Optimal Integration of Algae–Switchgrass Facility for the Production of

Sep 5, 2016 - (6) Although this option is interesting in terms of sustainability, the variability in solar incidence implies that part of the producti...
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Optimal integration of algae – switchgrass facility for the production of methanol and biodiesel Mariano Martín, and Ignacio E. Grossmann ACS Sustainable Chem. Eng., Just Accepted Manuscript • DOI: 10.1021/ acssuschemeng.6b01558 • Publication Date (Web): 05 Sep 2016 Downloaded from http://pubs.acs.org on September 8, 2016

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Optimal integration of algae – switchgrass facility for the production of methanol and biodiesel Mariano Martína1, Ignacio E. Grossmannb a

Department of Chemical Engineering. University of Salamanca. Plz. Caídos 1-5, 37008 Salamanca (Spain)

Department of Chemical Engineering. Carnegie Mellon University. 5000 Forbes Ave. 15213. Pittsburgh, PA b

Abstract. In this work we integrate switchgrass and algae in order to operate a biorefinery with no need for fossil based raw materials in the production of biodiesel (FAME). A superstructure optimization approach is used to select the optimal integrated topology, gasification and reforming technologies, that provides the thermal energy and the methanol that biodiesel production requires. The excess of methanol can be sold as biofuel or it can be further processed to gasoline. The optimal integrated process involves indirect gasification followed by steam reforming based on the need for high H2 to CO ratio to produce methanol and avoiding the use of oxygen. The integrated process produces 776ML/yr (205 Mgal/yr) of biofuels, 34% FAME, at 0.14€/L (0.53 €/gal). The plant does not emit CO2, but captures 1.27 kg of CO2 per kg of methanol produced.

Keywords: Lignocellulosic, Algae, CO2 capture, biodiesel, methanol, process design

1

Corresponding Author. M Martín: [email protected]

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Introduction Biodiesel is widely considered a biofuel although the alcohol required for its transesterification methanol, is typically produced from fossil resources like coal or natural gas. The use of methanol has been justified from technical and economic points of view, quicker reaction times and cheaper than any other alcohol. Alternatively, ethanol can be used as transesterification agent too. Martín & Grossmann 1 designed a facility that used ethanol produced out of the same algae for the production of biodiesel, Fatty acid ethyl ester (FAEE). The biodiesel production cost was competitive with that produced from fossil methanol and algae oil and no fossil fuel based chemical was needed. However, methanol can also be produced from either residues of the biodiesel industry or biomass wastes. Martín & Grossmann 2 evaluated the production of methanol from glycerol reforming to be used in the production of fatty acid methyl ester (FAME) but the methanol produced was not enough to run the process. Lately, several efforts have been presented to hydrogenate CO2 to produce methanol 3-5 and thus a further integration step was carried out so that CO2 is used to produce methanol together with hydrogen from electrolysis using solar or wind energy.6 Although this option is interesting in terms of sustainability, the variability in solar incidence implies that part of the production capacity is not fully used over most of the year, thereby, incrementing the capital costs. The integration of different renewable resources can also make biodiesel to be truly renewable. In fact, it is possible to produce methanol from the syngas produced from switchgrass or lignocellulosic material in general7-9 to be used for algae oil transesterification. This integrated process does not only secure biobased diesel production, but it reuses the CO2 captured in the syngas cleaning steps for algae growing avoiding further emissions. In this way, the process has negative CO2 emissions. Therefore, in this paper the production of algae from CO2 and solar energy is coupled with the use of switchgrass to obtain methanol. The paper is organized as follows. In section 2 we describe the process. In section 3 we discuss the main modeling assumptions and solution procedures for the MINLP problem formulated. Subsequently, in section 4 we present results of the operation of the facility, ending with the economic evaluation. Finally in Section 5 we draw some conclusions.

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Process description. The process consists of four sections. Algae oil production, biosyngas production, methanol synthesis and biodiesel production. Figure 1 shows the scheme for the integrated facility.

