Development of a Scalable and Comprehensive Infrastructure

ARTICLE pubs.acs.org/IECR

Development of a Scalable and Comprehensive Infrastructure Model for Carbon Dioxide Utilization and Disposal Jee-Hoon Han and In-Beum Lee* Department of Chemical Engineering, POSTECH, Pohang, KOREA ABSTRACT: Much of the previous research on carbon capture and storage (CCS) has focused on individual technologies for disposing of CO2, such as capture, storage, sequestration, or transport. Moreover, recent research work considers utilization of CO2 as fuels, chemicals, or nutrients for bioreactors. To efficiently manage CO2 and the economic benefits achieved by this process, the CO2 transport and processing infrastructure supporting CCS will have to be constructed at a macro-scale. This paper introduces a scalable and comprehensive infrastructure model for CO2 utilization and disposal that generates an integrated, profit-maximizing CCS system. The proposed model determines where and how much CO2 to capture, store, transport, utilize or sequester to maximize total annual profit while meeting the CO2 mitigation target. The applicability of the proposed model is demonstrated using a case study for treating CO2 emitted by an industrial complex on the eastern coast of Korea in 2020. The results may be important in systematic planning of a CCS infrastructure and in assisting national and international policy makers to determine investment strategies for developing CCS infrastructures.

1. INTRODUCTION Anthropogenic CO2 emission is a major contributor to climate change. This emission is mainly due to fossil fuel combustion by the power generation, industrial, and transport sectors (Figure 1).1 Developing countries, such as China, India, and Korea, are among the countries with the fastest-growing energy demands.2 Achieving sustainable development in such countries will require a drastic reduction in CO2 emissions. Using rapid carbon capture and storage (CCS) technologies to reduce CO2 emissions will likely be a major part of the solution to reducing atmospheric CO2 buildup.2 According to the International Energy Agency, by 2050, CCS technologies will contribute about 19% of key technologies for reducing CO2 emissions, and if CCS technologies are not used, the reduction cost of CO2 will increase 70% by 2050.3 CCS technologies separate CO2 from industrial and energyrelated sources, transport them to a storage location, and isolate them from the atmosphere for a long period. CCS can be classified into capture, storage, transport, and sequestration technologies. Capture technology separates CO2 from the flue gases produced by combustion of fossil fuels. Storage technology stores liquid CO2 in large steel tanks above ground, or loads it into ship at harbors. Transport technology delivers captured CO2 to a sequestration site. Sequestration technology stores CO2 in geological or marine reservoirs for long periods of time. CCS technologies to dispose of CO2 should consider geopolitical factors such as the location and capacity of the sequestration site, and must solve problems of geological security and environmental sustainability. New CCS technologies to utilize (recycle) CO2 as usable fuels, chemicals, or nutrients for bioreactors have economic and environmental benefits.2 CO2 transport cost strongly depends on the distance and the amount moved.4 The costs of pipelines depend on whether the pipeline is onshore or offshore, and on the CO2 mass flow rate. Marine transportation is typically cheaper than pipelines for distances greater than ∼1000 km and for amounts smaller than a few million r 2011 American Chemical Society

Figure 1. CO2 emissions from combustion of fossil fuels.

tonnes of CO2 per year. Thus, standardization of the characteristics of CO2 is necessary to transport and store large amounts of it, because large-scale CCS brings considerable economic benefits. Also, to efficiently manage CO2 on a macro-scale (e.g., a national industrial complex), constructing a scalable and comprehensive CCS infrastructure using all CCS technologies for CO2 disposal and utilization is positively necessary. Past research efforts were directed toward analyzing individual subprocesses (e.g., utilization, capture, storage, sequestration or transport) of technologies within the CCS infrastructure. Rao and Rubin economically evaluated CCS in power plants with equipped with monoethanolamine CO2 capture systems.5 McCollum and Ogden provided techno-economic model equations for estimating Received: November 9, 2010 Accepted: April 4, 2011 Revised: March 30, 2011 Published: April 04, 2011 6297

dx.doi.org/10.1021/ie200344t | Ind. Eng. Chem. Res. 2011, 50, 6297–6315

Industrial & Engineering Chemistry Research

ARTICLE

Figure 2. Schematic diagram of CO2 infrastructure.

equipment size and the costs of compression, pipeline transport, and injection and storage of CO2.6 Recently, however, attention has increasingly focused on the design and operation of the CCS infrastructure as a whole due to the large economic benefits achieved by this process. Middleton and Bielicki evaluated costs for a complete and integrated CCS system by analyzing a realistic and efficient pipeline network to connect spatially dispersed CO2 sources and reservoirs.7 Broek et al. compared the cost-effectiveness of CCS and CO2 storage in a very large formation under the North Sea to that in a smaller nearby formations in The Netherlands.8 The previous studies did not consider all physical forms of CO2 and only considered CO2 to be transported using a single transport mode such as pipeline. Moreover, few studies have considered utilization of CO2 within CCS. Therefore, the key features of this paper are that we expanded CCS modeling to consider utilization and disposal of CO2 and considered all methods of treating CO2 in all of its physical forms. The objective of this paper is to develop a model that suggests the optimal design of the infrastructure required to treat CO2 on the east coast of Korea in 2020, and to examine the applicability of the CCS infrastructure design model for this type of problem. The proposed mathematical model will outline all possible architectures of future CCS infrastructures and the optimal profit of the system, before they are developed in practice.

2. PROBLEM DESCRIPTION The proposed scalable and comprehensive CCS infrastructure model for CO2 utilization and disposal consists of capture facilities, transport modes, storage facilities, sequestration facilities and utilization facilities. The model is used to establish and investigate a number of strategic decisions required to fulfill the mandated reduction of CO2 emissions. These decisions include determination of: (i) the number, location, type and capacity of CO2 capture, storage, sequestration, and utilization facilities; (ii) the total amount of capture, storage, sequestration and utilization of CO2 in each region considered; and (iii) the size and type of transport. The model also maximizes the total annual profit of the CCS infrastructure while considering these decisions. Based upon these considerations, a CCS infrastructure was designed (Figure 2) which consists of a CO2 utilization network and a CO2 disposal network.

The networks for CCS infrastructure are assumed to operate at steady-state conditions in which CO2 emissions are constant over time. The network described by the model is demanddriven, which means that the establishment of capture facilities, storage facilities, sequestration facilities, utilization facilities and transport links depend mainly on CO2 emissions. However, to design a realistic configuration, a CCS infrastructure model must consider the time variance of CO2 emission and the emission reduction target. A multiperiod model will be considered in future work. Also, the following capital charge rates associated with the network investment were assumed: (i) for capture facilities, storage facilities, sequestration facilities and utilization facilities, 0.148 with a 30-year plant lifetime and a 14.8% discount rate;9 (ii) for tanker railcar and tanker truck transport modes, 0.163 with a 10-year lifetime and a 10.0% discount rate;10 and (iii) for pipelines and tanker ship transport modes, 0.148 with a 20-year lifetime and a 13.9% discount rate.11 The network design is formulated as a mixed-integer linear programming (MILP) problem.

3. MATHEMATICAL MODEL FORMULATION The mathematical formulation of the CCS infrastructure model will be presented as an objective function and several constraints. 3.1. Objective Function. The aim of the proposed model is to maximize the total annual profit TAP of the CCS infrastructure; TAP is the difference between total annual benefit TAB and total annual cost TAC max TAP ¼ TAB TAC

ð1Þ

The benefit and cost terms that are used to estimate the overall profit of the CCS infrastructure are discussed in detail in subsequent sections. 3.1.1. Total Annual Benefit. TAB is associated with the income from selling products made by utilizing CO2. It is calculated by multiplying the production amount Pe,p,g of each product by the unit selling benefit USBe,p TAB ¼

∑

∑ ∑g USBe, p Pe, p, g

ð2Þ

e ∈ fgreenpolymer, biobutanolg p

6298

dx.doi.org/10.1021/ie200344t |Ind. Eng. Chem. Res. 2011, 50, 6297–6315


ARTICLE

where USBe,p denotes the selling benefit per tonne or 0 for each product e ($ 3 (t or 0)1). 3.1.2. Total Annual Cost. TAC consists of facility capital cost FCC, transport capital cost TCC, facility operating cost FOC, and transport operating cost TOC TAC ¼ FCC þ TCC þ FOC þ TOC

þ

þ

∑g

"

CCR facility ð LR

∑e ∑p

PCCe, p BPe, p, g

Similarly, the number NTUoff i,l of transport units offshore can be expressed by fixing the average distance LO l,g,g 0 from the harbor to the final sequestration region offshore, and the flow rate Qi,l,g,g0 of CO2 between the regions Qi, l, g , g 0 2LOl, g , g 0 NTUoff i, l ¼ þ LUTl , SPl g g 0 TMA l TCapi, l

∑∑

¼

ð4Þ

∑m UMCi, mMi, m, g þ ∑s USCi, s Si, s, g ÞÞ

TCC ¼ TCConshore þ TCCoffshore

ð5Þ

Qpipelinei, l, g , g 0 , d e TPcapi, l, d NTPoni, l, g , g 0 , d " i, l, d, g, g 0 ; g 6¼ g 0 , l ∈ fpipeg

