Combined production of synthetic liquid fuel and electricity from coal using H2S and CO₂ removal systems

Tyurina, Elina A.; Skripchenko, Olga V. Article Combined production of synthetic liquid fuel and electricity from coal using H2S and CO₂ removal systems Energy Reports Provided in Cooperation with: Elsevier Suggested Citation: Tyurina, Elina A.; Skripchenko, Olga V. (2015) : Combined production of synthetic liquid fuel and electricity from coal using H2S and CO₂ removal systems, Energy Reports, ISSN 2352-4847, Elsevier, Amsterdam, Vol. 1, pp. 50-56, https://doi.org/10.1016/j.egyr.2014.11.005 This Version is available at: https://hdl.handle.net/10419/187811 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. 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If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. https://creativecommons.org/licenses/by-nc-nd/4.0/ Energy Reports 1 (2015) 50–56 Contents lists available at ScienceDirect Energy Reports journal homepage: www.elsevier.com/locate/egyr Combined production of synthetic liquid fuel and electricity from coal using H2S and CO2removal systems Elina A. Tyurina, Olga V. Skripchenko∗ Energy Systems Institute SB RAS, Irkutsk, Russia article info Article history: Received 3 September 2014 Received in revised form 26 November 2014 Accepted 30 November 2014 Available online 23 January 2015 Keywords: Combined production Synthetic liquid fuel Electricity Coal Methanol Rectisol method abstract The main aim of the research is to continue the studies on promising technologies of coal conversion into synthetic liquid fuel (methanol). The object of study is the plants for combined production of electricity and synthetic liquid fuel (PCPs), which are eco-friendly and more efficient as compared to the plants for separate production. The previous studies on PCPs consider the systems for fine cleaning of gasification products in a simplified way. This study presents the detailed mathematical modeling of the aforementioned systems and determines the values of energy consumption and investment in them. The obtained values are used to carry out the optimization studies and find the optimal parameters of PCPs with different degree of CO2removal from gasification products providing fine cleaning of gasification products from H2S. ©2014 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). 0. Introduction Implementation of coal projects in the electric power industry is hampered by low energy efficiency and a negative environmental impact of run-of-mine coal combustion, and high costs of delivering energy produced from coal (especially low-calorific coal) to end consumers. Therefore, there is a great interest in the problem of converting coal into synthetic liquid fuel (SLF) as an alternative energy fuel. One of the most promising directions in coal conversion is coal gasification with subsequent SLF synthesis at plants for combined production of electricity and synthetic liquid fuel (PCPs). An interest in this technology is explained by the fact that SLF synthesis is highly efficient, quite eco-friendly, and allows production of an environmentally friendly fuel. Great attention world-wide and in Russia is paid to the integrated processing of solid fuels into synthetic high-grade fuels with CO2removal (Gao et al.,2009;Guangjian et al.,2010;Hetland and Anantharaman, 2009;Larson et al., 2010;Manzolini et al.,2013;Pellegrini et al.,2011;Robinson and Tatterson, 2008;Sajo et al.,2011;Sun et al.,2010;Winkler,2007). Researchers from Energy Systems Institute SB RAS (Russia, Irkutsk) have been engaged in mathematical modeling of PCPs synthesizing various types of SLF (methanol, dimethyl ether, etc.) and ∗Corresponding author. E-mail addresses: [email protected] (E.A. Tyurina), [email protected] (O.V. Skripchenko). feasibility studies on them for a long time. The mathematical models of individual PCP modules and PCPs as a whole are developed. Optimal scheme and parameter solutions as well as conditions for PCP competitiveness are found (Kler et al.,2005;Kler and Tyurina, 2007;Tyurina et al.,2012). Comprehensive studies on the processing of organic fuel at PCPs were carried