Gas Turbine (FSIG

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Very High-Pressure Fuel-Slurry Integrated Gasifier/Gas Turbine (FSIG/ GT) Power Generation Applied to Biomass Marcio L. de Souza-Santos* Department of Energy, Faculty of Mechanical Engineering, University of Campinas, Rua Mendeleyev, 200, Cidade Universitaria, Campinas, São Paulo 13083-860, Brazil ABSTRACT: The work contributes to the study of the fuel-slurry integrated gasifier/gas turbine (FSIG/GT) concept for the electric power generation process consuming biomass or, more specifically, sugar cane bagasse (SCB). The FSIG/GT process allows for pumping of the solid fuel as a slurry into pressurized reactors, therefore dispensing the need for complex systems of sequential lock hoppers. The slurry drying is achieved through the application of a residual hot gas stream from the process. Because the dryer and gasifier operate at similar pressures, the transfer of particles can be made using simple rotary valves and Archimedes screws. The produced fuel gas is cleaned and injected into the turbine. Previous studies were limited at operational pressures around 2 MPa, while the present evaluates the process working at the vicinity of 10 MPa. This requires intercooling between compression stages as a result of limits of the temperature imposed by the axial compressor blade materials. Rankine cycles are employed to recover energy from the gas-cleaning and exiting process streams as well from the compression intercooling systems. At the present stage investigation, operations at 10 MPa led to overall efficiencies around 34%. That is significantly higher than that presently practiced at power plants of large sugar and alcohol mills but below that achieved in previous studies of FSIG/GT processes consuming SCB and operating around 2 MPa. The main reason for that is attributed to the impossibility of total energy recover and irreversibilities introduced during intercooling. Future works might improve that value.

1. INTRODUCTION The application of biomass, particularly sugar cane bagasse (SCB), as a renewable source of power with near-zero overall greenhouse gas emissions1−5 has increased.6−11 Presently, nearly 10 GW or around 8% of the Brazilian electric power capacity comes from thermoelectric units based on SCB.11 That represents in a 5-fold increase on the value achieved in 2006.10,11 Today, all that power generation from biomass is based on Rankine cycles with boilers operating at pressures near 8 MPa. The advance to more efficient processes, such as biomass integrated gasification/gas turbines (BIG/GTs),12−20 would introduce technical difficulties. The first is found in the gas cleaning to allow for injection into turbines, which demands stringent levels of particulate content as well alkaline concentrations.21−24 Solutions for that obstacle have been found through various techniques.25,26 However, another barrier is found when one tries to feed solid particulate fuels into pressurized vessels. The most common method requires cumbersome sequential operations of pressurized lock hoppers.27 A much simpler alternative is to pump water−fuel slurries into pressurized vessels.28−37 The fuel-slurry integrated gasification/gas turbine (FSIG/GT) applies such a technique, and various configurations have been studied.34−37 Until now, those studies were restricted to pressures in the range of 2 MPa. The present study explores the operation at a much higher pressure or around 10 MPa. Figure 1 shows a possible scheme to allow for such an alternative. As seen, the fuel is mixed with water to produce a slurry (stream 45), which is pumped into the circulating fluidized bed dryer. Because the dryer and gasifier operate at similar high pressures, the dried particles can be transferred from the dryer to the gasifier using simple Archimedes’ screws. The produced gas © 2015 American Chemical Society

Figure 1. Scheme of the studied FSIG/GT process: C, compressor; CB, combustor; CD, condenser; CL, cleaning system; CY, cyclone; D, dryer; DF, dried fuel; FE, screw feeding; FS, fuel-slurry pumping; G, gasifier; GT, gas turbine; HX, heat exchanger; M, mixer; SG, steam generator; ST, steam turbine; P, water pump; and V, valve or splitter.