CCR truck=rail ðNTUoni, l TMCi, l Þ LR

CCR ship ðNTUoff i, l TMCi, l Þ LR l ∈ fshipg

∑i ∑

TCCoffshorepipelines

¼

∑i l ∈ ∑ ∑∑∑ fpipeg g g d 0

CCR pipeline ðTPICoff d LOl, g , g 0 NTPoff i, l, g , g 0 , d Þ LR

ð13Þ The number NTPoffi,l,g,g0 ,d of pipelines offshore is determined by Qpipelinei, l, g , g 0 , d e TPcapi, l, d NTPoff i, l, g , g 0 , d " i, l, d, g, g 0 ; g 6¼ g 0 , l ∈ fpipeg

ð14Þ

Because use of multiple parallel pipelines between regions is not common for practical reasons, the number of pipelines between different regions is bounded by the following constraints:

∑d NTPoni, l, g, g , d e R " i, l, g, g 0 ; g 6¼ g 0 , l ∈ fpipeg

ð15Þ

∑d NTPoff i, l, g, g , d e R " i, l, g, g 0 ; g 6¼ g 0 , l ∈ fpipeg

ð16Þ

0

ð8Þ Here, NTUon i,l depends on the average distance L l,g,g0 between different regions (g, g 0 ) onshore, the capacity TCap i,l, of a transport container, the flow rate Q i,l,g,g 0 of CO2 between the regions, the availability TMAl of the

ð12Þ

where TPcapi,l,d is the transport capacity of the pipelines, which depends on its diameter. Similarly, the total capital cost of offshore pipelines is expressed using the distance LOl,g,g0 from the harbor to the offshore sequestration site

ð7Þ TCCoffshoreship ¼

TCConshorepipelines CCR pipeline ðTPICond Ll, g , g 0 NTPoni, l, g , g 0 , d Þ LR

where the total pipeline installation cost TPICon d consists of pipeline material cost, pipeline miscellaneous cost, right of way cost, and labor cost. The number of pipelines onshore NTPoni,l,g,g0 ,d is determined by

ð6Þ

Each term in the right-hand-side of eq 6 is further categorized in terms of transport mode. First, overall capital cost excluding pipeline transport is calculated by multiplying the number of transport units onshore NTUoni,l or offshore NTUoffi,l by the capital cost TMCi,l of transport modes including the costs of the transport container, the undercarriage, and the cab

∑i l ∈ frail∑, truckg

∑i l ∈ ∑ ∑∑∑ fpipeg g g d 0

3.1.2.3. Transport Capital Cost. TCC is the sum of the cost of building transport links onshore and offshore

TCConshoretruck=rail ¼

ð10Þ

ð11Þ

∑g ð∑e ∑p UPCe, p Pe, p, g þ ∑i ð∑c ∑si ∑sp UCCi, c, siCi, c, si, sp, g þ

ð9Þ

The total capital cost of onshore pipelines is

where the capital charge rate of facilities CCRfacility denotes depreciated present value per year over the lifetime of the system, and the learning rate LR denotes the reduction in the cost of CCS technologies as experience accumulates over time, or the factor to convert present costs into future costs.12. 3.1.2.2. Facility Operating Cost. FOC is the cost required to operate CCS facilities efficiently. It is obtained by multiplying the unit costs of utilization, capture, storage, and sequestration by the corresponding amounts of utilization, capture, storage, and sequestration FOC ¼

" i, l; l ∈ frail, truckg

" i, l; l ∈ fshipg

∑i ð∑c ∑si ∑sp CCCi, c, si, sp, g BCi, c, si, sp, g þ ∑m MCCi, m NMi, m, g ∑s SCCi, s NSi, s, g ÞÞ

∑∑

ð3Þ

3.1.2.1. Facility Capital Cost. FCC is the total cost of establishing utilization, capture, storage, and sequestration facilities. It is calculated by multiplying the required number of CCS facilities and their capital costs FCC ¼

transportation modes, their average speed SPl, and loading/unloading time LUTl Qi, l, g , g 0 2Ll, g , g 0 NTUoni, l ¼ þ LUTl SPl g g 0 TMA l TCapi, l

0

where R is a small number to limit the number of pipelines and assumed to be two. 6299



ARTICLE

The flow of a product form i between different regions can also only occur in pipelines with a type of diameter: Qi, l, g , g 0 ¼

∑d

GCship ¼

∑i l ∈ ∑fshipg ∑g ∑g 0

"

# Qi, l, g , g 0 2Ll, g , g 0 GEl þ LUTl TMA l TCapi, l SPl

Qpipelinei, l, g , g 0 , d 0

ð28Þ

0

" i, l, g, g ; g 6¼ g , l ∈ fpipeg

ð17Þ

3.1.2.4. Transport Operating Cost. Similar to eq 6, TOC consists of the costs of transport links onshore and offshore

The transport operating cost of pipeline onshore is TOConshorepipelines ¼

∑i l ∈ ∑ ∑ ∑ ∑ TPOCond Qpipelinei, l, g, g , d fpipeg g g d 0

0

ð18Þ

ð29Þ

Each term in the right-hand-side of eq 18 is partitioned according to transport mode. First, the transport operating cost of possible delivery excluding pipelines is the sum of fuel, labor, maintenance, and general costs:

where the total pipeline operating cost TPOCond consists of labor and utility cost used in such activities as compressing and pumping. Similarly, the transport operating cost of pipeline offshore

TOC ¼ TOConshore þ TOCoffshore

TOConshoretruck=rail ¼ FCtruck=rail þ LCtruck=rail þ MCtruck=rail þ GCtruck=rail

TOCoffshorepipelines ¼

ð19Þ

∑i l ∈ ∑ ∑ ∑ ∑ TPOCoff d Qpipelinei, l, g, g , d fpipeg g g d 0

0

ð30Þ

TOCoffshoreship ¼ FCship þ LCship þ MCship þ GCship ð20Þ The annual fuel cost, FC, is the product of fuel price FPl and annual fuel usage ! 2Ll, g , g 0 Qi, l, g , g 0 FCtruck=rail ¼ FPl ð21Þ FEl TCapi, l i l ∈ frail, truckg g g 0

∑

FCship ¼

∑

∑∑

∑i l ∈ ∑fshipg ∑g ∑g FPl 0

2LOl, g , g 0 Qi, l, g , g 0 FEl TCapi, l

! ð22Þ

The annual labor cost, LC, is the product of driver wage, DWl, and total delivery time LCtruck=rail ¼

∑i l ∈ frail∑, truckg ∑g ∑g 0

"

# Qi, l, g , g 0 2Ll, g , g 0 DW l þ LUTl TCapi, l SPl

ð23Þ LCship ¼


# Qi, l, g , g 0 2LOl, g , g 0 DW l þ LUTl TCapi, l SPl

The annual maintenance cost MC is the product of maintenance expense per unit distance traveled MEl and the total annual transport distance ! 2Ll, g , g 0 Qi, l, g , g 0 MEl MCtruck=rail ¼ TCapi, l i l ∈ frail, truckg g g 0

∑

∑∑

ð25Þ MCship ¼


2LOl, g , g 0 Qi, l, g , g 0 MEl TCapi, l

!

max Ccappmin i, c, si, sp, g BCi, c, si, sp, g e Ci, c, si, sp, g e Ccapi, c, si, sp, g BCi, c, si, sp, g

∑i l ∈ frail∑, truckg ∑g ∑g 0

# Q i, l, g , g 0 2Ll, g , g 0 GEl þ LUTl TMA l TCapi, l SPl

ð27Þ

ð32Þ

" i, c, si, sp, g

Equation 32 indicates that the amount of CO2 Ci,c,si,sp,g captured by each capture facility c of each source plant sp in region g is constrained by the binary variable BCi,c,si,sp,g, which represents whether or not to establish a capture facility in a source plant. The CO2 mass balance of individual regions should consider total annual capture, transport, utilization, and sequestration rates. Because we assume steady-state operation, the sum Qi,l,g0 ,g, of the total flow rates of CO2 imported to region g plus the total amount Ci,c,si,sp,g of CO2 captured in the region must be equal to the sum of the total flow rate Qi,i,l,g,g0 leaving the region, the total amount Ui,p,g of CO2 used in the region and the total amount Si,s,g of CO2 sequestered in the region

∑c ∑si ∑sp Ci, c, si, sp, g ¼ ∑l ∑g ðQi, l, g, g Qi, l, g , g Þ þ ∑s Si, s, g 0

0

0

þ

"

ð31Þ

where CEUc = 0.96 is the upper bound of CO2 capture efficiency for a type of capture facility c.9 The maximum amount of CO2 Ci,c,si,sp,g captured by a capture facility of type c in a source plant sp in region g is limited by the facility’s capacity. Moreover, often a minimum capture rate Ccapmin i,c,si,sp,g, must be maintained while the capture facility is operating. Ccapmin i,c,si,sp,g, of each facility of type c in source plant sp in region g is assumed to be 50% of Ei,si,sp,g, CO2 emissions from each source plant type sp in region g

ð26Þ

The annual general cost GC is the product of the general expense GEl and the number of transport units GCtruck=rail ¼

Ccapmax i, c, si, sp, g ¼ Ei, si, sp, g CEUc " i, c, si, sp, g

"

ð24Þ

∑

3.2. Constraints. 3.2.1. Capture Facilities Constraints. If an industry that emits CO2 is located in the region onshore, the maximum amount Ccapmax i,c,si,sp,g, of CO2 captured by capture facility of type c in a source plant sp belonging to the type of source industry si in region g is constrained as