out by such companies as Sasol, Shell, Mobil, Bechtel, Methanex. Nevertheless, the detailed analysis of the conducted studies in the aforementioned directions allows us to find out some unsettled issues. It should be mentioned, that in the previous studies on PCPs the systems for cleaning syngas from the compounds of sulfur and carbon dioxide were considered in a simplified way using expert data on specific energy consumption and investment. At the same time the catalytic SLF synthesis requires, among other things, the absence of sulfur compounds, because they facilitate ‘‘poisoning’’ of the catalysts and slow down the formation of SLF. It is also necessary to remove excessive carbon dioxide from the gasification products. Since these systems are quite expensive and energy consuming, their simplified representation does not allow us to determine technical and economic indices of the PCP as a whole with the required accuracy. Therefore, this calls for the mathematical modeling and feasibility studies on the PCP system for cleaning the gasification products. The specific process analyzed as an example of synthetic liquid fuel production is the synthesis of methanol. The studies have two stages. At the first stage we construct a mathematical model of the system for cleaning gasification products by the Rectisol method and conduct optimization feasibility http://dx.doi.org/10.1016/j.egyr.2014.11.005 2352-4847/©2014 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4. 0/). E.A. Tyurina, O.V. Skripchenko / Energy Reports 1 (2015) 50–56 51 Fig. 1. Calculated scheme of a two-stage system for H2S and CO2removal from gasification products based on the Rectisol method: W1—gas-water heat exchanger; T1–T4— heat exchangers; AS—sulfur absorber; AY1, AY2—CO2absorber of stages 1 and 2; NH1, NH2—vaporizers; DY—CO2desorber; DS—sulfur desorber; K1–K3—compressors; N1–N4—pumps. Notation of the flows: g—heating flow; n—heated flow; y—components removed from syngas. studies for this model. At the second stage the developed model is included in the mathematical model of the PCP as a whole in order to make further optimization feasibility studies. The main aim of these studies is to obtain optimal parameters of PCPs with different degree of carbon dioxide removal from gasification products. This is conditioned by the fact that some part of carbon dioxide participates in the reactions of methanol synthesis, which can increase methanol production or the release of additional carbon monoxide in the blast of syngas that enters the combustion chamber of the gas turbine for liquefaction. The second circumstance can affect the generation of additional electricity. 1. Mathematical modeling of the system for cleaning gasification products by the Rectisol method The developed mathematical model of the cleaning system rests on one of the efficient processes of cleaning gasification products from sulfur compounds and excessive carbon dioxide which is called the Rectisol process (the gas cleaning method with methanol at low temperatures). An interest in this method is explained, firstly, by the fact that during the field tests it proved to be effective in cleaning of syngas obtained by coal gasification, secondly, by the fact that PCPs have low temperature flows, which can be effectively used in the cleaning system, and thirdly, this technique ensures comprehensive removal of CO2, H2S, organic sulfur compounds and other impurities from gases with one and the same solvent. Different cleaning schemes are used depending on gasification method and composition of original gas. In this paper we consider two-stage removal of H2S and CO2from gasification products with cold methanol. Its design scheme (Kler et al.,2010,2011), for which we have developed a mathematical model, is presented in Fig. 1. When constructing a mathematical model for the system of H2S and CO2removal from gasification products, we used previously developed models of the system components: heat exchangers, vaporizers, compressors, mixers, etc., and developed new components: absorber and desorber of H2S and CO2. Mathematical model of the absorber includes relationships between