## Abstract

Even though almost all components of an integrated gasification combined cycle (IGCC) power plant are proven and mature technologies, the sheer number of them, the wide variety of competing technologies (e.g., gasifiers, gas clean-up systems, heat recovery options), and system integration options (e.g., cryogenic air separation unit and the gas turbine), including the recent addition of carbon capture and sequestration (CCS) with its own technology and integration options, render fundamental IGCC performance analysis a monumental task. Almost all published studies utilize highly complex chemical process and power plant heat balance software, including commercially available packages and in-house proprietary codes. This makes an objective assessment of comparable IGCC plant designs, performance (and cost), and other perceived advantage claims (IGCC versus other technologies, too) very difficult, if not impossible. This paper develops a coherent simplified parametric model based on fully physics-based grounds to be used for quick design performance assessment of a large variety of IGCC power plants with and without CCS. Technology parameters are established from complex model runs and supplemented by extensive literature search. The model is tested using published data to establish its confidence interval and is satisfactory to carry conceptual design analysis at a high level to identify promising alternatives and development areas and assess the realism in competing claims.

## Introduction

The integrated gasification combined cycle (IGCC) power plant has been the most promising clean coal technology for more than two decades. Several large-scale commercial IGCC power plants have been in operation for many years to the point that the technology can safely be considered field proven [1,2]. Nevertheless, the large capital cost driven by the immense size, complexity, and construction time of IGCC power plants prevented the technology from a more widespread acceptance. Even so, IGCC's favorable emission characteristics (vis-à-vis the conventional coal-fired thermal power plants) and especially its amenability to carbon capture and sequestration (CCS) have so far ensured that research and development of the technology (as well as commercial interest in IGCC) is as active as ever. It is expected to remain so for the foreseeable future due to the abundance of coal as an affordable fossil fuel for electric power generation—as long as its detrimental effects on the environment can be eliminated in an economically and technically feasible manner.

Over the last two decades, many excellent IGCC studies have been published. These studies explored key competing technologies from a performance and cost trade-off perspective [3,4]. All published studies utilize highly complex chemical process and power plant heat balance software, including commercially available packages such as Aspen Plus and/or HYSYS [5], PRO/II [6], GateCycle [7], GT PRO [8], and in-house proprietary codes. Complex simulation software is vital for hardware design and performance evaluation (design as well as off-design). Some software packages also include detailed capital cost estimation add-ins to facilitate trade-off studies to establish IGCC's position vis-à-vis competing clean coal and other electric power generation technologies. An extensive list of recently published works on IGCC models by Perez-Fortes et al. [9] points to Aspen Plus as the most widely used software. (Even then, gasification modeling is mostly done via first principles encapsulated in computer models developed by the researchers using programming languages such as C++ or computing platforms such as Matlab or Microsoft Excel.) Recently, a combination of Aspen Plus (for the process plant) and GT PRO (for the power plant) was used by researchers to model the entire IGCC plant (e.g., Dennis et al. [10]). Note that either software is capable to model the entire IGCC power plant with varying fidelity for plant subsystems. Nevertheless, the primary strength of either, i.e., chemical process modeling for Aspen and gas turbine (GT) and combined cycle (CC) modeling for GT PRO, precludes in-depth study of design options pertaining to all subsystems on a single platform. In addition to commercial software packages, proprietary, in-house calculation platforms capable of simulating the entire IGCC plant are also available in published literature, exclusively from academic researchers (e.g., see Chiesa and Lozza [11] and references listed therein).

Regardless of the particular modeling platform(s) used in obtaining them, it is practically impossible to reproduce the published IGCC performance numbers. The complexity of the models, the large number of model icons and inputs (hundreds of the former and literally thousands of the latter), myriad techniques used in combining different platforms, and obtaining the iterative solutions preclude a full-blown description of the system in the limited space available. (This is in addition to the obvious problem that one would have to pay the significant fees to obtain the requisite commercial software and go through the very steep learning curve of using them for the task at hand.) The end result is the lack of transparency, wide variation in performance claims for nearly identical systems, and impossibility of making a comparison among different claims on a truly common basis. Recently, Field and Brasington [12] identified the same problem and proposed an Aspen Plus “baseline” model, which is made available to the public in its entirety for in-depth review and evaluation.

A simplified model combining key IGCC subsystems in a coherent manner, which is amenable to a parametric evaluation to highlight the performance characteristics of most (if not all) IGCC plant variants, is essential. Such a simplified mathematical model of the IGCC plant is described at a high level by Pruschek [13]. The structure is similar to what is proposed herein; however, no details on model implementation were provided. A similar performance calculation structure (including cost estimating models) was provided by Rubin et al. [14] along with all requisite formulae with the exception of steam turbine (ST) performance calculation. Zhu and Frey [15] proposed a simple parametric model for the CC power block with focus on the GT.

This paper describes a simplified parametric approach to the performance calculation of an IGCC power plant. The resulting model is intended for the rapid and reasonably accurate conversion of a known GT performance (e.g., from a detailed, rigorous model) into overall plant performance. The plant performance is expressed in terms of net plant output and efficiency. The model is not intended for detailed design or off-design calculations. It is intended for the following applications:

• competitive syngas-fired GT performance evaluation and comparison on a common overall plant basis

• syngas-fired GT design space exploration (i.e., compressor pressure ratio, PR, firing temperature, amount of air extraction, diluent injection, and others) on an IGCC basis

• syngas-fired GT performance optimization in a limited design space covering gasification, gas cleanup, and oxygen production technologies with different feedstocks

• sensitivity and/or uncertainty analysis using Crystal Ball [16] Monte Carlo simulations

The model assumes that detailed and rigorous GT design performance data are available, either in the form of fixed inputs or a “live” model from a commercially available software package or an in-house code. Using several key GT design data such as exhaust conditions, syngas heat consumption, etc., remaining plant performance drivers are estimated via simple ratios and transfer functions. The key philosophy underlying the simple modeling approach, described below in detail, is that, from a practical GT-centric point of view, the IGCC plant is simply a gas-fired GTCC power plant with a “giant fuel gas skid.” (The GTCC power plant and the “fuel skid” are commonly referred to as power and process blocks; e.g., see Fig. 1.)

Fig. 1
Fig. 1
Close modal

In order to build the model in a logical and coherent manner and use it appropriately for the aforementioned purposes, one should be able to identify, quantify, and/or estimate the key subsystems of the process block and their functionalities. From a pure performance perspective (i.e., generation of net electric power and the associated thermal efficiency or, equivalently, fossil fuel consumption), the process block of an IGCC gas turbine has four key attributes:

• consumption of solid or liquid feedstock (e.g., coal, petcoke, oil shale, etc.)

• consumption of electric power, which is debited to the gross (generator) output of plant prime movers

• net consumption and/or generation of useful thermal energy, which, in the form of steam, is utilized by the steam turbine (ST) of the power plant for electric power generation

• generation of clean, gaseous fuel (which is referred to as synthesis gas or, in short, syngas)

The process block has three major components, which are bona fide plants in their own right:

• gasification plant (O2 or air-blown; includes syngas cooler)

• gas cleanup plant

• oxygen plant (if the gasifier is O2-blown) or air separation unit (ASU)

The gasification plant (GP), as shown in Fig. 1, has two subsystems:

1. (1)

gasifier

2. (2)

high-temperature gas cooling (HTGC)

1. (a)

2. (b)

quench

Strictly speaking, the next three subsystems are parts of the gas cleanup plant (GCP):

1. (1)

scrubber

2. (2)

CO shift reactor

3. (3)

low-temperature gas cooling (LTGC)

From a conceptual perspective, however, it is more convenient (at least in the opinion of the authors) to consider them an integral part of an extended GP. The gasifier converts the solid or liquid hydrocarbon feedstock to a gaseous mixture via partial oxidation. As such, the main product of this extended GP is production of raw syngas (SG) at a temperature suitably low for the GCP. The gasification process takes place at temperatures of 1200–1400 °C (2200–2600 °F) and pressures of 30–60 bar (435–870 psi). The resulting gas contains CO, H2, CH4, and other fuel constituents, which can be referred to as the desirable products (i.e., suitable to be used as GT fuels) in addition to the undesirable products such as CO2, H2S, NH3, particulate matter (PM), and neutral products such as N2 and H2O vapor.

If the raw SG from the gasifier was not so hot and so “dirty,” it could be directly used in the GT combustor and one would not be compelled to write the current paper. Alas, environmental regulations and even more stringent GT hardware design and life requirements preclude the utilization of the raw SG as turbine fuel. Thus, it is first cooled to a more reasonable temperature either in the RSC (by making steam at a high pressure) or via quench and “scrubbed” with water to remove particulates. Scrubbing also removes some NH3 and further cools the syngas to about 200 °C. (This is the so-called cold gas clean-up (CGCU) process. Alternative hot gas clean-up (HGCU) processes have been investigated in the past for their potential benefits (lower capital cost and higher efficiency) but they did not overcome their technical difficulties. For the most common variant of gasification technology for IGCC applications, slagging entrained-bed systems, the efficiency benefit was about 1 ppt [17].)