∑p Ui, p, g " i, g

ð33Þ

3.2.2. Intermediate Storage Facilities Constraints. Intermediate-storage facilities should be built to collect CO2 captured from source plants in a given region.13 In particular, intermediate storage facilities should reload CO2 at harbors for delivery by ship, whereas for pipeline-based transportation no intermediate 6300



ARTICLE

storage is required.13 Because the operation is assumed to be at steady state, the total inventory Mi,m,g of CO2 in physical form i of all storage facilities in a particular region g is the product of a safety stock factor SSF and the total flow rate Qi,l,g,g0 of CO2 in physical form i leaving region g

∑m Mi, m, g ¼ SSFðl ˇ fpipelineg ∑ ∑g Qi, l, g, g Þ " i, g 0

ð34Þ

0

SSF is introduced to allow operational flexibility in case of unanticipated events such as the closing of a capture plant. The capacity MCapi,m of each storage facility of type m storing CO2 in physical form i cannot exceed certain limits. This consideration guarantees that the inventory Mi,m,g of CO2 in physical form i in each storage facility m in region g will be bound within certain limits: max MCapmin i, m NMi, m, g e Mi, m, g e MCapi, m NMi, m, g " i, m, g ð35Þ

This constraint also implies that Mi,m,g is constrained by the number of storage facilities NMi,m,g. 3.2.3. Transportation Constraints. CO2 is moved from various emission sources to various final sequestration or utilization facilities to fulfill the mandated reduction of CO2 emissions. Therefore CO2 in physical form i can flow only from a source to a sequestration facility or utilization facility. To formulate the flow mathematically, subtour elimination constraints are employed in this paper as follows:14

The capacity Scapi,s of each sequestration facility of type s sequestering CO2 cannot exceed certain limits: max Scapmin i, s NSi, s, g e Si, s, g e Scapi, s NSi, s, g " i, s, g

This constraint also implies that the amount of CO2 sequestered by each sequestration facility s in region g is constrained by the number of sequestration facilities NSi,s,g. The amount Si,s,g of CO2 sequestered by any sequestration facility of type s in region g is determined by the available geological capacity GScapi,g for sequestering CO2 in region g Si, s, g e GScapi, g " i, s, g

ð36Þ

where Xi,l,g,g is binary variable representing whether or not to transport. CO2 in physical form i will flow from region g to a different region g0 only if the transportation mode l is established. Thus, a max minimum flow rate Qmin i,l and a maximum flow rate Qi,l of CO2 are needed to justify the establishment of a transportation mode between two regions 0

max Qimin , l Xi, l, g , g 0 e Qi, l, g , g 0 e Qi, l Xi, l, g , g 0

" i, l, g, g 0 ; g 6¼ g 0

max Pcapmin e, p BPe, p, g e Pe, p, g e Pcape, p BPe, p, g

" e, p, g; e ∈ fgreenpolymer, biobutanolg

∑i ∑l Xi, l, g, g

0

e 1 " g, g 0 ; g 6¼ g 0

ð38Þ

Likewise, all transport modes with all physical forms of CO2 entering a region g are bounded by the constraint

ð42Þ

The amount Ui,p,g of CO2 used by a utilization facility of type p in region g is calculated by multiplying the CO2 use factor CUFe,p of product form e by the production rate Pe,p,g of product form e produced in any utilization facility of type p in region g Ui, p, g ¼

∑

CUFe, p Pe, p, g e ∈ fgreenpolymer, biobutanolg

" i, p, g

ð43Þ

The total amount of CO2 sequestered and used in all regions cannot be less than the target amount T of CO2 to be reduced by CCS facilities

∑i ∑g ð∑s Si, s, g þ ∑p Ui, p, g Þ g T

ð44Þ

T is the product of the mandated reduction of CO2 emissions LMRi, the utilization UCCSi of CCS as CO2 reduction technology, and the total amount Ei,si,sp,g of CO2 emissions from all sources: T ¼

ð37Þ

All transport modes with all physical forms of CO2 leaving region g are bounded by the constraint

ð41Þ

3.2.5. Utilization Facilities Constraints. The production rate Pe,p,g of a product form e produced by any utilization facility of type p in region g cannot exceed certain limits. Thus, every product has a maximum production rate Pcapmax e,p . Moreover, often a minimum production rate Pcapmin e,p must be maintained while the plant is operating:

ug 0 ug þ nXi, l, g , g 0 e n 1 " i, l, g, g 0 ; g ¼ 2, :::n, g 0 ¼ 2, :::n; g 6¼ g 0

ð40Þ

∑i ∑si ∑sp ∑g LMR i UCCSi Ei, si, sp, g

ð45Þ

The overall decision-making problem can be formulated into the following MILP problem max subject to :

ð1Þ ð2Þ ð45Þ

ð39Þ

In the next section, a case study will be presented to illustrate the applicability of the proposed model.

3.2.4. Sequestration Facilities Constraints. CO2 sequestration is mainly divided into geological and marine methods. Specifically, these methods include enhanced oil recovery, enhanced coal-bed methane, depleted gas reservoir, depleted oil reservoir, saline aquifer storage, ocean storage via pipeline, and ocean storage in tanker ships.4 The specific sequestration method can be chosen based on the geological characteristics and sequestration capacity of a particular region.

4. CASE STUDY: AN INDUSTRIAL COMPLEX ON THE EAST COAST OF KOREA IN 2020 The industrial complex on the east coast of Korea in 2020 was chosen for several reasons. The east coast of Korea has a fairly well-established economic and environmental culture with the potential to develop the infrastructure for a new resource such as CO2. Also, data required to design such an infrastructure are available from relevant authorities, because eastern Korea has large industrial sources of CO2 such as power, steel, oil refinery

∑i ∑l Xi, l, g , g e 1 " g, g 0 ; g 6¼ g 0 0

6301


Industrial & Engineering Chemistry Research and petrochemical plants. In addition, the east coast of Korea has a long-term strategic initiative to promote widespread use of CO2 in the transport and industrial sectors. For example, interest in use of biobutanol as a transport fuel is increasing; CO2 is used in biological methods such as the culture of microalgae, which can be used to make biobutanol.15 Korean steel producer POSCO plans to build a biobutanol plant in Pohang city on the east coast of Korea. Furthermore, the United States Environmental Protection Agency (EPA) has warned about the toxicity and volatility of PVC or vinyl,16 so interest in use of “green” polymers as an alternative to PVC is increasing. This green polymer is made from CO2 and polypropylene oxide.17 Korean company SK Energy plans to build a green polymer plant in Ulsan on the east coast of Korea. Also, the east coast of Korea is located near Table 1. Capture, Storage, Sequestration, Utilization, and Transportation Technologies for the Examined Case Study activity capture technology intermediate storage technology sequestration method saline aquifer storage utilization method transportation mode

type the absorption and desorption of carbon dioxide in aqueous monoethanolamine (MEA) liquid CO2 (LCO2) in steel tank depleted gas reservoir biobutanol green polymer LCO2 tanker truck onshore LCO2 tanker ship offshore LCO2 tanker rail car onshore LCO2 pipeline on and offshore

ARTICLE

possible sequestration sites in marine reservoirs such as the Ulleung and Pohang basins.18 Considering these advantages, the east coast of Korea represents an ideal case study to map out all possible CCS infrastructures. This study examines only the capture, storage, sequestration, and utilization of liquid CO2. Transport of gaseous CO2 is inefficient because of the low density of the CO2 and because transport of gaseous CO2 in pipelines results in relatively high pressure drop per unit distance.11 The versatility of the proposed model was tested using several capture, storage, sequestration, and utilization technologies and transportation modes (Table 1). These technologies were then combined to form an available CCS infrastructure configuration. The superstructure of the proposed model (Figure 3) includes four CO2 source regions (Ulsan, Gangwon, Pohang and Gyeongnam) with different industry types and different modes of capture types at each plant in corresponding industries. Also, the regions use different types of storage technology, and two regions (Ulsan and Pohang) use different types of utilization technology. The model considers three sequestration regions (Ulleung Basin, Pohang Basin and Norway Basin) which use different types of sequestration technology. Tanker trucks, tanker railcars, and pipelines are used to transport different physical forms of CO2 from capture regions to utilization regions, where CO2 will be used for market use, whereas pipelines and tanker ships are used to transport different physical forms of CO2 from intermediate storage regions to sequestration regions, where CO2 will be stored for long periods. From this structure, the optimization model will search for the best design option of CCS technologies.

Figure 3. Configuration of all CCS technologies in the case study. 6302



ARTICLE

Figure 4. Estimation of greenhouse gas emission and CO2-reduction target in Korea 2020.

Table 2. Analysis Condition Selected for the Case Studya analysis condition description transportation

case 1 2 3 4 5 6 7 8 9 10

reduction target, T (utilization of CCS as CO2 reduction technology, UCCSi) 1

1,848,842 t CO2 3 y

(10%)

3,697,685 t CO2 3 y1 (20%)

capture

storage

MEA

LCO2

O O O O O O O O O O

O O O O O O O O

onshore pipe

rail

truck

O O

offshore ship

pipe

O O

O

O O

O O

truck

ship

O O

O O O

rail

sequestration

O O

O

O

O O O O O O O O

utilization

DGR

SAS

biofuel

Gpolymer

O O O O O O O O O O

O O O O O O O O O O

O O O O O O O O O O

O O O O O O O O O O

a

Case 1 and 6: Liquid CO2 (LCO2) network using pipeline onshore and offshore. Case 2 and 7: Liquid CO2 (LCO2) network using pipeline onshore and tanker ship offshore. Case 3 and 8: Liquid CO2 (LCO2) network using tanker truck onshore and tanker ship offshore. Case 4 and 9: Liquid CO2 (LCO2) network using tanker railcar onshore and tanker ship offshore. Case 5 and 10: All alternatives.