input and output parameters of the component (equilibrium compositions and flow rates of absorbent (methanol) and solute gas (gasification products); pressures and temperatures of flows), and the relationships between these variables and design characteristics of the device. In the mathematical model of the absorber initial data are represented by the flow rate and composition of the solvent and solute gas, input pressure, temperature and enthalpy. Below we present a system of equations, which describe the mathematical model. •Material balance of the process ΣG(i)=Gin L(i)+Gin g(i), where ΣG(i)—total flow rate of the component distributed from gaseous phase to solution in the whole device; Gin L(i)—flow rate of the absorbent (methanol), which contains distributed components, at the inlet to the section; Gin g(i)—flow rate of the gas component at the inlet to the section. •Heat balance of the process Gav g·cg·(tin g−tout g)−Gav L·cL·(tout L−tin L)+Qdif =0, where Qdif—differential heat of gas dissolution; Gav g,Gav L—average flow rates of phases in absorber section; cL—relative thermal capacity of absorbent; cg—relative thermal capacity of solute gas; tout L,tout g—temperature of absorbent and solute gas in the given section; tin L,tin g—initial temperature of absorbent and solute gas. •When determining the equilibrium composition of solutions in the absorber, we use Henry’s law for ideal solutions (since during the process there is no chemical interaction between gas and absorbent, and moderate pressures and low temperatures are used) Xi=ki·Pi, where Xi—mole fraction of extracted component in the solution; ki—the Henry’s law constant of the component; Pi—partial pressure of the gas component. 52 E.A. Tyurina, O.V. Skripchenko / Energy Reports 1 (2015) 50–56 •Mass transfer surface F=ΣG(i)/Kg·∆¯ Yav, where ΣG(i)—total flow rate of the component distributed from gaseous phase to solution in the whole device; Kg—mass transfer coefficient; ∆¯ Yav—motive force in concentration units of gaseous phase. •Mass transfer coefficient Kg=1/1/βg+m/βL, where βLand βg—mass transfer coefficients in liquid and gaseous phases, respectively, kg/(m2·c); m—distribution coefficient, kg of methanol/kg of gas. •Height of the absorber is determined by geometric relation H=F/0,785 ·a·d2 st ·ψa, where F—mass transfer surface; a—specific surface area of packed bed; dst—standard diameter of the absorber; ψa—share of the active packed bed surface. The system of equations is solved by the Newton iteration method with regard to the constraint on heat balance. By solving this system we determine the design characteristics of the absorber. Mathematical model of the desorber includes the relationships that are necessary to determine equilibrium composition of twophase mixtures, heat and material balances. The non-negativity constraints on temperature differences are taken into account. Design characteristics are determined (mass transfer surface, height of the desorber stage, etc.). Thus, the mathematical model of the system for cleaning gasification products by the Rectisol method is aimed at the engineering design of PCP components: determination of heating surfaces of heat exchangers, mass transfer surfaces of absorbers and desorbers, driving power of pumps and compressors, thermodynamic parameters, flow rates, etc. Based on the developed mathematical model of the system for cleaning gasification products by the Rectisol method, we conducted the optimization studies aimed at determining energy consumption and capital costs, depending on the degree of CO2 removal providing fine cleaning of gasification products from sulfur compounds. To this end, we solved the problems of non-linear mathematical programming that imply calculation of the parameters (mass transfer surfaces of absorbers and desorbers, etc.), which provide minimum capital investment in the cleaning system at a given price of ceramic acid resistant packing (Raschig rings) and take account of physical and technical constraints on the parameters of the cleaning system and energy consumed for H2S and CO2 removal. Mathematical statement of the problem is as follows min ∆KCY (x,y,KTO,KAS ,KDS ,KKR,∆NCY ) subject to H(x,y)=0; G(x,y)≥0; xmin ≤x≤xmax, where x—vector of independent optimized parameters; y—vector of dependent (calculated) parameters; H—vector of equality constraints (equations of material and energy balances, heat transfer, etc.); G—vector of inequality constraints; xmin,xmax—vectors of boundary values of optimized parameters; ∆KCY —investment in the system of H2S and CO2removal; KTO—investment in heat exchangers; KAS —investment in absorbers; KDS —investment in desorbers; KKR—investment in compressors; ∆NCY —energy consumption in the cleaning system. In total we optimize 20 parameters (methanol flow rate in the cleaning system, changes in the enthalpy of cold flows in vaporizers, nitrogen consumption at the desorber inlet, etc.). The system of constraints includes conditions for non-negativity of end temperature differences in heat exchangers, constraints on design temperatures and mechanical stress of heat exchanger tubes, mass transfer surface of absorbers and desorbers, etc. (135 constraints, altogether). Table 1 presents optimal parameters of the main components of the system for cleaning gasification products by the Rectisol method, depending on the degree of CO2removal. The results of the optimization studies on the cleaning system allow us to construct approximation relationships (Fig. 2) and determine investment and energy consumption for the cleaning system, depending on the degree of CO2removal. The studies on the system for cleaning gasification products by the Rectisol method showed that the lower the degree of CO2 removal the less the number of absorption stages. This can be explained by a decrease in the flow rate of absorbent required to absorb CO2from gasification products (the variant, in which CO2 removal is 40%, has one absorption stage). For the sake of comparison, the table presents the variant with CO2removal equal to 65% (shown in gray), which shows the degeneration of the second absorption stage. The obtained approximation relationships (Fig. 2) testify to an increase in energy consumption and investment in the cleaning system which is caused by the expansion of mass transfer surfaces of absorbers and desorbers after an increase in the share of CO2 removal. The developed mathematical model of the system for removal of H2S and excessive CO2from gasification products by the Rectisol method is included in the mathematical model of PCP as a whole (Fig. 3) in order to carry out further studies. 2. Optimization studies on the plant for combined production of electricity and synthetic liquid fuel (methanol synthesis) with regard for H2S and CO2removal The mathematical model of PCP is generally intended for engineering design of the plant components and contains about 2000 variables and several hundreds of algebraic and transcendental equations. The system of equations is solved by the Seidel method. The purpose of optimization studies based on the mathematical model of PCP with a system for cleaning gasification products from H2S and CO2is to obtain optimal thermodynamic and flowrate parameters of PCPs and their technical and economic indices, depending on the degree of CO2removal from gasification products in the cleaning system. The optimization was performed based on the criterion of minimum prices of the produced SLF with the given levels of internal rate of return and prices of consumed fuel and supplied electricity and with regard for physical and technical constraints on the plant parameters and for costs of the H2S and CO2removal system. The optimized parameters are enthalpy, pressure and flow rate of live steam, catalyst volume in PCP, etc. The system of constraints contains non-negativity constraints of the end temperature heads of heat exchangers and differential pressures along the once-through part of steam and gas turbines, constraints on design E.A. Tyurina, O.V. Skripchenko / Energy Reports 1 (2015) 50–56 53 Table 1 Optimal parameters of the system for cleaning gasification products by the Rectisol method, depending on the degree of CO2removal (notation of components corresponds to the notation in Fig. 1). Component Index Degree of CO2removal(%) 