If the IGCC power plant is designed for CCS, the next step is the so-called “sour shift” process, where a catalyst-filled reactor converts a significant portion of the CO in the raw SG to CO2. This reaction is exothermic and typically generates intermediate pressure (IP) steam, which is exported to the power block for power generation in the ST. It also increases the syngas H2/CO ratio from less than 1.0 (for most gasifiers) to 2.0 or even 3.0 (suitable for substitute natural gas (SNG) production). In plants without CCS, a COS hydrolysis reactor is required to reduce the COS content for easier sulfur removal. In plants with CCS, this conversion takes place simultaneously with the shift reaction and no separate hydrolysis reactor is needed.

Whether CO shift and/or COS hydrolysis reactors are present or not, the raw SG is still too hot for the acid gas removal (AGR) process. In the LTGC section, still hot raw syngas is cooled down to a temperature suitable to the cleanup process (e.g., about 38 °C). A significant part of the heat recovered during the cooling process is utilized to generate low pressure (LP) or IP steam and sent to the power block (parts might be utilized in the process block).

While there is a variety of processes for AGR, either commercially available or under development, the most common technique involves absorption into a liquid with chemical (e.g., methyl diethanolamine (MDEA), etc.) or physical (e.g., Selexol, Rectisol, etc.) solvents. The selection of the optimal AGR technology in the IGCC is controlled by factors such as gas flow rate, concentration of acid gases, and the need for removal of CO2 (i.e., a plant to be built with or retrofitted to CCS) as well as H2S. Detailed cost/performance tradeoff is required for a final choice. However, the most likely choice for the high-pressure systems is a physical solvent process. Whatever the chosen technology, the process involves absorption (removal of acid gases from the syngas into the liquid absorbent) and solvent regeneration (removal of the acid gases from the liquid absorbent). The latter process requires significant energy, which is typically supplied by LP steam extraction from the CC bottoming cycle for the H2S/CO2 rich solvent. In the plants with CCS, staged flashing is the technique for regeneration of the CO2 rich solvent from the CO2 absorber, which is the second stage of the AGR. The primary unit system in this paper is the U.S. customary system, which is the system used in the authors' company. Equivalent SI unit values are provided in the text. Common conversion factors are provided in the nomenclature where they first appear. The equations are listed in their original form to prevent confusion and errors that may result from conversion to SI units (notwithstanding the needless complexity introduced by conversion factors). Therefore, when substituting parameters into the equations, one should use their original, i.e., U.S. customary, units.

## Simple IGCC Model

### Model Inputs.

The model is anchored to the gas turbine, i.e., performance, number of units in the plant (usually one or two), and the clean syngas heat input at the GT fuel skid inlet. If the syngas information is not available or if the model is intended for a generic study and/or “back of the envelope” type studies, reasonable estimates can be made for a given gasification technology. Representative SG properties for different gasifiers and feedstocks are provided in the literature [18,19].

Detailed calculation of the gas turbine should provide the key information such as output, syngas mass flow rate, exhaust flow, composition and temperature, air extraction, and diluent nitrogen flows (if applicable). For a plant-level performance, gasifier feedstock flow and heating value (lower/net, LHV, or higher/gross, HHV) are also required. Total plant heat consumption (HC) is the product of the two. Secondary information includes feedstock sulfur content (% by mass) and carbon capture effectiveness (as a %), which are used in the model for adjustment of key ratios. Finally, steam (import) and boiler feed water (export) properties are needed to estimate the power block ST power generation due to steam imported from the process block heat exchangers.

### Model Structure.

The model is essentially a mathematical representation of the IGCC plant Sankey diagram, which is a visual depiction of the distribution of the power plant fuel energy input among key energy streams crossing the system boundary. The plant performance is expressed in terms of net plant output and efficiency. Plant net output is found by rolling up the total output of the prime movers and syngas expander (if present) and subtracting from that the total auxiliary power consumption:
$W·IGCC=NGT·W·GT+W·ST+W·SGX-W·AUX$
(1)
Syngas expander will be discussed later in the paper. Total plant auxiliary power consumption is found by rolling up the individual items, which will be defined and calculated in the following sections:
$W·AUX=W·GSF+W·GCP+W·ASU+W·CC$
(2)
Guidelines published by Gülen [20] (specifically, the detailed breakdown in Table 3 therein) are recommended for estimating the auxiliary power consumption of the power block, $W·CC$. The total power consumption of the GCP is the sum total of H2S and CO2 removal (capture) auxiliary power and CO2 compressor power, i.e.,
$W·GCP=W·H2S+W·CO2+W·CO2C$
(3)
If the IGCC plant is not equipped for CCS, the last two are zero. The total power consumption of the GP is essentially the auxiliary load associated with the gasifier, which can be estimated as
$W·GSF=αGSF·(43.2·M·feed)$
(4)

Key contributors to this item are dependent on the type of gasifier and associated feed system (e.g., “dry” versus “wet” or slurry systems). In wet systems, solid feedstock is preprocessed into slurry by fine grinding and water addition, which is pumped into the burner. In dry systems, pulverized and dried feedstock is pressurized in lock hoppers and fed into the gasifier with a transport gas by dense-phase conveying. Depending on the particular system, individual power consumers include coal grinding and slurry preparation, slurry feed pump, slag crusher, slag handling, etc. A reasonably good value for αGSF is 2.0 kW/STPD, which is adequate for auxiliary power consumption bookkeeping purposes.

Plant net efficiency is found by dividing the net plant power output by total feedstock consumption (in terms of HHV):
$ηIGCC=W·IGCCM·feed·HHVfeed$
(5)

(Note that the contribution of natural gas (NG) or another fuel burned in the Claus unit furnace or the coal dryer (if present, e.g., as in Puertollano [10]) to the denominator of Eq. (5) is ignored.) Proper efficiency definition for coal-fired power plants is extremely important. Herein, per Eq. (5), IGCC net efficiency is defined on an HHV as received (ar) basis, which includes the moisture and ash content of the feedstock. In almost all practical applications, pure electric power generation or combined heat and power (CHP), no use can be made of the latent heat contained in the water vapor in combustion products. Thus, one can argue that using LHV (ar) in the denominator of Eq. (5) presents a more realistic efficiency number (even though the feedstock is purchased on an HHV basis). Another source of confusion stems from the widely used solid feedstock heating value reporting on a moisture and ash free (maf) or dry and ash free (daf) basis, which excludes the moisture and ash content of the fuel in per unit mass heating value definition. For good coals with low moisture and ash content, this does not introduce a significant error (i.e., the denominator of the fraction in Eq. (5) is approximately constant). However, for poor coals such as lignite with very high moisture content, especially for the dry-fed gasification systems, this can be a source of large error and/or confusion. In fact, with certain coal drying systems making use of the vapor released during the coal drying process, LHV-based efficiency definition can be misleading [21]. In order to prevent any confusion and unnecessary clarification, all formulations in this paper are based on as received feedstock heating values and flows.

### Rankine Bottoming Cycle (RBC).

Total gas turbine heat consumption in LHV is given by
$HCGT=M·SG,Clean·LHVSG,Clean$
(6)
$M·SG,Clean=NGT·m·SG,Clean$
(7)
Gas turbine total exhaust gas exergy is
$E·exh=NGT·(m·exh·eexh)$
(8)
where eexh is the exhaust gas exergy per unit mass, which can be estimated (based on a reference state of 1 atm (absolute) and 15 °C) from the following formula [22]:
$eexh=0.001628·Texh1.60877$
(9)
The formula is valid between 900 °F and 1200 °F with a zero enthalpy reference of 77 °F for exhaust gas composition typical of 100% methane GT fuel. Depending on the syngas composition, the error is −1.5% (no CCS) to +2% (with CCS), which is not worth developing a more complex transfer function calculation and, if desired, a property package such as JANAF [23] can be used with the known composition. A simple correction to Eq. (9) for known GT exhaust gas moisture fraction yH2O is as follows
$eexh=0.001628·Texh1.60877·(0.9536+0.526·yH2O)$
(10)
The second law of thermodynamics asserts that the maximum power that can be generated by utilizing the energy in any “waste heat” stream (e.g., the exhaust of the GT) is exactly equal to the exergy of the said stream. The exergetic efficiency of the RBC is defined as the fraction of the GT exhaust exergy that is converted into net RBC work. For a CC, this results in
$ɛRBC=W·RBCE·exh$
(11)
Net RBC work is the difference between the ST generator output and the power consumed by the cycle feed pumps, so that
$W·ST=ɛRBC·E·exh1-λfp$
(12)
where λfp is the power consumption of the feed pumps as a fraction of the ST power output (see Ref. [20]). Based on the premise that there is a well-designed (or optimal) RBC design for a given GT exhaust, different technology curves in the form of f(Texh) can be generated. Such a curve is given in Gülen and Smith [24]. This optimal curve goes through the data points representing the RBC exergetic efficiencies extracted from the trade publication data and is adequately described by the following formula:
$ɛRBC=0.2441+0.0746·(Texh100)-0.00279·(Texh100)2$
(13)