In building the model, data were collected from a variety of sources and are shown in detail in the following subsequent sections. 4.1. CO2 Reduction Scenario and Estimation of Cost Data. The amount of CO2 emission tends to increase as an economy expands; therefore, focusing on the future amount of CO2 emission is appropriate. Furthermore, for actual CO2 treatment facilities to fulfill the mandated reduction in CO2 emissions by a certain future time, this amount should be established in advance. The Korean government plans to take measures to reduce greenhouse gas emissions by 30% in 2020 (Figure 4).19 For these reasons, this paper will address a CCS infrastructure in Korea around the year 2020. Probably, by that time many CCS facilities will be operating. Data collected from a variety of sources have different cost years for each of their parameters. The cost year in text and tables associated with the case study must consider 2010 as the year for their analysis. To estimate capital costs and unit operating costs of CCS facilities, we have used the Chemical Engineering Plant

Cost Index,20 and have assumed that the cost year basis is 2010 (constant dollars) and. We assumed that advances in CCS technologies will occur from 2010 to 2020 and that these advances will reduce the cost of CCS technologies. The learning rate LR is introduced to account for the reduction in the cost of CCS technologies as experience accumulates over time.12 This coefficient is defined as LR ¼ 1 þ ðkðt 1ÞÞ

ð46Þ

where t 1 represents the cost reduction with time and κ is the percentage of the corresponding reduction per year, assumed to be 5% y1. Although the construction and analysis of our model are clear, significant uncertainty remains in both CO2 reduction target and cost data. To examine the applicability of the CCS infrastructure model for these types of problem, we have used the scenariobased optimization with varying reduction targets by using different utilization rates of CCS technologies (Table 2). This 6303



ARTICLE

Table 3. Parameters Used for Estimating Total CO2 Emissions in Korea 2020 parameter average annual growth rate (%)

a

CO2 emission factor

a

KIIET30 b IPCC21

note

value

power industry steel industry petrochemical industry oil refinery industry power-coal (t CO2 3 MW1 3 h1) b pig iron-blast furnace (t CO2 3 t product produced1) b crude oil distillation units (t CO2 3 t product processed1) b ethylene distillation units (t CO2 3 t product processed1) b

1.7 2.5 2.8 1.4 0.95 1.35 0.05 1.73

Table 4. CO2 Emissions of Each Plant in 2020 industry type

plant

product type

power power power power power power power power steel steel steel steel steel oil refinery oil refinery oil refinery oil refinery oil refinery petrochemical petrochemical

Youngdong #1 unit Youngdong #2 unit Samcheonpo #1 unit Samcheonpo #2 unit Samcheonpo #3 unit Samcheonpo #4 unit Samcheonpo #5 unit Samcheonpo #6 unit Posco #1 unit Posco #2 unit Posco #3 unit Posco #4 unit Posco #5 unit Skenergy #1 unit Skenergy #2 unit Skenergy #3 unit Skenergy #4 unit Skenergy #5 unit KPIC Skchem

power-coal power-coal power-coal power-coal power-coal power-coal power-coal power-coal pig iron pig iron pig iron pig iron pig iron crude oil crude oil crude oil crude oil crude oil ethylene ethylene

region

CO2 emissions (t CO2 3 y1)

Gangwon Gangwon Gyeongnam Gyeongnam Gyeongnam Gyeongnam Gyeongnam Gyeongnam Pohang Pohang Pohang Pohang Pohang Ulsan Ulsan Ulsan Ulsan Ulsan Ulsan Ulsan

952 249 1 523 598 4 879 613 5 057 054 4 790 893 5 145 774 4 347 292 4 524 732 1 779 958 2 713 139 5 011 531 9 176 286 6 100 243 204 020 374 036 578 055 816 078 884 085 978 677 1 790 770

Table 5. Capital Costs and Unit Capture Costs of CO2 Capture Technology According to Each Industry

a

capacity (t CO2 3 y1) capture capital cost (million $) unit capture cost ($ 3 (t CO2)1)

power plantsa

iron and steel plantsb

oil refinery plantsc

petrochemical plantsd

1 480 000 333 49.76

2 795 000 639 38.29

1 013 000 283 80.26

969 000 558 58.85

Estimated based on Rubin et al.5 b Estimated based on Lie et al.31 c Estimated based on Gadalla et al.32 d Estimated based on M€ollersten et al.33

paper also examines the design and operation of five different configurations for the future CCS infrastructure based on the physical form of the CO2 (Table 2). Also, to determine the sensitivity of resulting network to uncertainties in cost data, we have used sensitivity analysis in section 5.2. 4.2. Estimation of CO2 Emissions. In designing a CCS infrastructure, the CO2 emissions at sources should be estimated. This paper employs a product-based emission factor method as follows:21 ECO2j ¼ PPj EFj

ð47Þ

where ECO2j represents CO2 emissions from production of product j, PPj is the annual production of product j, and EFj is the CO2 emission factor of product j. Regarding the industrial features of the east coast of Korea, we selected 11 major CO2 sources: two power plants, three steel plants, and six petrochemical plants in four regions. First, we analyzed the present scale of production of each plant. After

applying specific assumptions such as the economic growth rate of each plant in corresponding industries, we estimated the future scale of production of each plant. Then, using these estimates and a CO2 emission coefficient proposed by the International Panel on Climate Change19 (Table 3), we estimated the total CO2 emissions in 202021 (Table 4). 4.3. Capture Facilities. We calculated capital costs and unit capture costs of CO2 capture technology according to each industry (Table 5). Because the capital cost of CO2 capture facility is a strong function of its capacity, the capital cost of building a CO2 capture facility for each source plant varies with the emission rate.22 To estimate the capital cost of CO2 capture facility, we used the six-tenths factor rule23 as follows: 0:6 SB ð48Þ CB ¼ CA SA where CB = the approximate cost ($) of equipment having size SB, CA = is the known cost ($) of equipment having size SA, and SB/SA is the ratio known as the size factor, dimensionless. 6304



ARTICLE

Table 6. Costs of Capture Facility for Each Plant Based on CO2 Emission Forecast in 2020 industry type

plant

region

capital cost of capture facility for each plant ($)

unit cost of capture facility for each plant ($ 3 y1)

power power power power power power power Power steel steel steel steel steel oil refinery oil refinery oil refinery oil refinery oil refinery petrochemical petrochemical

Youngdong #1 unit Youngdong #2 unit Samcheonpo #1 unit Samcheonpo #2 unit Samcheonpo #3 unit Samcheonpo #4 unit Samcheonpo #5 unit Samcheonpo #6 unit Posco #1 unit Posco #2 unit Posco #3 unit Posco #4 unit Posco #5 unit Skenergy #1 unit Skenergy #2 unit Skenergy #3 unit Skenergy #4 unit Skenergy #5 unit KPIC Skchem

Gangwon Gangwon Gyeongnam Gyeongnam Gyeongnam Gyeongnam Gyeongnam Gyeongnam Pohang Pohang Pohang Pohang Pohang Ulsan Ulsan Ulsan Ulsan Ulsan Ulsan Ulsan

255 736 753 339 051 083 681 669 874 696 436 302 674 206 202 703 741 697 636 024 925 651 476 258 487 363 008 627 610 237 906 961 864 1 303 787 882 1 020 504 797 108 012 206 155 388 078 201 767 604 248 146 886 260 355 103 561 979 987 807 534 540

59.36 49.19 30.88 30.44 31.10 30.23 32.34 31.82 45.86 38.75 30.31 23.80 28.02 152.36 119.56 100.45 87.51 84.75 58.62 46.03

Table 7. Capital Costs and Unit Storage Costs of CO2 Storage Facilities

Table 8. Parameters Used to Estimate the Capital and Operating Costs of Transport Modes Excluding Pipeline

LCO2 storage facility (steel tank) storage capital cost ($) a a

unit storage cost ($ 3 (t CO2) )

0.72

Estimated based on Svensson et al.13

The unit capture cost benefits from economies of scale; therefore, as the capacity of capture increases the unit cost decreases. We first calculated the required capacity of a CO2 capture facility for each source plant according to its emission rate. After applying the six-tenths factor rule to forecast the costs of CO2 capture facilities, we estimated the capital and unit cost of a capture facility for each source plant (Table 6). 4.4. Intermediate Storage Facilities. The minimum storage capacity Mcapmin i,m of each storage type with respect to liquid CO2 was assumed to be 1,000 t CO2 3 y1. The maximum storage 1 13 capacity Mcapmax i,m of a steel tank is 1 000 000 t CO2 3 y . The capital cost for the establishment of storage facility type and the unit storage cost (Table 7) were obtained from ref 13. Because of fluctuations in both the scattered CO2 sources and CO2 disposal or utilization sites, a flexible storage system is required. This study allows for operational flexibility of inventory; SSF was set to 1.5. 4.5. Transport Modes. The maximum flow rate Qmax i,l of liquid CO2 transported was assumed to be 2.7 Mt CO2 3 y1, and the minimum flow rate Qmin i,l was assumed to be equal to the capacity of each transport mode (Table 8). This means that the minimum allowable quantity of CO2 flow between points is equal to a fully loaded transport unit. However, the maximum allowable quantity is based on the assumption that individual modes cannot transport more than what is captured by a large capture facility. The parameters used to calculate the capital and operating costs for the different types of transport modes excluding pipelines (Table 8) were obtained from refs 10, 24, and 25. The capital and operating costs for the different types of pipeline diameters (Table 9) were obtained from refs 6 and 24.