stream passes through a battery of cyclones and filters to drop the particle sizes within the limits tolerable for injection in gas turbines (stream 26). The drop on the alkaline concentration is accomplished by cooling the gas stream 26 at temperatures below Received: September 15, 2015 Revised: November 4, 2015 Published: November 5, 2015 8066

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Energy & Fuels the dew points of those substances. Such cooling drives the first steam Rankine cycle composed by equipment 17−21. The cleaned gas stream 12 is injected into the combustor 8. To allow for working within the feasible limits of temperatures, the compression of air for combustion requires intercooling (equipment 1−3). The recovered energy from the cooling drives another Rankine cycle composed of equipment 2 and 4−7. The hot gas leaving the combustor is injected into turbine 9. The exiting stream 14 drives the Rankine cycle, which combines equipment 10−14 and aided by the heat exchanger 30. That last equipment is employed to preheat the water (stream 22) before entering into the steam generator (equipment 10) as stream 47. Stream 48 exits the mixer that receives various streams (11, 44, and 58), coming from the various intercooling processes. Besides the intercooling already described, two others should be employed at the air compressions for gasification (equipment 22−28) and gas (stream 24) to be used in the slurry drying. That last intercooling involves equipment 16 and 33−37. Finally, the high-pressure stream leaving the dryer passes through cyclones to drop the particle contents and allow stream 59 to be injected in turbine 38 before exiting the process as stream 60.

Table 1. Main Characteristics of the Fuel (SCB) Consumed by the Process property high heating value (MJ/kg, dry basis) proximate analysis (%, wet basis) moisture volatile fixed carbon ash ultimate analysis (%, dry basis) C H N O S ash particle size distribution (retained mass %) sieve opening (mm) 1.680 0.841 0.354 0.250 0.177 average particle sphericity fuel particle density (kg/m3) apparent real or skeletal

2. METHODOLOGY Similar to previous works,29−32,34−38 the present work employs validated mathematical simulators to verify the feasibility as well to estimate the performance of power generation processes. The comprehensive simulator of fluidized and moving bed equipment (CeSFaMB; http://www.csfmb.com) has helped on the design and optimization of boilers, gasifiers, pyrolysis reactors, and dryers. The simulator has been validated38−49 and applied29−32,34−57 to many situations of diverse equipment operating under different conditions and consuming various feedstock. CeSFaMB provides point-by-point information on temperatures, mass flows, and compositions of all phases in the gasifier throughout its interior. Details of the mathematical model behind that simulation program can be found elsewhere.48 The industrial process and equipment simulator (IPES) has been applied in many previous works.29−32,34−37,58 Apart from the characteristics of streams leaving the gasifier and dryer, CeSFaMB−IPES performs mass and energy balances around each equipment and provides the temperature, pressure, mass flow, and composition of each stream in the process. The combination of those two software allowed for the process evaluation.

value 19.14 50.00 40.78 7.57 1.65 49.66 5.71 0.21 41.08 0.03 3.31

82.00 3.91 9.86 3.23 1.00 0.3 720 1400

dispenses further grinding, hence saving costs on fuel pretreatment. (3) Cylindrical geometry, typical of fibers, was taken as the preferential fuel particle shape. (4) The rate of SCB feeding was set at 36 kg/s (wet basis) or 18 kg/s (dry basis). Those values are in the range of the discarding rate from large sugar−alcohol industrial units. Nevertheless, the present computations might by applied to other scales, and the conclusions arrived here should remain valid. (5) The SCB water slurry contains 40% of dried solid. That has also been applied in previous works.29−31,35 The possibility of using commercially available equipment to pump such a slurry into the pressurized dryer is supported by publications.60,61 Additionally, a manufacturer (http://www. schwingbioset.com/) has indicated that piton pumps could handle slurries with up to 50% in dry biomass. Therefore, the assumption made here related to the dry solid content in the slurry is likely to be conservative. (6) Gasification occurs around 10 MPa. A slightly higher value was assumed for the dying to allow for easy transfer of dried particles to the gasifier using just Archimedes’ screws. (7) The decrease of the alkaline concentration in the fuel gas stream leaving the gasifier (stream 26) is accomplished by reducing its temperature to values around 800 K or below their dew point.24 That cleaning stage is required to allow for injection of gases (stream 13) into turbines.21−24 (8) The efficiencies taken for various critical machines are (a) 87% for axial air compressors62 (a similar value was assumed for gas turbine efficiency), (b) 80% for steam turbines,63 and (c) 90% for pumps.64 (9) The minimum temperature difference of 10 K has been imposed between exchanging heat streams. (10) The maximum temperature for gas injection into gas turbines was set at 1700 K. (11) The temperature of 950 K was set as the limit for streams leaving compressors.65 These premises could be revised in future investigations.