95 80 65 40 1 2 3 4 5 6 T1 Temperature of the cooled flow, K Inlet 298.1 298.1 298.1 298.1 Outlet 266.3 287.2 285.7 277.7 Temperature of the cooling flow, K Inlet 242.2 225.1 232.3 236.1 Outlet 285.1 240.2 250.7 265.1 Pressure of the cooling flow, kg/cm230.0 30.0 30.0 30.0 Pressure of the cooled flow, kg/cm230.0 30.0 30.0 30.0 Total area of heat exchangers, m236280.2 5798.2 8794.5 2342.0 T2 Temperature of the cooled flow, K Inlet 298.1 298.1 297.8 – Outlet 264.7 287.3 285.9 – Temperature of the cooling flow, K Inlet 247.2 257.4 266.6 – Outlet 285.5 269.1 278.8 – Pressure of the cooling flow, kg/cm250.0 50.0 50.0 – Pressure of the cooled flow, kg/cm250.0 50.0 50.0 – Total area of heat exchangers, m216994.9 2769.6 5959.7 – T3 Temperature of the cooled flow, K Inlet 254.8 275.6 285.2 250.7 Outlet 231.2 232.7 241.8 237.7 Temperature of the cooling flow, K Inlet 227.4 228.8 229.2 237.8 Outlet 246.8 239.9 241.7 224.1 Pressure of the cooling flow, kg/cm229.8 29.8 29.8 30.0 Pressure of the cooled flow, kg/cm230.0 30.0 30.0 20.0 Total area of heat exchangers, m234776.2 5972.8 5620.0 2073.4 T4 Temperature of the cooled flow, K Inlet 261.1 264.5 266.9 – Outlet 237.6 220.4 227.2 – Temperature of the cooling flow, K Inlet 219.0 192.1 220.2 – Outlet 242.0 234.9 259.9 – Pressure of the cooling flow, kg/cm250.0 50.0 50.0 – Pressure of the cooled flow, kg/cm230.0 30.0 30.0 – Total area of heat exchangers, m239151.5 5483.1 24857.9 – NH1 Temperature of the cooled flow, K inlet 231.9 233.7 242.5 238.1 Outlet 219.0 192.1 220.2 231.5 Temperature of the cooling flow, K Inlet 107.0 82.5 88.5 83.9 Outlet 184.0 139.9 193.7 109.2 Pressure of the cooling flow, kg/cm22.0 1.7 1.7 2.0 Pressure of the cooled flow, kg/cm250.0 50.0 50.0 30.0 Total area of heat exchangers, m24970.1 2620.5 2851.3 205.9 NH2 Temperature of the cooled flow, K Inlet 254.1 263.1 270.4 – Outlet 252.9 258.9 257.2 – Temperature of the cooling flow, K Inlet 99.7 118.1 86.2 – Outlet 185.4 172.8 156.7 – Pressure of the cooling flow, kg/cm22.0 2.1 2.1 – Pressure of the cooled flow, kg/cm250.0 50.0 49.6 – Total area of heat exchangers, m2955.8 509.7 1019.8 – AS Absorbent temperature, K Inlet 237.6 220.3 227.1 231.3 Outlet 242.3 237.6 242.7 245.0 Gas temperature, K Inlet 266.3 240.0 245.1 247.4 Outlet 242.3 225.3 232.1 236.3 Absorber mass transfer surface, m321190.7 13417.5 14541.7 9600.5 (continued on next page) 54 E.A. Tyurina, O.V. Skripchenko / Energy Reports 1 (2015) 50–56 Table 1 (continued) Component Index Degree of CO2removal(%) 95 80 65 40 1 2 3 4 5 6 AY1 Absorbent temperature, K Inlet 242.5 – – – Outlet 248.1 – – – Gas temperature, K Inlet 257.9 – – – Outlet 247.0 – – – Absorber mass transfer surface, m38810.7 – – – AY2 Absorbent temperature, K Inlet 247.1 252.1 261.6 – Outlet 254.2 263.2 270.5 – Gas temperature, K Inlet 264.6 265.6 272.9 – Outlet 257.9 257.1 266.7 – Absorber mass transfer surface, m37508.6 5009.7 916.7 – DS Absorbent temperature, K Inlet 212.5 218.3 222.3 225.6 Outlet 226.3 227.0 228.7 236.6 Gas temperature, K Inlet 315.4 346.3 336.5 266.8 Outlet 257.3 291.8 291.7 248.6 Desorber mass transfer surface, m313301.6 7760.3 6120.1 4961.0 DY Absorbent temperature, K Inlet 250.7 253.3 256.2 – Outlet 261.3 263.3 266.2 – Gas temperature, K Inlet 347.8 368.4 311.6 – Outlet 255.7 258.3 261.2 – Desorber mass transfer surface, m328430.4 6689.4 4858.9 – K1 Flow pressure, kg/cm2Inlet 29.9 29.9 29.9 – Outlet 50.0 50.0 50.0 – Flow temperature, K Inlet 285.2 240.8 250.8 – Outlet 311.4 311.0 310.7 – Consumed power, MW 11274.6 10295.8 10412.1 – Total area of built-in gas–water heat exchangers, m2 839.6 1047.3 1039.6 – K2 Flow pressure, kg/cm2Inlet 1.2 1.2 1.1 – Outlet 30.0 30.0 30.0 – Flow temperature, K Inlet 242.0 222.7 223.5 – Outlet 392.4 379.2 380.2 – Consumed power, MW 2814.8 3859.5 3858.1 – Total area of built-in gas–water heat exchangers, m2 222.0 282.6 281.5 – K3 Flow pressure, kg/cm2Inlet 20.0 20.0 20.0 20.0 Outlet 30.0 30.0 30.0 30.0 Flow temperature, K Inlet 290.0 290.0 290.0 290.0 Outlet 308.6 308.5 308.5 308.5 Consumed power, MW 9712.6 9712.6 9712.6 9712.6 Total area of built-in gas–water heat exchangers, m2 934.9 934.9 934.9 934.9 Total