tanker truck

tanker shipc

80 550 040 4.25 45 4380 12 31.08 0.40 0.10 3561

22 422 275 2.55 55 6570 2 31.08 1.65 0.15 4273

30,000 261 222 886 0.017 33 5310 33.5 78.68 0.94 7.16 456 353

capacity (t CO2 3 trip1) a transport capital cost ($)a fuel economy (km 3 L1) b average speed (km 3 h1) b mode availability (h 3 y1) b load/unload time (h 3 trip1) b driver wage ($ 3 h1) b fuel price ($ 3 L1) b maintenance expenses ($ 3 km1) b general expenses ($ 3 y1) b

10 228 607 1 a

tanker railcar

a Estimated based on Douglas and Dracos.25 b Estimated based on Almansoori and shah.10 c Estimated based on Hedle et al.24

Table 9. Capital costs and unit transport costs of pipeline with diameter 6.88 diameter (in)

a

capacity (t CO2 3 y1) transport capital cost ($ 3 km1) unit transport cost ($ 3 t CO21 3 y1)

onshore

a

offshore

9.27 b

onshore

a

offshoreb

730 000 216 900 303 660

1 460 000 292 247 409 146

5.15

3.34

7.21

4.68

Estimated based on McCollum and Ogden.6 b Estimated based on Hedle et al.24

The average transport distances between different regions (Table 10) were estimated based on the areas of the regions. These distances may vary depending on the region’s location and were measured from the center of each region, if possible.10 4.6. Sequestration Facilities. The minimum sequestration capacity Scapmin i,s of each sequestration type was assumed to be 10 kt CO2 3 y1; the maximum sequestration capacities Scapmax i,s of each sequestration type, and the capital and operating costs for the different types of sequestration facilities (Table 11) were obtained from refs 26, 27, and 28. 6305



ARTICLE

Table 10. Transport Distances within and between Regions (km) onshore

offshore

region

Ulsan

Gangwon

Pohang

Gyeongnam

Ulleung Basin

Pohang Basin

Ulsan Gangwon Pohang Gyeongnam

20 405 209 99

405 20 210 387

209 210 20 192

99 387 192 20

199 240 140 275

58

Norway

176 141

20,100

Table 11. Capital Costs and Unit Sequestration Costs of CO2 Sequestration Facilities depleted gas reservoira

a

candidate region for CO2 sequestration total (planned) sequestration (Mt CO2) c CO2 injection rate (kt CO2 3 y1) sequestration capital cost ($) unit sequestration cost ($ 3 (t CO2)1)

Ulleung Basin 1.0

saline aquifer storageb Pohang Basin

Norway

1.0

20.0 3417 3 383 308 4.61

57 580 276 7.66

Bock et al.26 b Kongsjorden et al.27 c Kang et al.28

Table 12. Selling Benefit, Capital Costs, and Unit Production Costs of CO2 Utilization Facilities biobutanol planta capacity CO2 use factor unit selling profit production capital cost (million $) unit production cost a

green polymer plantb

1

2 Mt 3 y1 0.431 t CO2 3 t1 2,000 $ 3 t1 1,421 710.62 $ 3 t1

300 ML 3 y 0.00279 t CO2 3 L1 1.2 $ 3 L1 100 0.48 $ 3 L1

Kim et al.29 b Jo, W.Y. and D.J. Woo.17

Table 13. Summary of Computational Results for the Examined Model case no.

1

2

3

4

5

number of constraints number of integer variables number of continuous variables optimality gap (%) CPU time (s)

1749 85 2312 0.0 0.015

1773 85 2340 0.0 0.015

1723 66 2243 0.0 0.016

1723 66 2343 0.0 0.016

1775 109 2318 0.0 0.031

case no.

6

7

8

9

10

number of constraints number of integer variables number of continuous variables optimality gap (%) CPU time (s)

1749 85 2312 0.0 0.031

1773 85 2340 0.0 0.016

1723 66 2243 0.0 0.032

1723 66 2343 0.0 0.32

1775 109 2318 0.0 0.047

4.7. Utilization Facilities. Green polymer is produced by polymerization of one mole of carbon dioxide and one mole of polypropylene oxide.17 Thus, 1 kg of green polymer constitutes 43.1 wt % of carbon dioxide and 56.9 wt % of polypropylene oxide;17 2.32 kg of green polymer can be made from 1 kg of carbon dioxide. The product will replace flexible polyvinyl chloride (FPVC) and target 20 uses for conventional items used FPVC.16 Also, its domestic and global markets is estimated about 3 million ton per year and at over U.S. $ 2000 per ton (Table 12). The minimum production capacities Pcapmin e,p were assumed to be 10 kt 3 y1 for a green polymer plant and 10 kL 3 y1 for a biobutanol plant. The maximum production capacities Pcapmax e,p of each utilization facility, and the selling benefits, capital costs and operating costs for the different production types of utilization facilities (Table 12) were obtained from refs 17 and 29.

5. .RESULTS AND DISCUSSION 5.1. Optimal CO2 Infrastructure. The aim of the proposed model is to outline the CCS infrastructure by fulfilling mandated reduction in CO2 for industrial complexes on the east coast of Korea in 2020. The proposed model was computed using CPLEX 9.0 (GAMS) in on a computer equipped with a Pentium 4 chip, operating at 3.16 GHz. The computational statistics and summaries of results are were obtained for fourteen networks (Table 13); all configurations were solved acceptably quickly, with acceptably low optimality gaps. The cost (Table 14) and profit (Table 15) (both in $U.S. t CO2) were obtained for each of the network configurations examined. Pipeline transport of liquid CO2 onshore and offshore was determined to be the most economical method: for an annual reduction target of 1 848 843 t CO2 y1, this method had a network wide cost 6306



ARTICLE

Table 14. Benefits, Costs, and Profit of CO2 Infrastructure for Annual Reduction Target of 1 848 842 t CO20 y1) case no.

1

2

3

4

5

benefits (million $ 3 y1) selling benefit of biobutanol selling benefit of greenpol network wide utilization benefit ($ t CO2

1

total annual benefits (million $ 3 y1)

)

360

360

355

356

360

4,000

4,000

4,000

4,000

4,000

5,070

5,070

5,070

5,070

5,070

4,360

4,360

4,355

4,356

4,360

costs disposal costs capital cost (million $ 3 y1) capture facilities

61.92

61.92

61.92

61.92

storage facilities

-

1.01

3.03

3.03

-

sequestration facilities

0.17

0.17

0.17

0.17

0.17

transportation modes total capital cost for disposal

61.92

7.76

31.8

28.89

29.48

7.76

69.86

94.91

94.02

94.60

69.86

operating cost (million $ 3 y1) capture facilities

71.64

71.64

71.64

71.64

71.64

storage facilities sequestration facilities

1.15

0.16 1.15

1.28 1.24

1.27 1.21

1.15

transportation modes

4.46

3.42

30.17

10.18

4.46

77.25

76.37

104.34

84.31

77.25

total operating cost for disposal 1

147.11

171.27

198.35

178.91

147.11

91.57

121.06

133.21

117.06

91.57

utilization facilities biobutanol

98.67

98.67

98.67

98.67

98.67

utilization facilities

140.23

140.23

140.23

140.23

140.23

238.90

238.90

238.90

238.90

238.90

144.00

144.00

141.94

142.51

144.00

1421.24

1421.24

1421.24

1421.24

1421.24

total disposal cost (million $ 3 y ) 1 network wide disposal cost ($ t CO2 ) utilization costs capital cost (million $ 3 y1)

Greenpol total capital cost for utilization operating cost (million $ 3 y1) utilization facilities biobutanol utilization facilities Greenpol total operating cost for utilization

1565.24

1565.24

1563.18

1563.76

1565.24

total utilization cost (million $ 3 y1)

1804.14

1804.14

1802.08

1802.65

1804.14

1

2,101

2,101

2,103

2,102

2,101

1,951

1,975

2,000

1,981

1,951

total annual profit (million $ 3 y1)

2,409

2,384

2,354

2,374

2,409

network wide profit ($ 3 t CO2

1,303

1,290

1,273

1,284

1,303

network wide utilization cost ($ 3 t CO2 1

total annual cost (million $ 3 y

)

)

profits 1

)

of ∼$2193 t CO21 and a profit of ∼$2409 t CO21; for an annual reduction target of 3 697 685 t CO2 y1 the cost was ∼$2185 t CO21 and the profit was $611 t CO2.1 In detail, for an annual reduction target of 1 848 843 t CO2 y1, the network wide disposal cost was $91.57 t CO21 and the utilization cost of pipeline based transportation was $2101 t CO21; whereas for an annual reduction target of 3 697 685 t CO2 y1, the network wide disposal cost was $84.31 t CO21 and the utilization cost of pipeline based transportation was $2101 t CO21. These results suggest that as reduction target increased, the network wide disposal cost for CCS infrastructure decreased, but the network wide profit for CCS infrastructure decreased. This is because the limitation in the production capacity of the utilization

facilities both disturbs additional production and causes a stagnant benefit from selling constant products made by utilizing CO2, although large-scale CCS brings cost reduction. These trends must be considered when planning additional construction of utilization facilities as reduction target increases. The largest portion of total annual cost is the operating cost of CCS utilization facilities (Tables 14, 15); the second largest portion is the capital cost of CCS utilization facilities, which is nearly three times larger than the total capital cost of CCS disposal facilities. Based on the results obtained, this infrastructure would be quite expensive at the current stage of technological development due to the high cost of the CCS utilization facilities. However, improved CCS technologies are likely to be 6307



ARTICLE

Table 15. Benefits, Costs, and Profit of CO2 Infrastructure for Annual Reduction Target of 3 697 685 t CO2 y1) case no.