This equation is very well suited to CC analysis of air-cooled GTs with the implicit assumption of a well-designed Rankine bottoming cycle based on today's most optimistic state-of-the-art (SOA) technology and aggressive equipment design specifications. Thus, it represents three-pressure reheat (3PRH) systems based on advanced F-class gas turbines with exhaust temperatures between 590 °C and 670 °C and heat recovery steam generator (HRSG) stack temperatures of about 82 °C. Typical IGCC bottoming cycles for gasifiers with RSC are two-pressure reheat (2PRH) systems with HRSG stack temperatures of about 250 °F. The reason for only two pressure levels is the large high pressure (HP) economizing and superheating duties in the HRSG associated with the RSC. This leaves relatively little exhaust gas energy for IP steam production (maybe for a few thousand pounds per hour). Economically, it makes sense not to build an IP section (superheater and evaporator) for that meager IP steam production opportunity. The high exhaust gas stack temperature is a direct result of the high-temperature condensate (∼230 °F) coming from the plant deaerator (to prevent sulfuric acid condensation on economizer tubes). Therefore, application of a reduction of 8 ppt to the SOA RBC exergetic efficiency is proposed to establish a suitable basis for IGCC applications. This should return a value of ∼65–68% at the GT exhaust temperatures typical for syngas-fired units.

In an IGCC power plant, the RBC has significant (net) exergy input in addition to the GT exhaust flow. In general, this additional exergy source is in the form of net steam import from the process block (i.e., the gasifier radiant and/or convective syngas coolers). By far the largest contributor is the HP steam generated in the RSC of the gasifier, followed by IP/LP steam generation in the LTGC section. The additional ST power output derived from the energy imported from the process block via LP, IP, and/or HP steam produced in various syngas coolers (designated by the subscript i in the formulas below) can be estimated as follows:
$W·'ST,i=ɛ'·Q·Net,i·(1-ToT¯stm,i)$
(14)
The net energy import from the process block is given by
$Q·Net,i=m·stm,i·(hstm,i-hfw,i)$
(15)
where hstm is the enthalpy of the imported (usually saturated) steam, hfw is the enthalpy of the boiler feed water exported to the process block (from the HRSG economizer) and $m·stm$ is the amount of steam generated in the syngas coolers. The mean-effective steam temperature is evaluated from the HRSG feed water supply and steam return (import) conditions as [24]
$T¯stm,i=hstm,i-hfw,isstm,i-sfw,i$
(16)
The enthalpies and entropies of water and steam can be evaluated using ASME steam properties [25] from the supply and return pressures and temperatures. The conversion effectiveness ε′ in Eq. (14) is a function of the steam pressure and temperature difference between export (i.e., feed water) and import (i.e., steam) streams [26]. A sensitivity study using GT PRO heat balance simulations showed that its value varies between 80% and 90+%. The following formula can be used to estimate the value of ε′:
$ɛ'=0.6+0.0631·(T¯stm,i-ΔTi100)$
(17)
where ΔTi is a correction, which accounts for the feed water heating in the process block steam generator:
$ΔTi=Tsat(pimp,i)-T¯fw,i=Tsat(pimp,i)-hf(pimp,i)-hfw,isf(pimp,i)-sfw,i$
(18)
Thus, the total ST power output can be estimated as
$W·ST=ɛRBC·E·exh1-λfp±∑iɛ'i·Q·Net,i·(1-ToT¯stm,i)$
(19)

This generic formulation assumes that there are several different net steam import (usually only two) streams from various syngas coolers at different pressures. Note that the “minus” sign is for the net steam export from the power block bottoming cycle. One example of a significant exergy export from the bottoming cycle is GT diluent steam injection. Typically, hot reheat or IP steam at 23 bar (absolute) and 345 °C is used as a diluent in the GT combustor for NOx abatement. As can be seen from the above formula, this is detrimental to the IGCC performance due to the lost ST work. While less steam is needed than N2 for the same level of NOx reduction (about one-third of N2 on a mass flow basis), in general, utilizing N2 as a diluent is more advantageous in IGCC systems.

### Gasifier Types.

Gasifiers are classified based on their reactor types (i.e., moving or fluidized bed, entrained flow), gasifying medium (e.g., steam and air, steam and oxygen), and reaction temperatures (i.e., high temperature “slagging” or low temperature “dry ash”). Key characteristics of existing gasification technologies are given in Refs. [18,19]. For a comparison of oxygen and air-blown gasification systems with a GT perspective, a recent paper by Parulekar [27] is recommended. The simplified model developed herein is exclusively for electric power generation. As such, due to its dominance in the existing plants [1], only the entrained flow technology is considered. (One can certainly develop a parameter group pertinent to a particular gasification technology for specific studies.) From a purely performance impact perspective, differentiating features of major entrained flow gasification systems are type of coal feed, syngas cooling, and reactant, which determine the following key model parameters: (i) cold gas efficiency (CGE), (ii) gasification sensible heat recovery, and (iii) ASU power consumption, which is a strong function of the degree of integration with the GT.

The composition and heating value of the clean syngas are of prime importance to the GT combustor and turbine design. Typical values are cited in the literature [18,19]. The H2/CO ratio is normally around 0.5 for dry-fed gasifiers and around 1.0 for the slurry-fed gasifiers (about 0.3 for the air-blown gasifier). In terms of the raw syngas at the scrubber inlet, syngas from the dry-fed gasifier has very low moisture, e.g., less than 5% (vol) vis-à-vis slurry-fed gasifier raw syngas with 20+% (vol). This is a disadvantage for the dry-fed systems with CCS due to the large steam need (about 2 for minimum steam/carbon ratio) for the water gas shift (WGS) reaction, which is diverted from the power block at the expense of ST power output.

### Gasifier Cold Gas Efficiency.

The key gasifier metric of interest is the CGE. This is the ratio of the heating value of the clean syngas consumed by the GT to the heating value of feedstock consumed by the gasifier (i.e., IGCC plant heat consumption). In terms of absolute values, it is difficult to make a reliable assessment. Gasifier cold gas efficiency is a strong function of the coal type (HHV, sulfur content, etc.), feedstock delivery system, gasifier pressure, and other design features such as syngas or CO2 recycle. For the entrained flow gasifiers with high gasification temperatures (∼1100 °C or higher), the energy supplied to the gasifier (mostly feedstock enthalpy, i.e., heating value) is roughly distributed as follows:

• raw syngas heating value (∼ 85%)

• sensible heat in the raw syngas (12–13%)

• heat losses and slag (2–3%)

In gasifiers with RSC, most of the sensible heat in the raw syngas is recovered during the gas cooling process by means of steam production. (Quench-cooled gasifiers allow only partial recovery.) Before being burned in the GT combustor, raw syngas is cleaned in a separate “chemical plant” (AGR), where sulfur is removed. The clean syngas at the end of the process retains approximately 75% of the HHV of the feedstock (approximately 72% on LHV basis). The basic energy balance described above leads to the definition of CGE, i.e.,
$ηCG=M·SG,CleanM·feed·ϖ·LHVSG,CleanHHVfeed$
(20)
where ϖ is the HHV/LHV ratio of the feedstock. Thus, for a known GT and gasifier (specified by its cold gas efficiency), feedstock mass flow rate $M·feed$ can be calculated as
$M·feed=M·SG,CleanηCG·ϖ·LHVSG,CleanHHVfeed$
(21)

Note that there is no universal agreement on the definition of $ηCG$. In this discussion, $ηCG$ is defined with two key assumptions:

1. (1)

The energy basis for syngas and feedstock is LHV.

2. (2)

The numerator of the efficiency formula Eqs. (20) and (21) is clean syngas to the GT.