Figure 1.- Integration of switchgrass and algae for the production of methanol and biodiesel. Algae oil production. The production of oil and starch from algae is performed by injecting CO2 into the water. The CO2 has two sources: the CO2 captured from the syngas cleaning step, and that from thermal plants and other facilities, see Figure 1. Water can be saline water or waste water so that the consumption of freshwater is reduced. Fertilizers need to be added too, see Figure 2. We assume that the dry algae biomass, 15 kg/s, is composed by lipids, starch and protein with 50% being lipids. Together with the algae, oxygen is produced and water is evaporated.10-11 Next, the algae are harvested. This stage has typically been the most energy intensive. However, Univenture Inc. developed a promising capillarity based technology. It integrates harvesting and algae drying. It operates similarly to membrane systems and paint drying. In spite of the lack of industrial size information on the operation of this system, we consider this option in our analysis. The oil is extracted using solvents, cyclo-hexane, and mechanical action. The leftovers of the biomass, carbohydrates and protein, are separated and can be used to obtain energy for the process or they can also be further treated to obtain glucose and added value chemicals. The oil is used for transesterification and biodiesel production. 12 3 ACS Paragon Plus Environment

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Figure 2.- Algae oil production Methanol Synthesis: The idea is to use lignocellulosic raw materials to produce syngas that is converted into methanol. The amount of biomass available is up to 20kg/s. The optimization will decide on the amount of its use. Next, the switchgrass is gasified and the gas is treated to remove hydrocarbons using reforming (steam or partial oxidation), followed by gas cleaning and composition adjustment for the optimal production of methanol. Finally, the CO2 captured in the syngas cleaning step is fed to the algae ponds, see Figure 1. Most of the stages are common to previous papers on gasification of biomass and gas clean up 13,14 or for methanol synthesis from syngas.2 Biodiesel synthesis The use of heterogeneous catalysts for the production of biodiesel simplifies the purification stages since they can be easily removed from the products, or they can be packed in the reactor. Therefore, the process is simpler than the ones using homogeneous catalysts as it can be seen in Figure 3. The reactants are prepared and fed to the reactor where equilibria, given by eq. (1), govern the operation of the reactor. TG + R ' OH ↔ DG + R ' COO − R1 DG + R ' OH ↔ MG + R ' COO − R2

(1)

MG + R ' OH ↔ Glycerol + R ' COO − R3

The model of the reactor is taken from the literature.12 After the reactor, a distillation column is used to recover the excess of methanol. The bottoms of the distillation column contain mainly glycerol and biodiesel, with small amounts of methanol, water, FFA and oil. A gravity separation allows the recovery of

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glycerol with purity higher than 92%, while the biodiesel is purified with distillation. In this column, the temperatures of the distillate and that of the bottoms have an upper bound to avoid product decomposition.

Figure 3.-Oil transesterification. Modeling. In this section, we describe the main assumptions used in modeling the process for the production of synthetic methanol using wind / solar power and CO2 to be used for the production of biodiesel. We use mass and energy balances, design equations, thermodynamic and phase equilibria and experimental data in order to develop models for all the units involved in the process. For the sake of reducing the length of the paper, we briefly describe the principles involved, and we refer to previous papers and their supplementary material 2,12-14 for more detailed modeling aspects. Compression stages are modeled considering polytropic behavior, and when cooling down, water condenses assuming that the gas phase remains saturated with water. We assume 10% pressure drop across each adsorbing bed. Oil production and transesterification The detailed modeling for these stages can be seen in the supplementary material of the paper Martín & Grossmann.12 Oil production The growth rate considered is 50 g/m2 d, and the CO2 consumption is given by Sazdanoff,11 eq.(2)  m3   g  CO 2   = 0.6565·algae growth  2  + 5.0784 m d   d 