investment, mln. dollars 136.9 108.8 128.3 65.1 Total electricity consumption, MW 27.406 24.913 25.053 10.237 temperatures and mechanical stresses of the heat exchanger pipes, constraints on minimum and maximum gasification temperatures, etc. Initial technical and economic information was chosen on the basis of the studies previously conducted at Energy Systems Institute SB RAS (Russia, Irkutsk), which were devoted to the investigation into the technologies of converting solid fuel into synthetic liquid and gaseous fuels and on the basis of the analysis of estimates of expenditures made for process and power plants (Kler et al.,2005;Kler and Tyurina, 2007;Tyurina et al.,2012). Fuel is gasified in gas generators with a fluidized bed and a dry slag removal system on the basis of steam-oxygen blast under a pressure of 2 MPa. Such a gas generator is analogous to the gas generator Winkler, which was quite thoroughly studied and commercially introduced. These gas generators are most often used in PCPs. The internal rate of return equals 15%, which corresponds to the world practice of studying large-scale projects. E.A. Tyurina, O.V. Skripchenko / Energy Reports 1 (2015) 50–56 55 150 140 130 120 110 100 90 80 70 60 40 50 60 80 85 95 30 25 20 15 10 5 0 Total investment, mln.dollars Degree of CO2 removal, % Total electric power consumed, MW Fig. 2. Relationship between the total investment and total electricity consumption in the cleaning system and the degree of CO2removal. Fig. 3. Simplified process flow sheet of PCP of methanol and electricity on coal: 1—fuel preparation system; 2—air separation system; 3—gas generator; 4—module for cooling gasification products; 5—module for cleaning gasification products by the Rectisol method; 6—syngas compressor; 7—regenerative gas–gas heat exchanger; 8— catalytic reactors of methanol synthesis; 9—methanol condenser; 10—methanol separator; 11—expansion gas turbine; 12—gas turbine combustion chamber; 13—primary gas turbine; 14—air compressor; 15—waste heat boiler; 16—steam turbine; 17—steam turbine condenser. Notation of flows: g—gas, b—air, w—feed water, y—coal, k—oxygen, p—low pressure steam, t—high pressure steam. I—module of syngas production, II—module of methanol synthesis, III—module of electricity production. The mathematical statement of the problem is as follows min CSLF(x,y,km,∆KCY ,∆NCY ) subject to H(x,y)=0; G(x,y)≥0; xmin ≤x≤xmax; IRR =IRRz, where x—vector of independent optimized parameters; y—vector of dependent (calculated) parameters; H—vector of equality constraints (equations of material and energy balances, heat transfer, etc.); G—vector of inequality constraints; xmin,xmax—vectors of boundary values of optimized parameters; CSLF—methanol cost; km—CO2removal coefficient; ∆KCY —investment in H2S and CO2removal system; ∆NCY —energy consumption in the removal system; IRR,IRRz—design and given internal rates of return. Table 2 presents optimal technical and economic indices of PCPs from coal with different degree of CO2removal. Fig. 4 shows optimal PCP indices versus the degree of CO2 removal from gasification products. Studying PCPs with a system for cleaning gasification products as a whole, we determined the optimal share of CO2removal (Fig. 4). This share corresponds to the variant with 50% removal and is characterized by the lowest price of produced methanol. Both an increase and a decrease in the share of CO2removal are typified by a higher price of methanol. 56 E.A. Tyurina, O.V. Skripchenko / Energy Reports 1 (2015) 50–56 Table 2 Optimal technical and economic indices of PCPs with different degree of CO2removal. Index Variants of PCPs with different degree of CO2removal(%) 25 50 90 Annual consumption of fuel (coal) Equivalent, thous. tce 2480 Natural, thous. t 4580 Coal price, dollars/tce 20 Annual production of methanol Equivalent, thous. tce 1323.5 1317.5 1255.2 Natural, thous. t 1852.9 1844.5 1757.3 Annual electricity supply, mln. kW h 1549.1 1508 1802 Power, MW Gas turbine 317.1 338.4 402.4 Steam turbine 243.01 229.5 246.9 Auxiliary 338.8 352.5 391.9 Effective 221.3 215.4 257.4 Investment in the system for cleaning gasification products, mln. dollars 53.8 76.1 126.1 Total investment in the plant, mln. dollars 1108 963.6 947.2 Thermal efficiency of methanol production, %. 