The rationale for these assumptions is simple: Clean syngas flow to the GT combustor and its LHV are readily available parameters, which are critical to GT performance simulation. (Recall that the GT simulation is the anchor for the IGCC performance simulation herein.) In the literature, different $ηCG$ definitions are available (e.g., based on syngas and feedstock HHV, etc.) In one commonly used definition, the numerator of the formula is the raw syngas at the exit of the scrubber or syngas coolers, i.e.,
$η'CG=M·SG,RawM·feed·HHVSG,RawHHVfeed$
(22)
Comparing the two cold gas efficiency definitions, one can write
$η'CGηCG=ρ·ϖ'ϖ$
(23)

where ϖ′ is the HHV to LHV ratio of the clean syngas and ρ is the ratio of the total HHV energy content of the raw syngas stream to the clean syngas stream (typically, 1.07 with no CCS and 1.11 with 90% CCS). The energy content ratio ρ depends on different factors such as the gasifier feedstock's sulfur content (i.e., raw syngas H2S content), gas cleanup process and effectiveness (i.e., with or without carbon capture), whether the clean syngas is moisturized or not. These are factors that impact the gas flow rate and heat content (note that H2S has an LHV of 15,235 kJ/kg). In general, a good value for non-CCS and CCS systems is 1.02 and 1.10, respectively. Thus; for example, if a gasifier is quoted with 80% $η'CG$ with a bituminous coal feedstock (ϖ is 1.05), the corresponding $ηCG$ to be used in the current model is:

• 80%·1.05/(1.02·1.07) = 77.0% for a system with no CCS, and

• 80%·1.05/(1.10·1.11) = 68.8% for a system with 90% CCS

Thus, a reduction in CGE from its base value is to be expected when CCS is introduced. The actual value is dependent on the specific gasification and gas cleanup system (typically, 5 to 9 ppt).

### Gasifier Heat Recovery.

In nonquench type gasifiers, the bulk of the heat recovery via HP steam production takes place in the RSC, which can be expressed as a fraction of the gasifier feedstock energy (LHV)
$Q·GSF=θGSF·(M·Feed·LHVFeed)$
(24)

This steam is utilized in the bottoming cycle of the CC plant to generate electric power. The power contribution can be estimated via Eq. (14) with $Q·GSF$ and $T¯stm$, which is evaluated from the HRSG feed water supply and RSC steam return (usually saturated at 115–140 barg) conditions using Eq. (16). Feed water conditions (if not known) can be estimated using a 15 bar adder (to saturated return steam pressure) and 20 deg subcool. Depending on the gasification and gas cooling technology, a second (but much smaller) contribution to the power block ST output can be estimated from the LP (or IP) steam produced in LTGC heat exchangers. The net heat import and the ST power contribution can be evaluated in a manner similar to that for the gasifier via Eqs. (24). and (14) by replacing $θGSF$ with $θGC$. Typical values for non-CCS systems are provided in Table 1.

Table 1

Gasifier heat recovery parameters

θε′p
GSFHR10 to 13%∼90%1500–2000
Q5 to 7%
GCHR1 to 3%∼70%100–300
Q3 to 5%
θε′p
GSFHR10 to 13%∼90%1500–2000
Q5 to 7%
GCHR1 to 3%∼70%100–300
Q3 to 5%

HR = heat recovery in radiant and/or convective syngas coolers; Q = quench-cooled gasifier.

The exact amount and quality of steam production via syngas cooling in multiple locations (e.g., gasifier, LTGC, gas shift reactor, etc.) are subject to system-level optimization (e.g., cost-performance tradeoff), heat exchanger design considerations such as fouling, and available power block hardware to make use of generated steam. (Note that heat import/export via condensate or HRSG feed water heating, heat rejection to plant cooling water, etc. are ignored due to their low exergy content.) Ideally, the values of $θGSF$ and/or $θGC$ should be determined from available information (e.g., technical papers, reports, published articles, or a detailed system model) on the particular gasification technology.

Note that there are two other uses for the raw gas sensible heat: clean syngas fuel heating and moisturization. (A third option is diluent nitrogen moisturization.) For suitably high gasifier pressures (e.g., 60–70 bar or higher), an SG expander can be considered in lieu of heat recovery. The numbers in Table 1 are commensurate with HTGC and LTGC heat recovery for dry syngas fuel at 175 °C to 200 °C at the GT fuel skid inlet with no SG expander. Fuel or diluent nitrogen (if available) moisturization is an effective use of low-grade waste heat for improved system efficiency and reduced combustor flame temperature to control NOx emissions [28]. Adjustments to the heat recovery parameters listed in Table 1 can be made to account for SG expander, fuel moisturization and/or fuel heating to higher temperatures. This will be discussed later in the paper.

Steam (usually HP) is supplied to the WGS reactor in CCS systems. Especially dry-fed gasifiers require significant steam import from the power block because the raw syngas has insufficient H2O vis-à-vis slurry-fed gasifiers. The exothermic shift reaction transfers the fuel heating value from CO to H2 and converts the carbon from CO to CO2. Heat generated during the exothermic shift reaction is recovered for IP or LP steam generation to be utilized in the ST. The net steam import resulting from these two mechanisms should be debited to the ST power generation in a manner similar to that for GT diluent steam injection.

### Coal Types.

Coals are ranked based on their energy and moisture/ash content. About 80% of the world's coal for power generation is bituminous or subbituminous. It is crucial to know the feedstock type and rank when using available gasifier data for calibration of the model parameters discussed herein. In general (but not always), especially for IGCC power generation applications, gasifier performance is quoted for a bituminous coal feedstock. However, lower rank subbituminous and lignite constitute nearly 50% of world coal reserves. The impact of coal quality on IGCC performance is strongest for slurry-fed gasifiers showing the largest variation in energy density of the gasifier feedstock and oxygen demand [21,29]. However, CCS performance loss in slurry-fed systems with quench is much less than in dry-fed systems due to the elimination of steam import (at the expense of ST output) for the shift reaction, i.e., about 4–6 ppt in net IGCC efficiency versus 8–10 ppt, respectively. Typical raw and clean syngas composition for a given gasifier and/or coal type can be obtained from the literature. For correction of a given performance for a different feedstock, data in Table 4 of Ref. [29] can be used.

### Air Separation Unit.

Cryogenic air separation is the commonly used commercial technology for the oxygen plant of the O2-blown gasification systems. The technology has high capacity and high reliability in producing oxygen at purities exceeding 99.5%. For IGCC performance calculations, the key ASU characteristic is the parasitic power consumption associated with the cryogenic distillation process, which is primarily gas compression work and can be estimated as follows:
$W·ASU=αASU·(3600·o·M·Feed)$
(25)
where o is the ratio of the O2 flow rate to the gasifier feedstock flow rate (total of all trains) and αASU is the ASU power consumption per unit O2 flow rate.
$o=M·O2M·Feed$
(26)

The value of o is a feature of the gasifier technology and the particular feedstock. In general, for the same type of coal, slurry-fed gasifiers require more O2 than the dry-fed ones since more heat is needed to vaporize all the water in the slurry. Typical values of o range between 0.7 and 1.2; for quick estimations a good default value is 0.8 for dry-fed and 1.0 for slurry-fed systems. (This parameter is subject to confusion and errors due to the definition of the oxygen and feedstock flows. Herein, the assumption is that (i) O2 from the ASU is 95% pure and (ii) feedstock is on as received basis. When calibrating the model to published data care must be given to the definitions used by respective authors.)

ASU power consumption is the sum total of the power consumption of three compressors: main air compressor (MAC), oxygen compressor, and diluent nitrogen compressor. In general, it is a function of the ASU cold box pressure, gasifier pressure (to which the O2 is compressed), GT pressure ratio, the diluent N2 consumption of the GT (for the diluent N2 compressor), and the GT air extraction (which will reduce the power consumption of the MAC). The ASU is the only process block system that has significant interaction with the GT via air extraction and diluent nitrogen streams and can significantly impact the GT and plant performance. Adjustments to the ASU power can be made for specified air extraction (AE) and diluent injection by simple ratios. A reasonable value for αASU is 250 kW per kpph of O2 (∼2 MJ/kg) with no GT air extraction (i.e., all ASU air is supplied by the MAC) and N2 sent to the GT as a diluent. This assumes a reasonably state-of-the-art compressor with 88% polytropic efficiency, 95% mechanical/electric efficiency, and an F-class GT with nominal compressor PR of 17–18. The other important consideration that goes into this number is related to the individual ASU compressor pressure ratios, which are functions of the ASU pressure, N2 and O2 pressures at the inlet to their respective compressors, gasifier pressure, and GT compressor PR. The number cited above (i.e., 250 kW/kpph = 2 MJ/kg) is based on the following assumptions:

• ASU pressure of 5 bar (75 psia)

• gasifier pressure of 45 bar (650 psia)

• N2 and O2 pressures equal to 90% of ASU pressure

• 95% O2 purity

• all N2 injected to the GT combustor (SOA F-class)

Changes from this basis will strongly impact αASU and a range of 150 to 300 is expected. Oxygen purity is a strong driver, especially above 98% (e.g., see Rubin et al. [14] for a chart, which can be used for adjustment). Adjustments for GT air extraction (replacing air supplied by MAC) and diluent injection can be made via basic rules of thumb resulting in the following formula:
$αASU=(250-450·ξ-35·(2.9-d))·(pGSF650)1/3$
(27)
Equation (25) contains a correction for the gasifier pressures different than the base value 45 bar. For example, for a 1200 psi gasifier (most likely a quench system), this would add ∼20% to the base estimate. Obviously, diluent N2 injection is limited by the amount of N2 available from the ASU, which is approximately
$M·N2=3.3·o·M·feed$
(28)

Typically, for systems without CCS, 100% of nitrogen from the ASU is about 1.2 to 1.4 in terms of diluent-to-fuel ratio, which corresponds to 2.6 to 3.1 in d. Air extraction cannot exceed about 15% to 20% of the GT compressor airflow. (For O2-blown gasification systems, 10% AE would replace about 40% of the MAC airflow.) Previous studies and past experience have shown that the best GT-ASU integration strategy is a combination of air extraction and injection of all N2 from the ASU [30]. This ensures the lowest NOx emissions with maximum possible turbine output (to the extent hardware limits are not exceeded).