(2) 5

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The amount of make-up water needed, 0.006kg per kg of biomass, and that of fertilizers, 0.14 kg per kg of dry biomass, are taken from the report by Pate.10 The energy consumed for the growth of algae is computed following Sazdanoff data. Next, algae are harvested and dried up to 5% moisture content using Univenture‘s design. The energy consumption of this stage is 40W for 500L/h of flow.12 The oil, representing 50% of the dry biomass, is extracted using a solvent together with mechanical action. Next, the solvent and the oil are separated in a vacuum distillation column so that the bottoms are below 350ºC to avoid oil decomposition. The oil is further sent to transesterification and the solvent is recycled. Oil transesterification Martín & Grossmann12 proved that the use of heterogeneous catalysts is promising due to the ease of separation of the products; there is no need for biodiesel washing reducing water consumption within the facility, and it is possible to process different oil sources. The reactor is modeled using the stoichiometry of the reaction. The conversion is computed by eq. (3), a surface response model developed in the above mentioned paper: yield = −73.6 + 2.5*T ( HX4, Reactor2 ) + 24.9*Cat + 8.8* ratio _ met − 0.01*T ( HX4, Reactor2 ) − 2

1.29*Cat 2 − 0.39* ratio _ met 2 − 0.26*T ( HX4, Reactor2 ) *Cat

(3)

Table 1 shows the range of operating variables. Table 1.-Range of operation of the variables. Heterogeneous catalysis

Variable Lower bound Temperature (ºC) 40 Molar ratio methanol (mol/mol) 6 Catalyst (%) 1

Upper bound 60 12 4

Next, the methanol is recovered using a distillation column. This column operates under vaccum with an upper bound for the bottoms temperature of 150ºC to avoid glycerol decomposition. The polar, glycerol phase, and non polar, biodiesel phase, are separated by gravity at 60ºC. The biodiesel phase has to be further purified. Another vacuum distillation column is required so that the top operates below 250ºC. All the columns are modeled using short cut methods,15 validated with CHEMCAD, with variable reflux ratios from 1 to 3.

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Methanol production The detailed modeling for these stages can be seen in Vidal and Martín,14 the supplementary material and papers of Martín & Grossmann.2,13 Gasification: Indirect gasification: This alternative consists of feeding the switchgrass together with steam and olivine to the gasifier, working at 1.6 bar. Hot olivine from the combustor provides the energy for the operation. We model this unit based on mass and energy balances considering the correlations and feed ratios (0.4kgsteam/kg dry biomass; 27kg olivine,kg dry biomass) from Phillips et al.9 to compute the gas composition. The solid remaining collects the residues from the biomass not transformed in gas and the ash. The solids are recovered in a cyclone and sent to a combustor, where by burning the carbonous residue with hot air at 200ºC, the olivine is reheated up and the residue decomposes into gases and ash. The energy balance between both units must hold. The ash is removed almost completely, 99%, in an electrostatic precipitator and the hot gases are used to provide energy within the process. Direct Gasification: It consists of a single unit. The biomass is fed to the gasifier together with oxygen and steam. Using the correlations by Eggeman16 and Zhu.17 it is possible to compute the gas composition and the optimal operating conditions, namely, temperature, pressure and the ratios between the steam, oxygen and the feed.

Gas clean-up: We consider steam reforming or partial oxidation for the removal of hydrocarbons. The tar reformer can work at low or high pressure.18 Steam reforming: In this unit we use the stoichiometry of reactions (4)-(5) and the conversions by Phillips et al.9 to compute the gas product. The operation is adiabatic and, to ensure the conversions, we constrain the outlet temperature to maintain an average temperature of 600ºC. C n H m + nH 2 O

NH 3

 → nCO + (

m + n) H 2 2

1 3  → N2 + H2 2 2

(4) (5)

Partial oxidation: We use pure oxygen in stoichiometric proportions to oxidize the hydrocarbons such as given by eq. (6). The same conversions per species as the ones in Phillips et al.’s 9 work are assumed, based on the experimental results by Vernon et al.19 and Deutschmann and Schmidt.20 The 7 ACS Paragon Plus Environment

