ/kg) MLoss = fraction of shaft power loss in mechanical transmission MstProDem = steam demand of background processes (kg/s)

MstProGen = steam production of background processes (kg/s) MWFuel = molar weight of hydrogen rich fuel (kg/mol) NCAS0 = reference number of compressor casings NCS = number of compressor stages OprTime = total operation time in the whole time span (h/y) PCAS = factor of cost penalty per additional compressor casing PowPPOPPPop = electrical power output for a specified power plant model (kW) PT = length of time period, defined by a fraction of the total time span QFuelCmb = heat release during hydrogen rich fuel combustion (kJ/mol) QRFM = heat required for steam methane reforming (kW) QDDGTOPMax = fuel consumption when gas turbine options operate with maximum shaft power output (kW) QPPOPPPOP,TMax = fuel consumption when power plant options operate with maximum power output (kW) SCRatio = steam carbon ratio for steam methane reforming SHDemCPP = specific heating demand for CO2 capture (GJ/ton CO2) SWDemCPP = specific power demand for CO2 capture (GJ/ton CO2) SLoss = steam loss fraction during steam distribution 11223


Industrial & Engineering Chemistry Research T = temperature (°C) TSupVHP = temperature of superheated VHP steam (°C) TExhDDGTop = exhaust temperature of a specified gas turbine model (°C) TExhSCPPop = exhaust temperature of a specified simple cycle power plant model (°C) TSF = exhaust temperature after supplementary firing in HRSG (°C) UCEExp = unit cost of electricity export (k$/kW 3 h) UCEFF = unit cost of end flash fuel (k$/kW 3 h) UCEImp = unit cost of electricity import (k$/kW 3 h) UCFF = unit cost of fresh fuel (k$/kW 3 h) WDDGTOPMax = maximum shaft power output for gas turbine options (kW) WDDGTOPMin = minimum shaft power output for gas turbine options (kW) WHGExDDGTOP = maximum excessive output for helper generators over the start-up requirement (kW) WHMExDDGTOP = maximum excessive output for helper motors over the start-up requirement (kW) WHMGUB = upper bound of shaft power output for helper motors and generators (kW) WCSCS = shaft power demand for each compressor stage (kW) WRC0 = reference size of compressors (kW) WSMDDGTOP = shaft power requirement for start-up of gas turbine options (kW) Continuous Variables

CCAP = annualized capital cost (k$/y) CDDGT = total cost of gas turbine drivers (k$) CELEC = electricity cost per year (k$/y) CEM = total cost of electric motors (k$) CFUEL = fuel cost per year (k$/y) CHMG = total cost of gas turbine starters/helper devices (k$) CPP = total cost of power plants (k$) CRC = total cost of refrigerant compressors (k$) DFst = inlet steam flow rate of decomposed single stage steam turbine (kg/s) DFstSTD = inlet steam flow rate of decomposed single stage steam turbine used as drivers (kg/s) DFstSTG = inlet steam flow rate of decomposed single stage steam turbine used for generating electricity (kg/s) EExp = amount of electricity export (kW) EImp = amount of electricity import (kW) EMCost = electric motor cost on each motor shaft (k$) EMSize = electric motor size on each motor shaft (kW) Fst = extraction steam flow rate for steam turbines (kg/s) HFDDGTExh = heat flow of DDGT exhaust at specified checking point (kW) HFDDGTStm = heat flow of steam at specified checking point (kW) HFSCPPExh = heat flow of SCPP exhaust at specified checking point (kW) HFSCPPStm = heat flow of steam at specified checking point (kW) HMGCost = helper motor or generator cost on each gas turbine shaft (k$) HMGSize = helper motor or generator size on each gas turbine shaft (kW) MCO2Rem = flow rate of CO2 for removal (ton/s) MExhHRSG = mass flow rate of exhaust sent to HRSG (kg/s) MExhRFM = mass flow rate of exhaust sent to steam methane reformer (kg/s)

ARTICLE

MFuelRFM = mass flow rate of hydrogen rich fuel combusted in steam methane reformer (kg/s) MNGFEED = natural gas consumption for steam methane reforming (kg/s) MstBoiler = flow rate of steam produced in boilers (kg/s) MstCPPDem = steam demand of CO2 capture processes (kg/s) MstCPPGen = steam production in CO2 capture processes (kg/s) MstHRSG = flow rate of steam produced in HRSG (kg/s) MstLetDown = flow rate of steam let down at steam mains (kg/s) NCAS = number of compressor casings NCSDDGT = number of compressor stages belonging to the same compressor on each gas turbine shaft NCSEM = number of compressor stages belonging to the same compressor on each electric motor shaft NDDGTS = number of gas turbine shafts driving compressor stages belonging to the same compressor NEMS = number of electric motor shafts driving compressor stages belonging to the same compressor PowDSTG = electrical power generated by decomposed single stage steam turbine generator (kW) PowEM = electrical power consumption of electric motors (kW) PowHG = electrical power generation of helper generators (kW) PowHM = electrical power consumption of helper motors (kW) PowPP = electrical power generation of power plants (kW) PowSTG = electrical power generated by a multistage steam turbine generator (kW) QB = fuel consumption of boilers (kW) QCPP = fuel consumption in CO2 capture processes (kW) QDDGT = fuel consumption of gas turbine drivers (kW) QDDGTOP = fuel consumption of gas turbine options (kW) QEFF = end flash fuel consumption (kW) QFF = fresh fuel consumption (kW) QPP = fuel consumption of power plants (kW) QPPOP = fuel consumption of power plant options (kW) QSFHRSG = fuel consumption for supplementary firing in HRSG (kW) QTotal = total fuel consumption (kW) TCOST = total annualized cost (k$/y) WCPP = shaft power demand from CO2 capture processes (kW) WDDGT = shaft power output of gas turbine drivers (kW) WDDGTOP = shaft power output of gas turbine options (kW) WDDGTSD = total shaft power demand on gas turbine shafts (kW) WDSTD = shaft power generated by decomposed single stage steam turbine driver (kW) WEM = shaft power output of electric motors (kW) WEMSD = total shaft power demand on electric motor shafts (kW) WHG = actual output of helper generators (kW) WHGEx = excessive output of helper generators over the start-up requirement (kW) WHM = actual output of helper motors (kW) WHMEx = excessive output of helper motors over the start-up requirement (kW) WSTD = total shaft power output of a multistage steam turbine (kW) WSTDSD = total shaft power demand on steam turbine shafts (kW) Binary Variables