6

7

8

9

10

360 4000 5070 4360

360 4000 5070 4360

360 4000 5070 4360

360 4000 5070 4360

360 4000 5070 4360

1

benefits (million $ 3 y ) selling benefit of biobutanol selling benefit of greenpol 1 network wide utilization benefit ($ 3 t CO2 ) 1 total annual benefits (million $ 3 y ) costs disposal costs capital cost (million $ 3 y1) capture facilities storage facilities sequestration facilities transportation modes total capital cost for disposal operating cost (million $ 3 y1) capture facilities storage facilities sequestration facilities transportation modes total operating cost for disposal total disposal cost (million $ 3 y1) 1 network wide disposal cost ($ 3 t CO2 ) utilization costs capital cost (million $ 3 y1) utilization facilities biobutanol utilization facilities Greenpol total capital cost for utilization operating cost (million $ 3 y1) utilization facilities biobutanol utilization facilities Greenpol total operating cost for utilization total utilization cost (million $ 3 y1) 1 network wide utilization cost ($ 3 t CO2 ) 1 total annual cost (million $ 3 y ) profits total annual profit (million $ 3 y1) 1 network wide profit ($ t CO2 )

113.97

96.21 4.04 2.06 63.37 165.68

110.84 7.06 2.06 54.62 174.59

104.82 6.06 2.06 57.53 170.46

113.97

140.08 3.78 15.31 34.46 193.63 368.22 104.07

131.24 3.94 15.31 22.27 172.76 343.22 96.25

135.42

15.31 14.21 164.93 294.98 84.31

140.44 2.16 15.31 17.02 174.92 340.60 93.47

15.31 14.21 164.93 294.98 84.31

98.67

98.67

98.67

98.67

98.67

140.23

140.23

140.23

140.23

140.23

238.90

238.90

238.90

238.90

238.90

144.00

144.00

144.00

144.00

144.00

1421.24

1421.24

1421.24

1421.24

1421.24

1565.24 1804.14 2101 2099

1565.24 1804.14 2101 2144

1565.24 1804.14 2101 2172

1565.24 1804.14 2101 2147

1565.24 1804.14 2101 2099

2260 611.43

2215 599.09

2187 591.63

2212 598.39

24 260 611.43

2.06 14.02 130.05 135.42

developed; if so the capital and operating cost of the CCS facilities will decrease in the future. This will lead to a reduction in the cost of a CO2 utilization network because of the low production cost of biobutanol and green polymers. Additionally, for case study 5, the difference in cost between capital cost and operating cost of each component of CCS disposal facilities was significant (Figure 5). The capital cost of the capture facility contributed ∼81% of the total capital cost of CCS disposal facilities and the operating cost of capture facility contributed ∼77% of the total operating cost of CCS disposal facilities. This result indicates that investment strategies for capture technology must be planned first. The most important factor in building a CCS infrastructure is to reduce the high costs of commercializing a capture technology. The detailed result of the optimal configuration for the future CCS infrastructure according to each reduction target will be explained. The network of case 5 (Figures 6, 7) includes all CO2 activities for an annual reduction target of 1 848 843 t CO2 y1. Various methods are used to treat CO2 from the point of capture to the point of sequestration or use (Figure 6). The total amount of CO2 captured in a region onshore is ∼1850 kt CO2 y1. Of the steel industries in the Pohang region, only POSCO # 2 Unit has a capture facility. The CO2 captured should be matched by

2.06 14.02 130.05

Figure 5. Case 5: Breakdown of network wide costs for CCS disposal facilities ($ 3 t CO21).

disposal activities such as sequestration or utilization activities such as production of biobutanol and green polymers. The total 6308



ARTICLE

Figure 6. Case 5: CO2 capture, sequestration and utilization activities of CCS facilities.

Figure 7. Case 5: CO2 storage and transport activities of CCS facilities.

amount of CO2 sequestered in a geographical region (Pohang Basin) is ∼150 kt CO2 y1; this is ∼8% of the total amount of CO2 captured (Figure 6). The total amount of CO2 used in production of biobutanol and green polymers is ∼1700 kt CO2 y1; this is ∼92% of the total CO2 captured. Depleted gas reservoirs are the main sites used to sequester CO2, and both biobutanol and green polymer production are the main methods of utilizing CO2 (Figure 6). Pipelines are the main transport mode used to transport liquid CO2 from the point of capture to the point of utilization or sequestration (Figure 7). Two pipelines are established to fulfill the disposal or utilization of CO2, and the amount of CO2 transported by a

9.27-in. pipeline from the Pohang region to the Ulsan region is ∼1012 kt CO2 y1, while the amount of CO2 transported by a 6.88in. pipeline from the Ulsan region to the Pohang basin is ∼150 kt CO2 y1. The reason for this result is the relative low cost per unit of capture for the steel industries in the Pohang region, compared with other industries. When the reduction target rate is low, a few steel plants fulfill the required reduction demand by itself. More captured CO2 is then transported to other regions regardless of the distances between regions. The configuration of CCS activities when the reduction target = 3 697 685 t CO2 y1 (Figure 8 and 9) is a little different from that 6309



ARTICLE

Figure 8. Case 10: CO2 capture, sequestration, and utilization activities of CCS facilities.

Figure 9. Case 10: CO2 storage and transport activities of CCS facilities.

when the reduction target = 1 848 843 t CO2 y1 (Figure 6 and 7). As the reduction target rate increased, CO2 captured from a oil refinery plant appeared in Ulsan region and CO2 captured from POSCO # 2 Unit was transferred to POSCO # 3 Unit steel plant in Pohang region in case 10 (Figure 8). Also, CO2 sequestered in depleted gas reservoirs in Pohang basin increased and CO2 began to be sequestered in depleted gas reservoirs in Ulleung basin. This means that when the reduction target rate is high, the configuration of case 10 requires more CCS facilities to fulfill the required reduction demand because of the high cost of transportation. In

this case, almost all pipelines were 9.27 in. diameter, rather than smaller diameters (Figure 9). From an economic viewpoint, when volumes of CO2 are large, the optimal configuration of the future CCS infrastructure is to use pipelines to distribute liquid CO2 onshore and offshore. Another feasible configuration for the future CCS infrastructure uses tanker railcars to deliver liquid CO2 to intermediate storage facilities near the harbor. On the basis of the results obtained (Table 15), this option can be a expensive at the current stage due to the high capital cost of the transport modes that use small-capacity containers. 6310



ARTICLE

Figure 10. A. CO2 transport cost as a function of CO2 flow onshore (per 200 km). B.CO2 transport cost as a function of CO2 flow offshore (per 200 km).

Figure 12. A. CO2 transport cost of 6.88-in. pipelines as a function of CO2 flow and transport distance onshore. B. CO2 transport cost of 9.27in. pipelines as a function of CO2 flow and transport distance onshore.

Figure 13. CO2 transport cost of tanker railcars as a function of CO2 flow and transport distance onshore. Figure 11. A. CO2 transport cost as a function of distance onshore (per a mass flow of 1 Mt CO2 y1). B.CO2 transport cost as a function of distance offshore(per a mass flow of 1 Mt CO2 y1).

Development of more cost-effective transport technologies of expandable capacity would reduce the cost of CO2 delivery using tanker railcars; this development would lead to decentralized distribution using various transport modes. This approach would also be useful in allowing cross-links among pipelines. 5.2. Sensitivity Analysis. The CCS infrastructures considering all alternatives (cases 5 and 10) were similar to the CCS infrastructures that consider only transportation through pipelines (cases 1 and 6) (Figures 69). This means that other transportation modes are not cost-competitive compared with

pipelines in the case of CCS infrastructures on the east coast of Korea in 2020. This study has analyzed several parameters to determine the optimum configuration. We calculated point-to-point delivery costs ($ 3 t CO21) over the range of transportation parameters (flow and distance) for each transportation mode (Figures 10 and 11). When the quantity of CO2 increases, pipeline costs fall greatly, but tanker truck and tanker railcar costs are relatively independent of CO2 flow rate (Figure 10); the two modes have approximately the same cost when the quantity of CO2 is 500 kt CO2 y1 onshore: at lower CO2 quantities, tanker railcars are the cheapest option, but at higher CO2 quantities, shipping through pipelines is the cheapest option (Figure 10A). In contrast, for large quantities 6311



ARTICLE

Table 16. Transport Mode Map Describing the Lowest-Cost CO2 Delivery Options As a Function of CO2 Flow and Transport Distance Onshore

Figure 14. CO2 transport cost of tanker trucks as a function of CO2 flow and transport distance onshore.