IGCC plants with air-blown gasifiers also include a small ASU to supply pressurized nitrogen, which is used for coal transport. Oxygen generated by the ASU is mixed with air extracted from the GT (100% of the oxidant) to the gasifier [27]. Power consumption is about 15% of the ASU for the same size of oxygen-blown gasifier per Eq. (27).

### Syngas Cleanup.

From an overall IGCC plant performance perspective, the gas cleanup plant (GCP) is a consumer of electric power (i.e., pumps and compressors) and heat energy (i.e., steam from the power block and/or various syngas coolers in the process block). In that sense, the following subsystems are of importance:

1. (1)

acid gas removal (AGR)

1. (a)

H2S removal

2. (b)

CO2 removal or capture (with CCS)

2. (2)

CO2 compression (with CCS)

3. (3)

Claus plant (sulfur recovery)

4. (4)

tail gas treatment unit (TGTU)

As far as H2S removal is concerned, the key performance metric is pumping power consumed per unit flow of raw or clean SG (or acid gas removed). The heat energy is usually small (68 MJ per kmol of acid gas removed for estimating purposes [18]) and of low exergy, i.e., the equivalent of a few megawatts of ST power output. While it is relatively easy to keep track of this ST power debit due to AGR regenerator steam load, ignoring it does not introduce a big error into the model within the framework of interest herein. (The values for θGC listed in Table 1 are net of the AGR steam load.) However, heat energy (i.e., steam) consumption can be significant for the CCS systems and should be tracked separately. Requisite adjustments are discussed in the following section.

Data from studies indicate that H2S removal auxiliary power consumption can be estimated as
$W·H2S=αH2S·(3.6·NGT·m·SG,Clean)$
(29)
$αH2S=4.0+1.5·(S-3%)$
(30)

A reasonably good value for αH2S (Selexol-based system) is 4.0 kW/kpph (∼32 kJ/kg). This is for a typical U.S. bituminous coal from Illinois or Appalachia with sulfur content (by mass) of about 3%.

### Carbon Capture and Sequestration.

CO2 capture auxiliary power consumption can be estimated as
$W·CO2=αCO2·M·CO2$
(31)

A reasonable default value for αCO2 is 80 kW/pps (175 kJ/kg) for the solvent based capture unit via chemical absorption (e.g., see Hoffmann et al. [31]). Rigorous models of the actual system, based on chemical or physical solvents, can provide a more accurate number, which can be substituted (if available) but is unlikely to change the final answer by much. Thermal energy consumption by the stripper reboiler is about 600 kW/pps (usually low pressure steam) [31]. No separate accounting is made for the thermal energy. In the absence of specific information, using the values listed in Table 1, the following rules of thumb are recommended:

• Dry-fed gasifier: Set θGSF to zero, multiply non-CCS value of θGC by 3.5.

• Slurry-fed gasifier: Set θGSF to two-thirds of the non-CCS value, multiply non-CCS value of θGC by 2.5.

Estimation of $M·CO2$ for generic IGCC systems with CCS is based on captured CO2 flow rate expressed as a mass fraction of the total raw syngas flow rate $χCO2$:
$χCO2=M·CO2M·SG,Raw$
(32)
Thus, using the clean-to-raw total syngas flow ratio σSG
$M·CO2=χCO2·M·SG,CleanσSG$
(33)
For quick estimations or generic IGCC system evaluations, a reasonable value for $χCO2$ is 0.75. Typical values for σSG are 0.2 and 0.95 for systems with 90% carbon capture and without (coal sulfur 3% by weight), respectively. Following adjustments are proposed for carbon capture effectiveness, ηCap, (with CCS) and coal sulfur by weight S (no CCS):
$σSG=0.20-(ηCap-90%)·0.80 (with CCS)$
(34)
$σSG=0.95-(S-3%)·1.50 (no CCS)$
(35)
CO2 compressor power consumption can be estimated as
$W·CO2C=αCO2C·M·CO2$
(36)

The value of CO2 compressor power consumption and; consequently, αCO2C is a function of storage pressure (typically ∼150 bar), the distance of storage location to the plant (which determines the pipeline and associated pressure loss allowance) and the compression system. For a typical application with intercooled gas compressors, a good value for αCO2C, representing the SOA, is 105 kW per pps of CO2 flow (∼230 kJ/kg). This assumes 85% stage efficiency for the compressor with three flashing pressure levels. This is adequate for auxiliary power consumption bookkeeping purposes, which is essentially insensitive to gas turbine optimization. For a single flash level, a good value is 135 kW/pps (∼300 kJ/kg). There are studies showing 20% reduction CO2 compression power if the CO2 is liquefied during the compression process and then pumped to the final pressure as a liquid [32]. Even further reduction is possible via refrigeration during liquefaction but the benefit in parasitic loss saving is offset by the lost ST power as a result of steam extraction required to drive the refrigeration cycle.

### Syngas Expander.

Gasifier pressures are typically high (30 to 60 bar) and thus present an opportunity to generate additional power via expansion of syngas to pressures commensurate with the GT fuel skid inlet. The latter is typically about 50% higher than the combustor inlet, e.g., around 25 bar for most existing F-class units. Whether a SG expander is present or not is subject to economic optimization due to the design problems associated with gland seals, leakage at valves and flanges, and gas path component materials commensurate with high pressures and temperatures. In general, pump-based slurry-fed systems are more amenable to higher gasification pressures requisite for feasible expander designs than dry-fed systems with lock-hoppers and transport gas conveyor systems (i.e., about 62 bar or higher). For a reasonable design with inlet temperature of 538 °C (1000 °F) (uncooled parts), the following relationship can be used:
$W·SGX=100·ln(πSGX)·M·SG,Clean$
(37)
where πSGX is the syngas expander pressure ratio (about 2 to 3). For a reasonable estimate, using the GT compressor pressure ratio, the following formula can be used:
$πSGX=pGSF2·pamb·πGT$
(38)
Note that the SG expander work from Eq. (37) is no longer available for HTGC heat recovery and θSGX should be subtracted from θGSF:
$θSGX=W·SGXM·Feed·LHVFeed$
(39)

### Syngas Heating and Moisturization.

Utilizing the low-grade waste heat to heat the GT fuel is a standard CC feature to improve efficiency. Advanced F-class units in natural gas (NG) fired applications typically utilize intermediate pressure economizer feed water from the HRSG to heat the fuel gas to about 200 °C (about 400 °F). In IGCC plants, there is enough waste heat in the HTGC and LTGC sections to accomplish this level of fuel heating. Higher temperatures are possible, both in NG-fired CC and IGCC power plants, up to ∼540 °C (1000 °F) or even higher in the latter. However, studies have shown that a point of diminishing returns is reached at around 315 °C, beyond which no significant performance improvement is achieved to warrant the cost and complications associated with materials and design of piping, performance heater and GT fuel skid systems [33].

Fuel gas moisturization is a direct contact heat and mass exchange process (typically in a packed column referred to as fuel gas saturator) utilizing low level waste heat (low pressure HRSG economizer feed water in NG-fired CC) to simultaneously heat the GT fuel gas and increase its mass [34]. The added benefit of moisturization is the reduction of combustor flame temperature for lower NOx emissions. The same benefit is equally available to the cold (∼38 °C) and dry syngas fuel from the AGR in the IGCC power plant. Utilizing the waste heat in the LTGC, moisturizing the clean syngas up to about 20% (volume) of H2O content at about 150 °C is possible. This can be accounted for using the following relationship:
$θSAT=0.18%+0.162·μSG$
(40)

In Eq. (40), μSG is the clean syngas moisture content by volume at the exit of the fuel gas saturator and θSAT is the net heat required to moisturize the fuel gas as a fraction of the gasifier feedstock heat input (LHV). In a study involving fuel gas moisturization, θSAT from Eq. (40) should be subtracted from the θGC listed in Table 1 (unless air extracted from the GT can be utilized for the same purpose). Note that part of the moisturization water can be extracted from the HRSG downstream of the low pressure evaporator and making use of waste heat, which otherwise would be lost through the stack (i.e., no exergy penalty). This is limited by the allowable HRSG stack temperature to prevent sulfuric acid condensation on economizer tubes.