3. PREMISES The main assumptions used in the present work are listed as follows: (1) The technique of bubbling fluidized bed was chosen for the gasification process, while the circulating fluidized bed was applied to the drying stage. Other techniques might be employed for either processes. Nonetheless, it should be noticed that usually bubbling fluidization allows for greater flexibility in terms of fuel composition, density, and particle size distribution (PSD)48,59 than other options. In previous works,34−37 the bubbling bed technique was also applied to the slurry drying but detailed simulations using CeSFaMB showed that the circulating bed alternative would require lower flow rates of hot gas (stream 25) to complete the fuel-slurry drying. This represents savings on the power required for the compression of stream 24 and, therefore, improving the overall power plant efficiency. Future works would also verify if other techniques could lead to higher efficiencies in the fuel gasification process. (2) The characteristics of the consumed SCB are the same as those used in previous works29−31,35,37,40,44,48 and listed in Table 1. Its PSD is the usually found for the SCB leaving sugar−alcohol mills. This 8067

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Energy & Fuels

4. RESULTS AND DISCUSSION 4.1. Gasifier. CeSFaMB software was employed in the gasifier optimization having the mass flow of injected air and internal reactor diameter as variables. The exergetic and cold efficiencies were set as optimization objectives, which are defined as follows: (a) The exergetic efficiency is given by

Table 2. Main Operational Conditions of the Optimized Gasifier

ηexe = exergy of exiting gas /total exergy of streams (gaseous or solids) entering the gasifier

(1)

The exergy of each stream is represented by its mass flow (kg/s) times the respective specific exergy (kJ/kg). (b) The cold gas efficiency or just cold efficiency is defined by ηcold = enthalpy of exiting gas at 298 K /total enthalpy of streams (gaseous or solids) entering the gasifier

main input condition or parameter

value

bed internal diameter (m) bed height (m) freeboard internal diameter (m) freeboard height (m) insulation thickness around the bed and freeboard (mm) number of flutes in the distributor number of orifices per flute diameter of orifices (mm) position of fuel feeding (m) mass flow of feeding fuel (dry) (kg/s) mass flow of injected air (kg/s) temperature of injected air (K) mass flow of injected steam (kg/s) average pressure inside the equipment (MPa) main output condition or parameter

4.0 4.0 5.5 6.0 100 5.0 × 104 10 3.0 1.0 17.99 12.0 766.0 0.0 2.0 value

mass flow of gas leaving the equipment (kg/s) mass flow of solids discharged from the bed (kg/s) mass flow of elutriated solids (kg/s) fluidization voidage (bed middle) minimum fluidization velocity (bed middle) (m/s) fluidization superficial velocity (bed middle) (m/s) carbon conversion (%) average temperature at the middle of the bed (K) average temperature at the top of the freeboard (K) pressure loss at the distributor (kPa) pressure loss in the bed (kPa) transport disengaging height (TDH) (m) rate of energy input by fuel to the equipment (MW) total rate of energy input to the equipment (MW) rate of energy output by hot gasa (MW) rate of energy output by cold gasb (MW) hot efficiency (%) cold efficiency (%) exergy flow brought with the dry fuel (MW) exergy flow brought with the injected gas (MW) total entering exergy flowc (MW) exergy flow leaving with the gas (MW) total exiting exergyd (MW) ratio between total leaving and entering exergy flows (%) ratio between the exergy leaving with the produced gas and the total entering exergy (%)