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reactions are exothermic, and thus, the unit is a source of energy within the process for integration and steam generation. Cn H m +

n O2 2

 → nCO +

m H2 2

(6)

To remove solids, cold or hot cleaning is considered. Finally, a PSA system using a bed of oxides is used to trap the traces of hydrocarbons left after reforming. Cold cleaning. We use a wet scrubber that operates at 40ºC and 1.2 bar when the syngas has been produced in the indirect gasifier.21 Thus, water condenses from the gas stream and solids (char) and NH3 are removed with the liquid phase. The flow of water is 0.25 kg per m3 of gas.22 The liquid phase is sent to treatment, while the gas exits the scrubber saturated at the operating conditions. The gas stream is compressed to 4.5 bar and cooled down to 25ºC to be sent to the following stage. Hot cleaning. When operating at medium or high pressure, the use of ceramic filters is suggested. They operate above 300ºC to remove the solids (Char, Olivine). Next, the gas is expanded to obtain energy for the process. Final hydrocarbon and H2S elimination: A system of various PSA adsorbent beds is used. The operating conditions are 25ºC and 4.5 bar.21 After cooling to 25ºC, water condenses and it is eliminated before the adsorbent unit. We model this unit as two columns assuming that all of the hydrocarbons left in the gas stream are removed, as well as the ammonia, nitrogen and H2S. One of the columns, MS1, operates, while the second unit the MS2 is being regenerated. Composition adjustment. Once the main contaminants are eliminated, the ratio between CO and H2 may need to be adjusted for the optimal production of methanol. In order to perform such an adjustment, three alternatives that can operate simultaneously as seen in Figure 1, are considered. The alternatives do not correspond to integer decisions, but a fraction of the total stream can be fed to each technologies. The first one is the use of water shift to reduce the amount of CO by producing more H2. The second is a bypass. Finally, a hybrid membrane / PSA system with a bed of Zeolite 13X is considered to remove the excess of hydrogen. Hydrogen is an asset as byproduct of the process.

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Water gas shift: The model for this reaction is carried out based on the chemical equilibrium of the WGSR, eq. (7). The product composition is computed assuming that equilibrium is reached for the operating pressure, temperature and feed composition, computing the steam added too. The equilibrium constant is taken from the literature.23,24

CO+ H 2 O

← → CO2 + H 2

(7)

Bypass: In case there is no need to adjust the CO:H2 ratio or if we only need to process a fraction of the raw syngas, we allow a bypass. H2 Membrane / PSA system: Alternatively, if the fraction of hydrogen is larger than that required, a hybrid system consisting of a metal membrane and a PSA system is used to recover the excess of hydrogen. The unit operates at 25 ºC and 4.5 bar. Recovery of 100% is assumed. Methanol Synthesis Figure 4 shows a detail of this section of the process. It can be divided into two steps, CO2 capture and synthesis loop. For the reactor to operate properly the ratio hydrogen to CO must be within 1.75 and 3,25 while the CO2 plays an important role and has to be within 2-8% in the feed.26 Furthermore, the syngas composition must satisfy the following ratio25,27, given by eq. (8):

1.5 ≤

H 2 − CO2 ≤ 2.5 CO + CO2

(8)

Thus, after the composition adjustment, in order to achieve the required composition of CO2 in the feed stream, a fraction of the syngas is further treated in an adsorbent bed, operating at 4.5 bar and 25ºC, and the rest is bypassed. The bed adsorbs 95% of the CO2 in the stream processes. The CO2 captured is further used to grow the algae. Methanol is produced using a catalyst composed of CuO −ZnO –AlO following the set of reactions given in eq. (9)

CO + 2 H 2 ↔ CH 3OH

(9)

CO2 + H 2 ↔ CO + H 2O

The product of the reactor is computed by modeling the unit considering the molar balance to carbon, hydrogen and oxygen, the energy balance and assuming that chemical equilibrium at the operating pressure and temperature is achieved. Actually, although the equilibrium concentration is the target, the 9 ACS Paragon Plus Environment