Figure 15. CO2 transport cost of tanker ships as a function of CO2 flow and transport distance offshore.

offshore, ship transportation is also very cost-effective due to the large loading capacity (Figure 10B); however, due to the high pressures required, large-scale ship transportation of CO2 is limited by current technology and lack of experience in designing containers for transporting liquid CO2.13 Because the cost of transporting CO2 by ship is sensitive to transport capacity, smaller ships will face relatively high transport costs, whereas an evolution toward higher capacities may result in a decrease in transport costs. The delivery distance affects the costs of all transportation modes (Figure 11). For transportation onshore, pipelines are relatively insensitive to the distance, whereas tanker trucks are very sensitive to the distance (Figure 11A). Tanker railcars are

also relatively insensitive to the distance, but this option can be expensive at the current stage due to the high capital cost of the transport mode using containers of relatively small capacity. Thus, tanker trucks are preferable over other transportation modes over short distances (110 km), tanker railcars are preferable for moderate distances, and pipelines are most efficient for long distances (>10 km). For transportation offshore, cost of transport using pipelines is more sensitive to the distance than is transport using tanker ships (Figure 11B). Pipelines are less expensive than tankers for short-distance transport (1000 km). 6312


Industrial & Engineering Chemistry Research Transportation costs of all delivery modes depend on the distance and CO2 flow (Figures 1215). Increases in transport distance and CO2 quantity affect the costs of each transport mode. Transportation costs of pipelines depend very strongly on both the distance and CO2 flow (Figure 12): at very low flows and long distances the price is very high, but at high flows and moderate distances, the cost is low; this pattern becomes more extreme as pipe diameter increases. Transport costs of tanker railcars are relatively independent of CO2 flow rate (Figure 13). However, the transport distance affects the number of transport units and operating costs, so it increases total delivery costs. Transport costs of tanker trucks have a slight dependence on the distance and are more sensitive than costs associated with tanker railcars, because the capacity of tanker trucks is lower than that of railcars (Figure 14). In contrast, transport costs of tanker ships are decrease exponentially as the flow rate increases, but are relatively insensitive to the distance (Figure 15). Ship transport becomes costcompetitive with pipeline transport over larger distances and quantities, but has the disadvantage of requiring intermediate storage capacity and delaying loading and unloading at harbors. We determined the lowest-cost transport mode for 195 combinations of distance (5500 km) and flow rate (0.55000 kt CO2 y1) (Table 16). Tanker trucks were cheapest for low flow rates and short distances, but tanker railcars were cheapest at short to medium distances, and pipelines were cheapest for large flow rates, regardless of transport distances.

6. CONCLUSIONS This paper has introduced a scalable and comprehensive CCS infrastructure model that estimates profit, provides the optimal configuration of the CCS infrastructure, and identifies optimal CCS technologies. The proposed model is uniquely able to systematically address many problems related to planning the infrastructure for CO2 utilization and disposal under the mandated reduction of CO2 emissions. The aims of this work were (i) to develop quantitative tools that can support strategic decisions in CCS infrastructure design and operation; (ii) to identify the main data requirements for various components of the CCS infrastructure such as utilization, capture, storage, sequestration or transport; and (iii) to assess the capability of the CCS infrastructure design models to address such problems for treating CO2 on the east coast of Korea in 2020. On the basis of the results obtained, construction of a CCS infrastructure would be expensive at the current stage of technological development because of the high capital cost and operating cost of the small-capacity CCS facilities. However, because more costeffective CCS technologies with expandable capacity are likely to be developed in the near future, the construction of CCS infrastructure may bring many benefits. ’ AUTHOR INFORMATION Corresponding Author

*Tel. þ82-54-279-2274. Fax. þ82-54-279-5528. E-mail: iblee@ postech.ac.kr.

’ ACKNOWLEDGMENT This paper was supported by the Korea Research Foundation Grant funded by the Korea Government (MOEHRD, Basic Research Promotion Fund) (KRF-2008-313-D00178).

ARTICLE

’ NOMENCLATURE Indices

c = type of capture facility d = pipeline diameter e = product form g = geographical region g0 = geographical region (g0 6¼ g) i = physical form of CO2 l = type of transport mode m = type of intermediate storage facility p = type of utilization facility or production facility s = type of sequestration facility si = type of source industry sp = source plant name Parameters

Ccapmax i,c,si,sp,g = maximum CO2 capture capacity of facility type c in source plant sp of industry type, si t CO2 y1 min Ccapi,c,si,sp,g = minimum CO2 capture capacity of facility type c in source plant sp of industry type si, t CO2 y1 CCCi,c,si,sp,g = capital cost of building CO2-capture facility type c capturing in source plant sp of industry type si in region g $ CCRfacility = capital charge rate of facilities the rate or return required on invested capital cost 0 e CCRfacilitye 1 CCRpipeline = capital charge rate of pipelines the rate or return required on invested capital cost 0 e CCRpipeline e1 CCRtruck/railcar = capital charge rate of tanker trucks and railcars the rate or return required on invested capital cost 0 eCCRtruck/railcare 1 CCRship = capital charge rate of tanker ships the rate or return required on invested capital cost 0 e CCRship e 1 LR = learning rate cost reduction as technology manufacturers accumulate experience 0 e LR e 1 CEUc = upper bound of CO2 capture efficiency for type of capture facility c 0 e CEUc e 1 CUFe,p = CO2 use factor of product form e in utilization facility type p, t CO2 t1 or t CO2 3 L1 DWl = driver wage of transport mode l, $ h1 Ei,si,sp,g = amount of CO2 emitted from source plant sp of industry type si in region g, t CO2 y1 FEl = fuel economy of transport mode l, km 3 L1 FP l = fuel price of transport mode l, $ L1 GE l = general expenses of transport mode l, $ y1 GScapi,g = available geological capacity for sequestering CO2 in region g t CO2, y1 0 Ll,g,g = average delivery distance between regions g and g0 by transport mode l onshore, km 3 trip1 LMRi = level of mandated requirement of reducing CO2 emissions LOl,g,g0 = average delivery distance from harbor region g onshore to sequestration region g0 offshore by transport mode l, km trip1 LUTl = Load/unload time of transport mode l, h trip1 Mcapmax i,m = maximum storage capacity of facility type m to store CO2 in physical form i, t CO2 y1 min Mcapi,m = minimum storage capacity of facility type m to store CO2 in physical form i, t CO2 y1 MCCi,m = capital cost of establishing intermediate storage facility type m storing CO2 in physical form, i $ MEl = maintenance expenses of transport mode l, $ km1 6313


Industrial & Engineering Chemistry Research n = total number of regions 1 Pcapmax e,p = maximum CO2 production capacity of facility type p, t y 1 or L y 1 Pcapmin e,p = minimum CO2 production capacity of facility type p, t y 1 or L y PCCe,p = capital cost of establishing utilization facility type p producing product form e, $ Qmax i,l = maximum flow rate of CO2 in physical form i transported by transport mode l t CO2, y1 min Qi,l = minimum flow rate of CO2 in physical form i transported by transport mode l t CO2, y1 max Scapi,s = maximum CO2 sequestration capacity of facility type s t CO2, y1 min Scap i,s = minimum CO2 sequestration capacity of facility type s t CO2, y1 SCCi,s = capital cost of establishing CO2 sequestration facility type, s $ SPl = average speed of transport mode l, km h1 SSF = safety stock factor of CO2 inventory within a intermediate storage facility, % TCapi,l = capacity of transport mode l to transport CO2 in physical form i, t CO2 trip1 T = target amount of CO2 to be reduced by CCS facilities, t CO2 y1 TMAl = availability of transport mode l, h y1 TMCi,l = cost of establishing transport mode l to transport CO2 in physical form i, $ TPCapi,l,d = capacity of pipeline with diameter d to transport CO2 in physical form i, t CO2 y1 TPICoffd = total capital cost of installing pipeline with pipe diameter d offshore, $ km1 TPICond = total capital cost of installing pipeline with diameter d onshore, $ km1 TPOCoffd = total operating cost of pipeline with pipe diameter d offshore, $ km1 t CO21 TPOCond = total operating cost of pipeline with pipe diameter d onshore, $ km1 t CO21 UCCi,c,si = unit capture cost for CO2 captured by capture facility type c in source industry si, $ t CO21 UCCSi = utilization of CCS as CO2 reduction technology UMCi,m = unit storage cost for CO2 in physical form i stored by intermediate storage facility type m, $ t CO21 UPCe,p = unit production cost for product form e produced by utilization facility type p $ t1 or $ L1 USBe,p = unit selling benefit of product form e produced by utilization facility p, $ t1 or $ L1 USCi,s = unit sequestration cost for CO2 sequestered by sequestration facility type s, $ t CO21 R = small number to limit the number of pipelines Binary Variables

BPe,p,g = one if product form e is produced by utilization facility type p in region g, otherwise 0 BCi,c,si,sp,g = 1 if CO2 in physical form i is captured by capture facility type c in source plant sp of industry type si in region g, 0 otherwise Xi,l,g,g0 = 1 if CO2 in physical form i is to be transported from region g to g0 by transport mode l, 0 otherwise Continuous Variables

Ci,c,si,sp,g = amount of CO2 in physical form i captured by capture facility type c in source plant sp of industry type si in region g, t CO2 y1 FCC = facility capital cost, $ y1