(2)

The enthalpy of each stream is represented by its mass flow (kg/ s) times the respective specific enthalpy (kJ/kg), with the latter composed by the sensible enthalpy plus low heating value. Similar to previous works,34−37 conditions of impossible or difficult bubbling bed operations have been found because at least one of the following situations occurred: (1) The bed dynamic characteristics fall outside the range of bubbling fluidization. That happens when the gas superficial velocity became smaller than the minimum fluidization or above the second turbulent limit at any point in the bed. (2) The temperature of segregated ash from the fuel reached values equal or above the ash-melting threshold. This leads to particle agglutinations and bed collapse. (3) The steady-state operation could not be maintained. For instance, this happens when the rate of unreacted fuel particle entrainment cannot be compensated by the rate of fuel feeding, thus preventing the bed level to be kept constant. The optimization showed that the operation providing the highest exergetic efficiency (HHE) coincided with the operation where the highest cold gas efficiency (HCE) was achieved. Such was found when 14 kg/s of air was injected into a 4 m internal diameter reactor. Table 2 summarizes the operational parameters of that operation. The produced gas composition is described in Table 3. Figure 2 depicts the temperature profiles of various phases in the gasifier bed section. The sudden variation of the temperature is mainly due to pyrolysis occurring near the fuel feeding position or at 1 m above the gas distributor surface. Tar fast release and destruction around the fuel feeding position are illustrated in Figure 3. Figure 4 shows the temperature profiles of various phases in the freeboard. As seen in the present case, relatively small variations of temperatures are found in that region. The concentration profiles of main gases throughout the entire reactor are shown in Figures 5 and 6. Sudden variations of concentrations can be noticed as a result of the pyrolysis that takes place around the fuel feeding position, therefore demonstrating how important that process is during gasifications, particularly of biomasses. Details on the various reactions and the phenomena involved in fluidized bed gasifiers can be found elsewhere.48

26.56 1.695 0.095 0.672 0.092 0.150 81.32 936.0 936.0 0.01 22.84 3.88 324.98 329.89 286.21 260.23 86.76 78.88 491.2 4.84 496.1 280.42 284.70 57.39 56.53

“Hot gas” refers to the temperature, pressure, and composition as found at the exiting point from the gasifier. b“Cold gas” refers to the gas properties if at 298 K, 101.325 kPa, dry, and tar free. cSum of exergies brought by gases, liquids, or solids injected or fed into the gasifier. dSum of exergies carried by gases, liquids, or solids leaving the gasifier. a

4.2. Dryer. The optimization of fuel-slurry drying is sought to minimize the mass flow of stream 25 to save power required for compressing stream 24 (Figure 1). Determining the temperature, pressure, and composition of that stream was possible through the application of IPES software to simulate the whole process. Details about that simulation are described ahead. As mentioned above, the circulating fluidized bed technique was chosen for the drying operation. To simplify the optimization, just the dryer internal diameter and mass flow of hot gas injected into it have been taken as variables. Other dimensions and assumptions used as inputs are described in Table 4. 8068

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Energy & Fuels Table 3. Composition of the Gas Stream Leaving the Gasifier chemical species

molar percentage

H2 H2O H2S NH3 NO NO2 N2 N2O O2 SO2 CO CO2 HCN CH4 C2H4 C2H6 C3H6 C3H8 C6H6 tar

16.8108 4.0732 0.0110 0.2272 0.0000 0.0000 26.7590 0.0000 0.0000 0.0018 34.3168 8.3168 0.0205 9.0606 0.1823 0.1417 0.0068 0.0064 0.0655 0.0000

Figure 4. Temperature profiles of various phases in the gasifier freeboard region.