For 260 °C moisturized syngas fuel at the GT fuel skid inlet, θSAT is given by the formula
$θSAT=1.39%+0.183·μSG$
(41)

This level of fuel heating would require high pressure feed water from the HRSG or HP steam from the gasifier syngas coolers (e.g., θSAT is about 5% for 20% fuel moisture). Moisturization heat duty given by Eq. (40) should be debited to θGC. The remainder (if any) and the difference in θSAT between Eq. (41) and Eq. (40) should be debited to θGSF.

Air extracted from the GT (at more than 370 °C) is a high grade heat source. In IGCC plants with ASU-GT integration, it is almost always utilized to heat the diluent N2 from the ASU. Remaining heat can be utilized to heat the fuel gas or nitrogen saturator circulating water, other feed water or for partial heating of the fuel gas. Possibilities are myriad and highly dependent on the GT and ASU N2 compressor designs, which determines extraction air, diluent N2, and moisturized SG flows and temperatures. Based on the GT simulation output, requisite adjustments can be easily made to the heat recovery parameters.

### Summary.

The parameters to be used in the simple IGCC model are listed in Table 2 for quick reference. In the absence of specific information pertaining to particular gasification and/or gas cleanup technologies, the suggested default values can be used. This should suffice for studies focusing on GT design modifications to adopt a natural-gas-fired unit for generic syngas applications. For more in-depth studies, especially those with novel process block technologies, the recommendation is to develop a specific parameter list from available data (e.g. from published studies, detailed process model runs, etc.).

Table 2

Parameters to be used in the simple IGCC model

RangeDefault
Cold gas efficiencyηCG70% to 80%70% (use known value)
O2-to-coal (pps/pps)o0.8 to 1.00.8 (dry fed)
1.0 (slurry fed)
HHV/LHVϖ1.02 to 1.061.04
Sulfur in coal% (wt.)0.3% to 5%3.0%
Gasifier auxiliary kW per feed (STPD)αGSF1.0 to 3.02.0
H2S Removal auxiliary kW per clean SG (kpph)αH2S1.0 to 7.04.0
CO2 Capture auxiliary kW per CO2 (pps)αCO20 to 10080 (90% CCS)
0 (no CCS)
CO2 compression kW per CO2 (pps)αCO2C100 to 135105 (90% CCS)
0 (no CCS)
Clean SG per raw SG (pps/pps)σSG0.2 to 1.00.2 (90% CCS)
0.95 (no CCS)
CO2 per raw SG (pps/pps)χCO20.5 to 0.80.75
Air extraction/W2AE0% to 20%
Diluent N2/O20 to 3.1
ASU compression kW per O2 (kpph)αASU150 to 300250 (0 for air-blown)
QGSF/HCFeedθGSFsee Table 1 12% (heat recovery)
6% (quench)
QGC/HCFeedθGCsee Table 1 2% (heat recovery)
4% (quench)
RangeDefault
Cold gas efficiencyηCG70% to 80%70% (use known value)
O2-to-coal (pps/pps)o0.8 to 1.00.8 (dry fed)
1.0 (slurry fed)
HHV/LHVϖ1.02 to 1.061.04
Sulfur in coal% (wt.)0.3% to 5%3.0%
Gasifier auxiliary kW per feed (STPD)αGSF1.0 to 3.02.0
H2S Removal auxiliary kW per clean SG (kpph)αH2S1.0 to 7.04.0
CO2 Capture auxiliary kW per CO2 (pps)αCO20 to 10080 (90% CCS)
0 (no CCS)
CO2 compression kW per CO2 (pps)αCO2C100 to 135105 (90% CCS)
0 (no CCS)
Clean SG per raw SG (pps/pps)σSG0.2 to 1.00.2 (90% CCS)
0.95 (no CCS)
CO2 per raw SG (pps/pps)χCO20.5 to 0.80.75
Air extraction/W2AE0% to 20%
Diluent N2/O20 to 3.1
ASU compression kW per O2 (kpph)αASU150 to 300250 (0 for air-blown)
QGSF/HCFeedθGSFsee Table 1 12% (heat recovery)
6% (quench)
QGC/HCFeedθGCsee Table 1 2% (heat recovery)
4% (quench)
Table 3

Sensitivity of IGCC net efficiency (percentage points HHV) and output to selected model parameters in Table 2

ParameterηGTCGEαASUθGSFθGCεRBCαH2Sε′
Change (%)+1+1−10+1+1+1−25+1
ΔηIGCC (%)1.000.590.720.350.230.260.060.06
ΔWIGCC (%)0.160.091.830.880.570.650.160.16
ParameterηGTCGEαASUθGSFθGCεRBCαH2Sε′
Change (%)+1+1−10+1+1+1−25+1
ΔηIGCC (%)1.000.590.720.350.230.260.060.06
ΔWIGCC (%)0.160.091.830.880.570.650.160.16
Table 4

Model prediction error (deviation) vis-à-vis published data

Average Absolute ± SDMaximumMinimum
ST MW (%)5.6±4.517.7−9.9
ASU MW (%)7.3±7.029.4−16.2
IGCC Gross MW (%)2.2±1.76.2−3.9
IGCC Gross η(%)1.0±0.72.8−1.7
IGCC Net MW (%)3.9±3.68.1−16.1
IGCC Net η(%)1.4±1.25.6−2.8
Average Absolute ± SDMaximumMinimum
ST MW (%)5.6±4.517.7−9.9
ASU MW (%)7.3±7.029.4−16.2
IGCC Gross MW (%)2.2±1.76.2−3.9
IGCC Gross η(%)1.0±0.72.8−1.7
IGCC Net MW (%)3.9±3.68.1−16.1
IGCC Net η(%)1.4±1.25.6−2.8

Sensitivity of IGCC performance to selected model parameters in Table 2 is summarized in Table 3. The data in Table 3 confirms the well-known recipe to IGCC performance improvement, namely that GT is the key driver of performance and closely followed by gasifier CGE and ASU parasitic power consumption.

## Applying the Model

The simple IGCC model described in the preceding section is intended for specific applications outlined in the Introduction. It is not a bona fide design tool and, as such, it cannot be used to investigate the intricate design details of various IGCC subsystems. The model is primarily geared to engineers involved in the design of GTs for electric power generation. Typically, gas turbines are not designed from a blank sheet for IGCC or other low calorific value gases such as steel mill applications (where the GT fuel is a blend of blast furnace and coke oven gases). Gas turbines designed for natural gas fuel (mostly methane) are modified to fit the specific application (hardware as well as controls). From electric power generation perspective, the primary interest is in the following areas in terms of their impact on IGCC performance (output and efficiency):

• GT design and optimization (mainly firing temperature and PR)

• GT-ASU integration

• gasification technology (for a given GT)

• CCS

• gasifier feedstock (for a given GT and gasifier)

GT design optimization and integration with ASU impact the process block via requisite air extraction and/or diluent injection and to a lesser extent by the quantity of syngas. As far as the first four items are concerned, the model is expected to reproduce the qualitative performance trends dictated by the fundamental characteristics of the pertinent processes. In order to ascertain this capability, selected data from the published sources are compared with the model predictions (Refs. [4,10,35–45]). The IGCC plant data used herein cover the following range:

• quench and heat recovery (RSC) type gasifiers

• oxygen and air-blown gasifiers

• plants with and without CCS

• zero to ∼20% GT air extraction

• zero to full diluent N2 injection

• diluent steam injection

• bituminous feedstock

Unfortunately, no plant data with enough detail could be found for low rank (e.g., lignite) coals. A few published plant data with low rank coals (also several others one should add) turned out to be severely inconsistent and deemed to be unreliable. In fact, this should be considered another confirmation of the usefulness of the model presented herein (i.e., weeding out unreliable performance data). Such cases are left out from the study because it is difficult to judge whether the inconsistencies are due to typos, unreasonable assumptions, or other types of inadvertent mistakes.

The model is applied with the default parameters summarized in Table 2 with the exception of the CGE, which is calculated from the published data. To the extent possible, per availability of detailed system data, requisite adjustments for SG expander, GT steam injection, and SG humidification are made. No system-specific adjustments are made beyond what is described in the main body of the paper. Only in some cases, where discrepancy was simply too big, significant effort has been made to tweak the parameters (strictly per published information) to close the gap between the model and published performance. In some instances, this proved unsuccessful and, as mentioned earlier, those cases with inexplicable inconsistencies have been left out from the comparison.