YDDGTC = indicates whether gas turbine shaft DDGT is supplying power to compressor C YDDGTCS = Indicates whether gas turbine shaft DDGT is supplying power to compressor stage CS 11224


Industrial & Engineering Chemistry Research YDDGTOP = indicates whether the gas turbine option DDGTOP (actual model) is selected to drive the gas turbine shaft DDGT YEExp = to allow or not allow exporting electricity YEM = indicates whether electric motor EM is active YEMCS = indicates whether electric motor shaft EM is supplying power to compressor stage CS YEMC = indicates whether electric motor shaft EM is supplying power to compressor C YHM = existence of continuous helper motor on gas turbine shaft DDGT YPPOP = indicates whether the power plant option PPOP (actual model) is selected to occupy the power plant place PP YSF = indicates whether the specified heat recovery steam generator applies supplementary firing YSTD = indicates whether the steam turbine driver at pressure level Lv is selected YSTDCS = indicates whether steam turbine shaft STD is supplying mechanical power to compressor stage CS YSTG = indicates whether the steam turbine generator at pressure level Lv is selected YVHP = indicates whether the specified heat recovery steam generator produces VHP steam

ARTICLE

(14) Lozza, G.; Chiesa, P. Natural Gas Decarbonization to Reduce CO2 Emission From Combined Cycles—Part II: Steam-Methane Reforming. J. Eng. Gas Turbines Power 2002, 124, 89. (15) Del Nogal, F. L. Optimal design and integration of refrigeration and power systems. PhD thesis, Centre for Process Integration, The University of Manchester, UK, 2006. (16) Freguia, S.; Rochelle, G. T. Modelling of CO2 Capture by Aqueous Monoethanolamine. AIChE J. 2003, 49, 1676. (17) Brooke, A.; Kendrick, D.; Meeraus, A.; Raman, R.; Rosenthal, R. GAMSA user’s guide; GAMS Development Corporation: Washington, DC, 1998.

SOS2 variables

LDDGTWQ(i) = linearization of gas turbine performance variation under part load operation LPPPowQ(i) = linearization of power plant performance variation under part load operation

’ REFERENCES (1) Papoulias, S. A.; Grossmann, I. E. A structural optimization approach in process synthesis - I utility systems. Comput. Chem. Eng. 1983, 7, 695. (2) Hui, C. S.; Natori, Y. An industrial application using mixedinteger programming technique: a multi-period utility system model. Comput. Chem. Eng. 1996, 20, S1577. (3) Iyer, R. R.; Grossmann, I. E. Synthesis and operational planning of utility systems for multiperiod operation. Comput. Chem. Eng. 1998, 22, 979. (4) Shang, Z.; Kokossis, A. A systematic approach to the synthesis and design of flexible site utility systems. Chem. Eng. Sci. 2005, 60, 4431. (5) Marechal, F.; Kalitventzeff, B. Targeting the integration of multiperiod utility systems for site scale process integration. Appl. Therm. Eng. 2003, 23, 1763. (6) Del Nogal, F. L.; Townsend, D. W.; Perry, S. J. Synthesis of power systems for LNG plants. GPA Europe Spring Meeting, Bournemouth, UK, 2003. (7) Marechal, F.; Kalitventzeff, B. Identification of the optimal pressure levels in steam networks using integrated combined heat and power method. Chem. Eng. Sci. 1997, 52, 2977. (8) Petroulas, T.; Reklaitis, G. V. Computer-aided synthesis and design of plant utility systems. AIChE J. 1984, 30, 69. (9) Steeneveldt, R.; Berger, B.; Torp, T. A. CO2 capture and storage closing the KnowingDoing gap. Chem. Eng. Res. Des. 2006, 84, 739. (10) Herzog, H. J.; The economics of CO2 capture. Proceedings of the Fourth International Conference on Greenhouse Gas Control Technologies, Interlaken, Switzerland, August 30September 2, 1998; Eliasson, 1999. (11) Corradetti, A.; Desideri, U. Analysis of Gas-Steam Combined Cycles with Natural Gas Reforming and CO2 Capture. J. Eng. Gas Turbines Power 2005, 127, 545. (12) Bolland, O.; Undrum, H. A novel methodology for comparing CO2 capture options for natural gas-fired combined cycle plants. Adv. Environ. Res. 2003, 7, 901. (13) Lozza, G.; Chiesa, P. Natural Gas Decarbonization to Reduce CO2 Emission From Combined Cycles—Part I: Partial Oxidation. J. Eng. Gas Turbines Power 2002, 124, 82. 11225


Optimization of Power-Intensive Energy Systems with Carbon Capture

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