Figure 5. Concentration profiles of CO2, CO, and O2 throughout the gasifier.

Figure 2. Temperature profiles of various phases in the gasifier bubbling bed.

Figure 6. Concentration profiles of H2O, H2, and CH4 throughout the gasifier.

4.3. Process. The gasifier optimization provided the characteristics of stream 26 (Figure 1). From that, IPES was applied for a first evaluation of the whole process, including the determination the properties of stream 25, which completed the information required for the dryer optimization. The various steam-based or Rankine cycles were also optimized to provide maximum efficiencies. As seen, the whole procedure involved iterative optimizations. The result produces the temperature, pressure, composition, and mass flows of all streams as well the operational details of drying and gasification. The power generation overall efficiencies based on the first and second laws of thermodynamics were computed as well. Table 5 lists the temperatures, pressures, and mass flows of all process streams. It is worth noticing that, during the simulations, the quality of steam leaving steam turbines was never allowed to acquire values below 100%. In addition, pressure of stream 60, leaving turbine 38, had to be raised to ensure the exiting temperature above the

Figure 3. Concentration profiles of tar and other gases in the bed.

The best situation led to a dryer with an internal diameter of 1.4 m at which 56 kg/s of hot gas (stream 25) were injected; values below that accomplished no or just partial removal of the water in the feeding slurry. Refining those values is also possible, but it should not result in significant changes on the conclusions arrived at the present stage of investigation. The temperature profiles in the dryer dense and lean regions are shown in Figures 7 and 8. Figure 9 depicts the changes of the water vapor concentration in the gas phase flowing through the equipment. The surge at 0.5 m is owed to fuel slurry feeding in the dryer at that position. 8069

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Energy & Fuels Table 4. Main Dimensions and Operational Characteristics of the Dryer main input condition or parameter

value

internal diameter (m) total height (m) insulation thickness around the equipment (mm) number of flutes in the distributor number of orifices per flute diameter of orifices (mm) slurry feeding position (above the distributor) (m) mass flow of feeding fuel (50% wet) (kg/s) mass flow of water added to form the fuel slurry (kg/s) percentage of dry fuel in the slurry (%) mass flow of injected gas (kg/s) temperature of injected gas (K) average pressure inside the equipment (MPa) main output condition or parameter

1.4 10.0 200 1 × 103 10 3.0 0.5 36.0 9.0 40.00 56.0 975 10.0 value

mass flow of gas leaving the equipment (kg/s) mass flow of solids discharged from the dense region (kg/s) concentration of water in the leaving solid (%) molar fraction of water in the exiting gas stream (%) fluidization superficial velocity (middle of dense region) (m/s) tar flow at the top of the lean region (kg/s) pressure loss at the distributor (kPa) pressure loss in the dense region (kPa) exergy flow brought with the slurry (MW) exergy flow brought with the injected gas (MW) total entering exergy flow (MW) exergy flow leaving with the gas (MW) total exiting exergy (MW) ratio between leaving and entering exergy flows (%) ratio between exergy leaving with gas and total entering (%)

Figure 9. Concentration of water in the gas flowing upward in the equipment.

dew point of water in the gas mixture. Actually, those conditions are too stringent and might be relaxed to some degree, which would increase the overall power generation efficiency. Table 6 summarizes the overall conditions used to compute the power generation efficiencies according to the first and the second laws of thermodynamics. As seen, the present work showed that first law efficiency of the present proposition for power generation approaches 34%. That value is significantly higher than the present average of 20% achieved in power plants installed at large sugar and alcohol mills.67 Nonetheless, they are still below that predicted by previous investigations of power units consuming SCB.35,37,66 The main reason for that was the limit imposed to the temperature of streams leaving axial compressors or around 950 K.65 Such threshold demands intercooling circuits, which, despite energy recovering using steam cycles as well as other strategies, cannot avoid irreversibilities and losses to the environment. On the other hand, intercooling is not required if the lower pressures of compressions were applied. For instance, air can be compressed from room temperature to near 4 MPa without intercooling. The previous works35,37,66 were limited to the last range of pressures. Attention should also be called to the fact that special heat exchangers would be able to handle the high temperatures involved in the operation of equipment 17.68−70