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reactor design is what determines how close to that target we operate. For the purpose of this work, we assume that equilibrium is reached. The equilibrium constants are given by the experimental results of Cherednichenko28 and Bisset29. Thermodynamics indicate that the reaction is favored by low temperatures and high pressures. However, today’s synthesis processes take place at low pressure (50-100 bar) since these processes use far less energy than the ones with high pressure as the synthesis gas compression is a costly operation. Furthermore, although the equilibrium conditions favor low temperatures, methanol converters must be operated at temperatures in the range 200–300 ◦C to ensure the catalysts are active and to use the heat of reaction effectively.26,27,30 Since the conversion is typically low, the product, methanol, together with water are recovered from the stream by condensation in a flash separation. The flash is modeled as a gas-liquid equilibrium as a function of the pressure and temperature. The gases, hydrogen, CO and CO2 , are recycled to the reactor. The methanol must be purified. If the amount of water is low, molecular sieves are used. Otherwise, a distillation Colum is required.

Figure 4.- Methanol synthesis section Solution procedure The aim is to optimize the topology and the operating conditions by minimizing the production cost to design a facility that integrates switchgrass and algae for a fully biobased diesel. To improve the design and energy efficiency of the integration of biomass types, mathematical optimization techniques are used. We propose a conceptual design based on the optimization of a superstructure embedding the various 10 ACS Paragon Plus Environment

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process units involving biomass gasification and syngas purification considering alternatives for some of the steps in the process to evaluate the trade-offs related to thermal energy vs. direct electricity production. The optimization of the superstructure is formulated as an MINLP problem, where the model involves a set of constraints representing mass and energy balances for all the units in the system. An economic evaluation is performed to compute the investment and the production costs of fuels of the facility. On the one hand, for the biodiesel section we use the same production capacity as previous papers,12 261 ML/yr (69 Mgal/yr) of FAME. For the switchgrass processing section we consider a feed up to 20 kg/s of biomass, typically the processing capacity of second generation bioethanol plants.13 The production capacity of methanol is allowed to range from that needed for oil transesterification up to fully use of the switchgrass. In order to compare the technologies involved we use the objective function described in eq. (10), a simplified profit evaluation involving the production of methanol and biodiesel and the cost of the main utilities such as steam, oxygen and electricity. Z= fc ( MetOH )Pr oduced + fc ( FAME )Pr oduced − steam _ used −   fc ( O2 )Consumed + ( CE / 3600 )· ∑ W ( Compres i ) − W (Turbine)  Gasifier / Oxidation  i = compresors 

CO2 ·



Steam _ used =



fc ( Water )Consumed ·CSteamHP +

Gasifier /WGSR

  CSteamLP   Q( HXi ) Q( HXi ) ∑ ∑  λ  Sources = HX 17, HX 18, Sinks = HX 3, HX 17, HX 12  HX 29,Tar ( PO ) 

(10) Due to the small amount of alternative topologies, a decomposition of the MINLP is carried out into 4 NLP’s for each one of the reforming and gasification technologies, with 5600 variables and 4600 constraints each, where we compare the values of the objective functions selecting the topology with highest profit. Next, a detailed economic evaluation is performed after the design of a heat exchanger network.31

Results and discussion Topology and process operation. The best integrated process, for the largest profit, corresponds with the use of Ferco gasifier and steam reforming, due to the need for a H2 to CO ratio close to 2, in which case the use of steam refoming reduces the need for higher production of H2 in the WGSR. Furthermore, the alternatives using oxygen as

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raw material are also penalized. Figure 5 shows the relative objective function of the four options there F stands for Ferco, R, Renugas, S, steam reforming and O, partial oxidation.