64.6 64 63.5 Price of electricity supplied, cent/kW h 4 Price of methanol production, dollars/tce 257 225 241 Fig. 4. Dependence of annual methanol production, annual electricity supply, and price of methanol production on the degree of CO2removal. 3. Conclusion The studies on the system for cleaning gasification products by the Rectisol method showed that the lower the degree of CO2 removal the less the number of absorption stages, which can be explained by a decrease in the flow rate of the absorbent required to absorb CO2from gasification products. As a result of the conducted studies, the developed mathematical models of this system were used to construct the approximation relationships and determine the energy consumption and capital costs, depending on the degree of CO2removal providing fine cleaning of gasification products from sulfur compounds. The optimization feasibility studies on the PCP carried out on the basis of the obtained relationships in terms of energy consumption and capital costs for the cleaning system, depending on the degree of CO2removal, showed that the optimal variant characterized by the highest efficiency is the variant with 50% removal. The obtained results and the developed mathematical models of the system for fine cleaning of gasification products from carbon dioxide and sulfur compounds by the Rectisol method can be used in the studies on both PCPs and coal-fired combined heat and power plants in terms of energy consumption and investment in the system or at pre-design and design stages of their development. References Gao, Z., Huang, W., Yin, L., Xie, K., 2009. Liquid-phase preparation of catalysts used in slurry reactors to synthesize dimethyl ether from syngas: Effect of heattreatment atmosphere. Fuel Process. Technol. 90, 1442–1446. Guang-jian, L., Zheng, L., Ming-hua, W., Wei-dou, N., 2010. Energy savings by coproduction: A methanol/electricity case study. Appl. Energy 87, 2854–2859. Hetland, J., Anantharaman, R., 2009. Carbon capture and storage (CCS) options for co-production of electricity and synthetic fuels from indigenous coal in an Indian context. Energy Sustain. Dev. 13, 56–63. Kler, A., Dekanova, N., Tyurina, E., et al., 2005. Thermal Power Systems: Optimization Studies. Nauka, Novosibirsk. Kler, A., Tyurina, E., 2007. Production of coal derivatives in the course of advanced coal processing: modeling of technologies, comparative effectiveness. Combust. Plasma Chem. 4 (4), 276–281. Kler, A., Tyurina, E., Mednikov, A., 2011. Energy-technology installations for combined production of hydrogen and electricity with CO2removal systems. Int. J. Hydrog. Energy 36, 1230–1235. Kler, A., Tyurina, E., Mednikov, A., Stepanov, V., 2010. The combined technology for production of synthetic fuels and electricity with reduced CO2emissions. Int. J. Low-Carbon Technol. 5, 264–272. Larson, E., Fiorese, G., Liu, G., et al., 2010. Co-production of decarbonized synfuels and electricity from coal +biomass. Energy Environ. Sci. 3, 28–42. Manzolini, G., Macchi, E., Gazzani, M., 2013. CO2capture in integrated gasification combined cycle with SEWGS—Part B: Economic assessment. Fuel 105, 220–227. Pellegrini, L., Soave, G., Gamba, S., Lange, S., 2011. Economic analysis of a combined energy–methanol production plant. Appl. Energy 88, 4891–4897. Robinson, K., Tatterson, D., 2008. Economics on Fischer–Tropsch coal-to-liquids method updated. Oil Gas J. 106, 22–25. Sajo, P. Naik, Taegong, Ryu, Vy, Bui, et al., 2011. Synthesis of DME from CO2/H2gas mixture. Chem. Eng. J. 167 (1), 362–368. Sun, S., Jin, H., Gao, L., Han, W., 2010. Study on a multifunctional energy system producing coking heat, methanol and electricity. Fuel 89, 1353–1360. Tyurina, E., Mednikov, A., Skripchenko, O., 2012. Reducing CO2emissions from coal-fired plants for co-production of electricity and synfuels. In: PRESCO 2012 PROCEEDINGS The Energy Debate: Challenges & Alternatives, pp. 101–106. Winkler, H., 2007. Energy policies for sustainable development in South Africa. Energy Sustain. Dev. XI (1), 26–34.