ARTICLE

FCship = fuel cost for CO2 transportation by tanker ship, $ y1 FCtruck/railcar = fuel cost for CO2 transportation by tanker truck and railcar, $ y1 FOC = facility operating cost, $ y1 GCship = general cost for CO2 transportation by tanker ship, $ y1 GCtruck/railcar = general cost for CO2 transportation by tanker truck and railcar, $ y1 LCship = labor cost for CO2 transportation by tanker ship, $ y1 LCtruck/railcar = labor cost for CO2 transportation by tanker truck and railcar, $ y1 MCship = maintenance cost for CO2 transportation by tanker ship, $ y1 MCtruck/railcar = maintenance cost for CO2 transportation by tanker truck and railcar, $ y1 Mi,m,g = inventory of CO2 in physical form i stored by intermediate storage facility type m in region g, t CO2 y1 Pe,p,g = amount of product form e produced by utilization facility p in region g, tonne y1 or L y1 Qi,l,g,g0 = flow rate of CO2 in physical form i transported by transport mode l between regions g and g0 , t CO2 y1 Qpipelinei,l,g,g0 ,d = flow rate of CO2 in physical form i transported by pipelines with diameter d between regions g and g0 , t CO2 3 y1 Si,s,g = amount of CO2 in physical form i sequestered by sequestration facility type s in region g, t CO2 y1 TAB = total annual benefit, $ y1 TAC = total annual cost, $ y1 TAP = total annual profit, $ y1 TCC = transport capital cost, $ y1 TCCoffshore = transport capital cost for CO2 offshore, $ y1 TCCoffshorepipeline = transport capital cost for CO2 transport via pipeline offshore, $ y1 TCCoffshoreship = transport capital cost for CO2 transport via tanker ship offshore, $ y1 TCConshore = transport capital cost for CO2 onshore, $ y1 TCConshorepipeline = transport capital cost for CO2 transport via pipeline onshore, $ y1 TCConshoretruck/railcar = transport capital cost for CO2 transport via tanker truck and railcar onshore, $ y1 TOC = transport operating cost, $ y1 TOCoffshore = transport operating cost for CO2 offshore, $ y1 TOCoffshorepipeline = transport operating cost for CO2 transport via pipeline offshore, $ y1 TOCoffshoreship = transport operating cost for CO2 transport via tanker ship offshore, $ y1 TOConshore = transport operating cost for CO2 onshore, $ y1 TOConshorepipeline = transport operating cost for CO2 transport via pipeline onshore, $ y1 TOConshoretruck/railcar = transport operating cost for CO2 transport via tanker truck and railcar onshore, $ y1 Ui,p,g = amount of CO2 used by utilization facility p in region g, t CO2 y1 ug = number of regions visited after visiting region g Integer Variables

NMi,m,g = number of intermediate storage facilities of type m storing CO2 in physical form i in region g NSi,s,g = number of well or injection facilities of type s sequestering CO2 in region g NTPoffi,l,g,g0 ,d = number of pipeline with diameter d for transporting CO2 in physical form i from harbor region g onshore to sequestration region g0 offshore 6314


Industrial & Engineering Chemistry Research NTPoni,l,g,g0 ,d = number of pipeline with diameter d for transporting CO2 in physical form i between regions g and g0 onshore NTUoffi,l = number of transport units of type l offshore for CO2 in physical form i NTUoni,l = number of transport units of type l onshore for CO2 in physical form i

’ REFERENCES (1) Baumert, K.; Herzog, T.; Pershing, J. Navigating the NumbersGreenhouse Gas Data and International Climate Policy; Report of the World Resources Institute; 2005. (2) Benson, S. Carbon dioxide reuse and sequestration: The state of the art today. In Energy 2000: State of the Art, 2000: pp 205226. (3) Energy Technology Perspectives 2010; International Energy Agency, 2010. (4) Metz, B. D., O. De Coninck, H. Loos, M. Meyer, L. Carbon Dioxide Capture and Storage; IPCC Special Report; 2005. (5) Rubin, E. S.; Chen, C.; Rao, A. B. Cost and performance of fossil fuel power plants with CO2 capture and storage. Energy Policy 2007, 35 (9), 4444–4454. (6) McCollum, D. L. Techno Economic Model for Carbon Dioxide Compression, Transport and Storage and Correlations for Estimating Carbon Dioxide Density and Viscosity; Institute of Transportation Studies University of California: Davis, CA, 2006. (7) Middleton, R. S.; Bielicki, J. M. A scalable infrastructure model for carbon capture and storage: SimCCS. Energy Policy 2009, 37 (3), 1052–1060. (8) van den Broek, M. Feasibility of storing CO2 in the Utsira formation as part of a long term Dutch CCS strategy. An evaluation based on a GIS/MARKAL toolbox. Int. J. Greenhouse Gas Control 4(2), 351366. (9) Rao, A. B.; Rubin, E. S. Identifying cost-effective CO2 control levels for amine-based CO2 capture systems. Ind. Eng. Chem. Res. 2006, 45 (8), 2421–2429. (10) Almansoori, A.; Shah, N. Design and operation of a future hydrogen supply chain: Snapshot model. Chem. Eng. Res. Des. 2006, 84 (6A), 423–438. (11) McCoy, S. T.; Rubin, E. S. An engineering-economic model of pipeline transport of CO2 with application to carbon capture and storage. Int. J. Greenhouse Gas Control 2008, 2 (2), 219–229. (12) Almansoori, A.; Shah, N. Design and operation of a future hydrogen supply chain: Multi-period model. Int. J. Hydrogen Energy 2009, 34 (19), 7883–7897. (13) Svensson, R. O.; M. Johnsson, F.; Stromberg, L. Transportation systems for CO2—Application to carbon capture and storage. Energy Convers. Manage. 2004, 45 (1516), 2343–2353. (14) Miller, C. E.; Tucker, A. W.; Zemlin, R. A. Integer Programming Formulation of Traveling Salesman Problems. J. ACM 1960, 7 (4), 326–329. (15) Li, Y.;Biofuels from microalgae. Biotechnol. Prog. 2008, 24 (4), 815–820. (16) EPA Enforcement Reduces Threat from Polyvinyl Chloride Manufacturing Plants Enforcement Alert 2007, 9(3). (17) Jo, W. Y.; Woo, D. J. Characteristics of biodegradable plastics (greenpol). J. KOWREC 2001, 9 (1), 30–35. (18) Park, S. H., Kwon, S.J.; , W. Y. Oh. Economic evaluation of CO2 ocean sequestration in Korea. In Proceedings of the ISOPE Ocean Mining Symposium; 2007. (19) National Energy Committee(NEC). The 1st National Energy Master Plan; The 3rd National Energy Committee Report 2008; 2008. (20) Economic indicators: Chemical Engineering Plant Cost Index (CEPCI): Marshall & swift equipment cost index. Chem. Eng. 2010, 117(4), 80. (21) Intergovernmental Panel on Climate, C., 2006 guidelines for greenhouse gas inventories, 2006.

ARTICLE

(22) Davison, J. Performance and costs of power plants with capture and storage of CO2. Energy 2007, 32 (7), 1163–1176. (23) Williams, R. Six-tenths factor aids in approximating costs. Chem. Eng. 1947, 54 (12), 124–125. (24) Hedle, G., Herzog, H.; , Klett, M.; , The economics of CO2 storage. MIT LFEE 2003003 RP, 2003. (25) Douglas, J. N.; Dracos, J.S. Assess Carbon Dioxide Transportation Options in the Illinois Basin; Midwest Geological Sequestration Consortium: 2004. (26) Bock, B. R.; Herzog, R.; Klett, H.; Davison, M.; De la Torre Ugarte, J.; Simbeck, D. Economic Evaluation of CO2 Storage and Sink Options; 2003. (27) Kongsjorden, H.; Karstad, O.; Torp, T. A. Saline aquifer storage of carbon dioxide in the Sleipner project. Waste Manage. 1998, 17 (56), 303–308. (28) Kang, S. G.; Huh, C. The latest progress on the development of technologies for CO2 storage in marine geological structure and its application in Republic of Korea. J. Korean Soc. Mar. Environ. Eng. 2008, 11 (1), 24–34. (29) Kim, Y.-J. Ocean Bio-Energy. BT NEWS 2009, 16(1), 618. (30) Korea Institute for Industrial Economics & Trade, Research Report 531, 2008. (31) Lie, J. A. V.; Hcogg, T.; Grainger, M. B.; D. Kim, T. J.; Mejdell, T. Optimization of a membrane process for CO2 capture in the steelmaking industry. Int. J. Greenhouse Gas Control 2007, 1 (3), 309–317. (32) Gadalla, M.;Estimation and reduction of CO2 emissions from crude oil distillation units. Energy 2006, 31 (13), 2062–2072. (33) Mollersten, K.; Yan, J.; Moreira, J. R. Potential market niches for biomass energy with CO2 capture and storage—Opportunities for energy supply with negative CO2 emissions. Biomass Bioenergy 2003, 25 (3), 273–285.

’ NOTE ADDED AFTER ASAP PUBLICATION This paper was published on the Web on April 15, 2011. An Acknowledgment paragraph was added to the paper, and the corrected version was reposted on April 22, 2011.

6315


Development of a Scalable and Comprehensive Infrastructure

Recommend Documents