Similarly, published GT data from the listed references are used in the model. However, reasonable assumptions (for missing information) and corrections are made to ensure heat and mass balance integrity of the GT control volume. As highlighted by the sensitivity data in Table 3, apart from the GT, the two critical subsystems are the ASU and the ST. Model predictions of the ASU power consumption (via Eqs. (25)(27)) and ST power generation (via Eqs. (8)(19) and (24) and the data in Table 1) are shown in Figs. 2 and 3. Model predictions of the IGCC net output and efficiency are shown in Figs. 4 and 5. Absolute average difference between the model predictions and the published data are listed in Table 4.

Fig. 2
Fig. 2
Close modal
Fig. 3
Fig. 3
Close modal
Fig. 4
Fig. 4
Close modal
Fig. 5
Fig. 5
Close modal

The comparison summarized in Figs. 25 and Table 4 suggests that the model is adequate for high-level and consistent comparison of published performance data for a wide variety of IGCC systems on a common basis. The biggest discrepancy is introduced by the plant auxiliary power consumption, which can be traced to the wide variation in auxiliary load scope assumptions and optimistic boundary conditions (e.g., aggressively low steam condenser pressure, feed pump sizing, etc.). It is, therefore, recommended to compare published IGCC performances on an adjusted gross basis, including only the prime movers, SG expanders and the ASU (if present). Standard corrections for ambient conditions and the steam condenser pressure can be made using suitable correction curves.

## Conclusions

A simple IGCC performance model is developed to facilitate syngas fired GT performance optimization and integration studies for IGCC power plants. The model contains simple parametric equations derived from the first principles and can be easily programmed into a spreadsheet. The model is also suitable to evaluation and comparison of published performance data on a common basis. Comparison with published data for a wide range of IGCC plants with and without CCS shows that, even with default parameters, the model is capable to reproduce the plant performance with reasonable error. This ability can be further enhanced by developing system specific parameter sets (for different gasification and gas cleanup technologies) for higher fidelity. The model can also be expanded to incorporate secondary IGCC plant features such as CO2 recycle compressor or diluent nitrogen moisturization.

## Acknowledgment

The authors would like to thank GE Energy for permission to publish.

Nomenclature
cp =

constant-pressure specific heat (Btu/lb-R, 4.1868 kJ/kg-K)

d =

diluent nitrogen-to-oxygen ratio

e =

specific exergy (Btu/lb, 2.326 kJ/kg)

$E·$ =

total rate of exergy transfer (Btu/s or kW, 1.05506 Btu/s)

h =

specific enthalpy (Btu/lb)

$m·$ =

mass flow rate per unit or train (pps, 0.4536 kg/s, or kpph, 453.6 kg/h)

$M·$ =

total mass flow rate for all units or trains in the plant (pps or kpph)

N =

number of units or trains

p =

pressure (psi, 0.06895 bar)

ppt =

percentage points

$Q·$ =

rate of heat transfer (Btu/s or kW)

s =

specific entropy (Btu/lb-R)

S =

coal sulfur by weight (%)

T =

temperature (°F,  °C = [°F – 32]/1.8)

$T¯$ =

mean-effective temperature (°F)

$W·$ =

power (Btu/s or kW)

yH2O =

GT exhaust gas moisture fraction (molar basis)

Greek Symbols
αASU =

oxygen plant power consumption per unit O2 flow rate (kW/kpph)

αCO2 =

carbon capture unit power consumption per unit captured CO2 flow rate (kW/pps = 2.20462 kJ/kg)

αCO2C =

CO2 compressor power consumption per unit captured CO2 flow rate (kW/pps)

αGSF =

gasifier power consumption per unit feedstock flow rate (kW/STPD, 1 STPD is 2000 lbs or 907.2 kg per day)

αH2S =

AGR power consumption per unit clean syngas flow rate, total for all GTs (kW/kpph)

$χCO2$ =

CO2 flow rate (fraction of the total raw syngas flow rate)

ε =

bottoming cycle exergetic efficiency

ε′ =

exergetic conversion effectiveness

η =

efficiency or effectiveness

λfp =

boiler feed pump power as a fraction of ST power

μ =

moisture fraction (by volume)

o =

gasifier oxygen to feedstock mass flow ratio

π =

pressure ratio

θ =

heat duty as a fraction of gasifier feedstock input (LHV)

ρ =

raw-to-clean syngas HHV energy content ratio

ϖ =

gasifier feedstock higher to lower heating value ratio

ϖ′ =

clean syngas higher to lower heating value ratio

σSG =

clean-to-raw syngas mass flow ratio

ξ =

air extraction as a fraction of compressor airflow

Subscripts
AE =

air extraction

AUX =

auxiliary

BC =

bottoming cycle

Cap =

carbon capture

CC =

combined cycle

CG =

cold gas

exh =

GT exhaust

f =

saturated water

feed =

gasifier feedstock (coal, petcoke, etc.)

fw =

feed water

GC =

gas cooling

GCP =

gas cleanup plant

GSF =

gasifier

GT =

gas turbine

imp =

import (steam from process to power block)

RBC =

Rankine bottoming cycle

SAT =

saturator (i.e., “moisturizer”)

sat =

saturated (steam/water)