83.45 17.98 0.0 47.95 1.20 0.000 1.5 28.08 506.0 46.97 554.1 68.15 364.3 65.75 12.30

5. CONCLUSION Figure 7. Temperature profiles of various involved phases in the dryer dense region.

The FSIG/GT process has been simulated for cases operating at very high pressure. At the present instance, the power generation concept has been tested for operations at 10 MPa and consuming SCB. After optimizations of the gasifier and dryer dimensions and operational conditions as well as the whole power generation process strategy, the overall first law efficiency reached values close to 34%. Despite being significantly higher than the average 20% presently practiced at large sugar and alcohol mills, that value is still below what has been found in previous studies for operations at 2 MPa.35,37,66 The main reason for that rests on the need of intercooling between compression stages to avoid surpassing the present temperature limits of materials composing axial compressor blades.65 Thus, future works would concentrate on processes operating below 4 MPa, when the temperatures of gas streams leaving axial compressors can be kept beneath those limitations.

Figure 8. Temperature profiles of various involved phases in the dryer lean region.

8070

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Energy & Fuels Table 5. Temperature, Pressure, and Mass Flow of the Power Generation Streams stream

fluid nature

temperature (K)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30

air air air air water steam steam water water water water gas gas gas gas water water water steam steam water water gas gas gas gas steam steam water water

298.00 768.99 430.76 710.28 391.81 758.00 408.66 391.70 298.00 298.01 382.28 800.00 1700.00 751.49 375.26 298.00 298.00 344.90 740.00 498.81 467.00 467.26 375.18 375.18 975.47 1065.00 864.35 409.40 391.70 391.97

pressure (kPa) 0.10133 0.20500 0.20400 0.99900 0.40200 0.40100 0.20000 0.19000 0.10100 0.32000 0.31000 0.99900 0.98990 0.12000 0.11500 0.10133 0.13000 0.11000 0.10000 0.14000 0.13900 0.10100 0.11100 0.11100 0.10100 0.10000 0.10000 0.20000 0.19000 0.10010

× × × × × × × × × × × × × × × × × × × × × × × × × × × × × ×

mass flow (kg/s)

stream

fluid nature

temperature (K)

185.00 185.00 185.00 185.00 22.20 22.20 22.20 22.20 140.00 140.00 140.00 28.85 201.85 201.85 201.85 300.00 300.00 300.00 286.00 286.00 286.00 286.00 157.85 56.00 56.00 28.85 3.90 3.90 3.90 3.90

31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

water water water air air air air water steam steam water water water water slurry slurry water water water gas gas water steam steam water water water water gas gas

298.00 298.00 327.73 298.00 768.99 488.48 802.12 391.81 758.00 428.86 391.70 298.00 298.01 405.93 298.00 298.05 345.00 313.63 333.60 884.17 617.20 317.80 758.00 428.86 317.70 298.00 298.01 407.76 606.00 338.87

103 104 104 104 104 104 103 103 103 103 103 104 104 103 103 103 103 103 105 104 104 105 103 103 105 105 105 103 103 105

main parameter

value 212.88 318.67 105.79 314.21 33.67 506.0 20.91

a

As a result of compressors and pumps. bFrom steam and gas turbines. On the basis of the lower heating value (LHV). dDefined as useful mechanical power output/rate of energy input by fuel slurry. eDefined as useful mechanical power output/rate of exergy input by fuel slurry.

c

■

AUTHOR INFORMATION

Corresponding Author

*Telephone: +55-19-97107134. Fax: +55-19-3513278. E-mail: [email protected]. Notes

The authors declare no competing financial interest.

■

0.11000 0.13000 0.11000 0.10133 0.20500 0.20400 0.10100 0.40200 0.40100 0.20000 0.19000 0.10100 0.32000 0.31000 0.11000 0.22000 0.10050 0.31000 0.30000 0.20500 0.20000 0.40200 0.40100 0.20000 0.19000 0.10100 0.32000 0.31000 0.10090 0.90000

× × × × × × × × × × × × × × × × × × × × × × × × × × × × × ×

103 103 103 103 104 104 105 104 104 103 103 103 103 103 103 104 105 103 103 104 104 104 104 103 103 103 103 103 105 103

mass flow (kg/s) 70.00 70.00 70.00 12.00 12.00 12.00 12.00 1.20 1.20 1.20 1.20 6.00 6.00 6.00 45.00 45.00 28.20 175.00 175.00 56.00 56.00 5.00 5.00 5.00 5.00 29.00 29.00 29.00 83.54 83.54

(3) Krzywański, J.; Rajczyk, R.; Nowak, W. Model research of gas emissions from a lignite and biomass co-combustion in a large scale CFB boiler. Chemical and Process Engineering 2014, 35 (2), 217−231. (4) Krzywanski, J.; Rajczyk, R.; Bednarek, M.; Wesolowska, M.; Nowak, W. Gas emissions from large scale circulating fluidized bed boilers burning lignite and biomass. Fuel Process. Technol. 2013, 116, 27−34. (5) Werther, J. Potentials of biomass co-combustion in coal-fired boilers. Proceedings of the 20th International Conference on Fluidized Bed Combustion; Xi’an, China, May 18−21, 2009; pp 27−42. (6) Maues, J. A. Optimization of Power Generation from Bagasse and Sugarcane Waste in a Brazilian Sugar and Alcohol Mill. Proceedings of ISES World Congress 2007 (Vol. I − Vol. V); Springer: Berlin, Germany, 2009; pp 2444−2448, link.springer.com/chapter/10.1007%2F978-3540-75997-3_495#page-1 (accessed March 3, 2014). (7) Macedo, I. C.; Seabra, J. E.A; Silva, J. E. A. R. Greenhouse gases emissions in the production and use of ethanol from sugarcane in Brazil: The 2005/2006 averages and a prediction for 2020. Biomass Bioenergy 2008, 32 (7), 582−595. (8) Deepchand, K. Sugar Cane Bagasse Energy Cogeneration Lessons from Mauritius. Proceedings of the Parliamentarian Forum on Energy Legislation and Sustainable Development; Cape Town, South Africa, Oct 5−7, 2005; http://www.un.org/esa/sustdev/sdissues/ energy/op/parliamentarian_forum/deepchand_bagasse.pdf (accessed Nov 24, 2013). (9) Brazilian Ministry of Mines and Energy (MME). 2007 Report; http://www.mme.gov.br/mme/menu/ben2007.html (accessed April 14, 2014). (10) Brazilian Ministry of Mines and Energy (MME). Planning for 2020; http://www.mme.gov.br/mme/menu/pde2020.html (accessed Nov 16, 2013).

Table 6. Main Overall Process Efficiency Parameters mechanical power inputa (MW) mechanical power outputb (MW) net mechanical power output (MW) rate of energy input by fuel slurryc (MW) efficiency based on first lawd (%) rate of exergy input by fuel slurry (MW) efficiency based on second lawe (%)

pressure (kPa)

REFERENCES

(1) Roth, I. F.; Ambs, L. L. Incorporating Externalities into a Full Cost Approach to Electric Power Generation Life-cycle Costing. Energy 2004, 29, 2125−2144. (2) Basu, P. Biomass Gasification, Pyrolysis and Torrefaction: Practical Design and Theory, 2nd ed.; Academic Press: San Diego, CA, 2013. 8071

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DOI: 10.1021/acs.energyfuels.5b02093 Energy Fuels 2015, 29, 8066−8073