SG =

syngas

SGX =

syngas expander

stck =

heat recovery steam generator stack

stm =

steam

## References

1.
Minchener
,
A. J.
,
2005
, “
Coal Gasification for Advanced Power Generation
,”
Fuel
,
84
, pp.
2222
2235
.10.1016/j.fuel.2005.08.035
2.
Holt
,
N. A. H.
,
2003
, “
Operating Experience and Improvement Opportunities for Coal Based IGCC Plants
,”
Mater. High Temp.
,
20
(
1
), pp.
1
6
.10.3184/096034003782749198
3.
Zheng
,
L.
, and
Furinsky
,
E.
,
2005
, “
Comparison of Shell, Texaco, BGL and KRW Gasifiers as Part of IGCC Plant Computer Simulations
,”
Energ. Convers. Manage.
,
46
, pp.
1767
1779
.10.1016/j.enconman.2004.09.004
4.
U.S. Department of Energy, National Energy Technology Laboratory
,
2010
, “
Cost and Performance Baseline for Fossil Energy Plants Volume 1: Bituminous Coal and Natural Gas to Electricity
,” Revision 2, DOE/NETL-2010/1397.
5.
Aspen HYSYS Version 7.3,
Aspen Technology, Inc.
,
Burlington, MA
, website: www.aspentech.com
6.
PRO/II Version 8.3,
Invensys Inc.
,
Plano, TX
, website: iom.invensys.com
7.
GateCycle Version 5.6,
General Electric
, Atlanta, GA, website: http://site.ge-energy.com/prod_serv/products/oc/en/opt_diagsw/gatecycle.htm
8.
GT PRO Version 20.0,
Thermoflow, Inc.
,
Sudbury, MA 01776
, website: www.thermoflow.com
9.
Perez-Fortes
,
M.
,
Bojarski
,
A. D.
,
Velo
,
E.
,
Nougues
,
J. M.
, and
Puigjaner
,
L.
,
2009
, “
Conceptual Model and Evaluation of General Power and Emissions in an IGCC Plant
,”
Energy
,
34
, pp.
1721
1732
.10.1016/j.energy.2009.05.012
10.
Dennis
,
R. A.
,
Shelton
,
W. W.
, and
Le
,
P.
,
2007
, “
Development of Baseline Performance Values for Turbines in Existing IGCC Applications
,”
ASME Turbo Expo 2007
,
Montreal
,
, May 14–17,
ASME
Paper No. GT2007-28096, pp.
1017
1049
.10.1115/GT2007-28096
11.
Chiesa
,
P.
, and
Lozza
,
G.
,
1999
, “
CO2 Emission Abatement in IGCC Power Plants by Semiclosed Cycles: Part A—With Oxygen-Blown Combustion
,”
ASME J. Eng. Gas. Turb. Power
,
121
, pp.
635
641
.10.1115/1.2818519
12.
Field
,
R. P.
, and
Brasington
,
R.
,
2011
, “
Baseline Flowsheet Model for IGCC With Carbon Capture
,”
Ind. Eng. Chem. Res.
,
50
(
19
), pp
11306
11312
.10.1021/ie200288u
13.
Pruschek
,
R.
,
1998
, “
Enhancement of Efficiency of Integrated Gasification Combined Cycle (IGCC) Power Plants
,” ftp://ftp.euro-cleancoal.net/pub/pdf/j2phase2/chap5.pdf
14.
Rubin
,
E. S.
,
Berkenpass
,
M. B.
,
Frey
,
H. C.
,
Chen
,
C.
,
McCoy
,
S. T.
, and
Zaremsky
,
C. J.
,
2007
, “
Technical Documentation: IGCC Systems With Carbon Capture and Storage
,” Final Report, U.S. DOE Contract DE-AC21-92MC29094.
15.
Zhu
,
Y.
, and
Frey
,
H. C.
,
2007
, “
Simplified Performance Model of Gas Turbine Combined Cycle Systems
,”
J. Energ. Eng.
,
133
, pp.
82
90
.10.1061/(ASCE)0733-9402(2007)133:2(82)
16.
Oracle Crystal Ball,
Oracle Corporation, Redwood Shores
,
CA
, website: www.oracle.com
17.
Electric Power Research Institute (EPRI)
,
1977
, “
Comparative Evaluation of High and Low Temperature Gas Cleaning for Coal Gasification–Combined Cycle Power Systems
,”
EPRI
,
Palo Alto, CA
, EPRI Report AF-416.
18.
Probstein
,
R. F.
, and
Hicks
,
R. E.
,
2006
,
Synthetic Fuels
,
Dover Publications, Inc.
,
Mineola, NY
.
19.
Rezaiyan
,
J.
, and
Cheremisinoff
,
N. P.
,
2005
,
Gasification Technologies: A Primer for Engineers and Scientists
,
CRC Press, T&F Group
,
Boca Raton, FL
.
20.
Gülen
,
S. C.
,
2010
, “
Importance of Auxiliary Power Consumption for Combined Cycle Performance
,”
J. Eng. Gas Turb. Power
,
133
, p.
041801
.10.1115/1.4002254
21.
,
O.
,
Herzog
,
H.
,
Bolland
,
O.
, and
Beer
,
J.
,
2009
, “
Impact of Coal Quality and Gasifier Technology on IGCC Performance
,”
Norwegian University of Science and Technology (NTNU), Trondheim, Norway and Massachusetts Institute of Technology
,
Cambridge, MA
.
22.
Gülen
,
S. C.
,
2011
, “
A Simple Parametric Model for the Analysis of Cooled Gas Turbines
,”
ASME J. Eng. Gas Turb. Power
,
133
, p.
011801
.10.1115/1.4001829
23.
Stull
,
D. R.
, and
Prophet
,
H.
,
1971
,
JANAF Thermodynamic Tables
, 2nd ed.,
National Standard Reference Data Series–National Bureau of Standards (NSRDS-NBS) 37, National Bureau of Standards
, Gaithersburg, MD.
24.
Gülen
,
S. C.
, and
Smith
,
R. W.
,
2010
, “
Second Law Efficiency of the Rankine Bottoming Cycle of a Combined Cycle Power Plant
,”
ASME J. Eng. Gas Turb. Power
,
132
, p.
011801
.10.1115/1.3124787
25.
ASME
,
2009
,
ASME International Steam Tables for Industrial Use
, 2nd ed., ASME Books, New York.
26.
Gülen
,
S. C.
,
2010
, “
A Proposed Definition of CHP Efficiency
,” Power,
154
(
6
), pp.
58
63
, available at: http://www.powermag.com/issues/features/A-Proposed-Definition-of-CHP-Efficiency_2721.html
27.
Parulekar
,
P. S.
,
2011
, “
Comparison Between Oxygen-Blown and Air-Blown IGCC Power Plants: A Gas Turbine Perspective
,”
ASME Turbo Expo 2011
,
Vancouver
,
, June 6–10,
ASME
Paper No. GT2011-45154, pp.
537
545
.10.1115/GT2011-45154
28.
Jones
,
R. M.
, and
Shilling
,
N. Z.
,
2003
, “
IGCC Gas Turbines for Refinery Applications
,” GE Energy, Schenectady, NY, Paper No. GER-4219.
29.
Holt
,
N.
,
Booras
,
G.
, and
Todd
,
D.
,
2003
, “
A Summary of Recent IGCC Studies of CO2 Capture for Sequestration
,”
Gasification Technologies Conference
,
San Francisco
,
CA
, October 12–15.
30.
Frey
,
H. C.
, and
Zhu
,
Y.
,
2006
, “
Improved System Integration for Integrated Gasification Combined Cycle (IGCC) Systems
,”
Environ. Sci. Technol.
,
40
(
5
), pp.
1693
1699
.10.1021/es0515598
31.
Hoffmann
,
S.
,
Bartlett
,
M.
,
Finkenrath
,
M.
,
Evulet
,
A.
, and
Ursin
,
T.
,
2009
, “
Performance and Cost Analysis of Advanced Gas Turbine Cycles With Precombustion CO2 Capture
,”
J. Eng. Gas Turb. Power
,
131
, p.
021701
.10.1115/1.2982147
32.
Botero
,
C.
,
Finkenrath
,
M.
,
Belloni
,
C.
,
Bertolo
,
S.
,
D'Ercole
,
M.
,
Gori
,
E.
, and
Tacconelli
,
R.
,
2009
, “
Thermoeconomic Evaluation of CO2 Compression Strategies for CO2 Capture Applications
,”
ASME Turbo Expo 2009
,
Orlando
,
FL
, June 8–12,
ASME
Paper No. GT2009-60217, pp.
517
526
.10.1115/GT2009-60217
33.
Electric Power Research Institute (EPRI)
,
1980
, “
Gasification Combined Cycle Plant Configuration Studies
,”
EPRI
,
Palo Alto, CA
, EPRI Report AP-1393.
34.
Smith
,
R. W.
,
Johansen
,
A. D.
, and
Ranasinghe
,
J.
,
2005
, “
Fuel Moisturization for Natural Gas Fired Combined Cycles
,”
ASME Turbo Expo 2005
,
Reno-Tahoe
, NV, June 6–9,
ASME
Paper No. GT2005-69012, pp.
529
535
.10.1115/GT2005-69012
35.
McDaniel
,
J.
,
2002
, “
Tampa Electric Polk Power Station Integrated Gasification Combined Cycle Project: Final Technical Report
,” U.S. Department of Energy, National Energy Technology Laboratory (DOE/NETL), Morgantown, WV.
36.
U.S. Department of Energy and Wabash River Coal Gasification Project Joint Venture
,
2000
, “
The Wabash River Coal Gasification Repowering Project: An Update
,” Topical Report Number 20.
37.
Wabash River Coal Gasification Repowering Project Joint Venture
,
2002
, “
Wabash River Coal Gasification Repowering Project: Project Performance Summary
,” U.S. Department of Energy, Office of Fossil Energy, Paper No. DOE/FE-0448.
38.
U.S. Department of Energy, National Energy Technology Laboratory
,
2002
, “
Wabash River Coal Gasification Repowering Project: A DOE Assessment
,” Paper No. DOE/NETL-2002/1164.
39.
Elcogas
,
2000
, “
IGCC Puertollano: A Clean Coal Gasification Power Plant
,” Elcogas, Puertollano, Spain, website: http://212.170.221.11/elcogas_body/images/IMAGEN/TECNOLOGIAGICC/thermie.pdf
40.
Shelton
,
W.
, and
Lyons
,
J.
,
2000
, “
KRW Gasifier IGCC Base Cases
,” U.S. Department of Energy, National Energy Technology Laboratory (DOE/NETL), Morgantown, WV, Paper No. PED-IGCC-98-005.
41.
Bartone
,
L.
, and
White
,
J.
,
2007
, “
Industrial Size Gasification for Syngas, Substitute Natural Gas and Power Production
,” U.S. Department of Energy, National Energy Technology Laboratory, Morgantown, WV, Paper No. DOE/NETL-401/040607.
42.
Bechtel Corp., Global Energy Inc., and Nexant Inc.
,
2002
, “
Gasification Plant Cost and Performance Optimization: Task 1 Topical Report IGCC Plant Cost Optimization
,” Volume 1, U.S. Department of Energy, National Energy Technology Laboratory (DOE/NETL), Morgantown, WV.
43.
Hoffmann
,
J.
,
Matuszewski
,
M.,
,
Rutkowski
,
M.
,
Schoff
,
R.
,
Stiegel
,
G.
, and
Tennant
,
J.
,
2006
, “
Comparison of Pratt and Whitney Rocketdyne IGCC and Commercial IGCC Performance
,” U.S. Department of Energy, National Energy Technology Laboratory, Morgantown, WV, Paper No. DOE/NETL-401/062006.
44.
Ishibashi
,
Y.
,
2009
, “
Second Year Operation Results of CCP's Nakoso 250 MW Air-Blown IGCC Demonstration Plant
,”
Gasification Technologies Conference
2009, website: http://www.ccpower.co.jp/research/pdf/doc/2009gtc_ccp_rev9-1.pdf
45.
Jaeger
,
H.
,
2006
, “
Japan 250 MW Coal Based IGCC Demo Plant Set for 2007 Start-Up
,” Gas Turbine World, May-June.