Figure 5.- Relative objective function (F stands for Ferco, R Renugas, S Steam reforming and O, partial oxidation) For the optimal integrated process, Table 2 sumarizes the main operating conditions of the different units involved in the optimal topology: Table 2.- Major operating conditions Unit/Op. Condition T (ºC) P (bar)

Gasifier/Combustor WGSR 890/983 200 1.6 5

H 2 − CO2 CO + CO2 Steam (kg/kgfeed) Cat Met/Oil (mol/mol) Cat add

6.8/20

Methanol 200 87.6 2.25

Transesterification 60 4

20.145/6.07 3.6 6.531 0.262

The production capacity of the facility is 776ML/yr (205 Mgal/yr) of which 261 ML/yr (69Mgal/yr) correspond to biodiesel by using the full availability of biomass and algae. We still produce glycerol as byproduct, 21 t/yr. The consumption of CO2 is 1.99 kg per kg of methanol sold, 3.46kg per kg of biodiesel produced. However, in this process CO2 is captured from the switchgrass processing section, 0.71 kg of CO2 per kg of methanol sold. Thus, in order for our process not to emit the CO2, it can be injected into the 12 ACS Paragon Plus Environment

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algae ponds. As a result 36% of the CO2 requireed by the integrated process is provided internally, the rest (1.27 kg of CO2 per kg of produced methanol or 2.33 kg per kg of biodiesel) is the real reuse capacity of the process coming from a capture system within power or cement production plants. In case of using solar panels and CO2 to produce the methanol requried for the transesterification, the facility requires some heat, 3.2 MW, and 6.9 MW cooling.6 Furthermore, the stand alone production of biodiesel12 requires 1.94 MJ/gal of biodiesel. However, the facility evaluated in this work, where methanol is produced via syngas, requires 25 MW of electricity, and 77 MW of cooling after heat integration. No thermal energy is required after heat integration. The high operating temperatures of the gasification section provides the energy for the biodiesel production. Economic evaluation of the integrated process. We consider the labour costs, utilities (electricity and cooling water), chemicals (fertilizers, glycerol as credit), equipment maintenance and amortization (linear with time in 20 years), taxes, overhead (2.1% investment) and administration.32The total cost after the credit from glycerol (at 0.3€/kg) is 108 M€ /yr (0.14€/L). The raw materials, swichgrass, represents the major share. However, there are four main contributions almost with the same importance, see Figure 6. It is important to note that we are not considering a price for the CO2 due to the complexity of assigning an economic value to it. On the one hand, we can get some credit since we are avoiding its emission or saving the money a company needs to pay for its transportation and sequestration. On the other hand, the moment a mature market for CO2 is developed, we may need to pay to use it. Assuming that any producer saves the carbon tax if we use the CO2, at €40/t of CO2, the production is reduced by 20%, to 0.11€/gal. This is the maximum credit we might obtain of the CO2, since the capture process is expensive and the producer may decide to reduce what they pay to avoid emission based on the cost for capture.

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Figure 6.- Breakdown of production costs The investment cost is also computed based on Sinnot’s factorial method.32 The estimation of the units uses the correlations presented in the supplementary material of Almena and Martín33 based on Matche.34 Piping, insulation, instrumentation and utilities and chemicals represent 20%, 15%, 20% and 10% of the equipment cost. The land and buildings cost is estimated to be 8 M€, and raw material accounts for the biomass and the water. These items add up to the fixed cost (132 M€). The fees represent 1% of the fixed cost. Direct cost is 133M€. The investment cost including start up, and other expeeses adds up to 180 M€. The distribution of the investment cost per section, taking into account that the heat exchangers are for all of them due to the integration, is presented in Figure (7). Lignocellulosic biomass processing represents 60% of the total while the biodiesel section is the lower investment.

Figure 7.- Share of the different sections to the equipment cost 14 ACS Paragon Plus Environment

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We can compare this fully renewable biodiesel with the one produced following different paths either using algae to produce ethanol and oil,11 or by using solar energy to produce both algae and methanol via CO2 hydrogenation.6 For comparison purposes, we have scaled both in terms of total biodiesel production to be 261—106 L/yr (69Mgal/yr). Comparing this integrated facility with the one that uses solar energy to produce the methanol required for the transesterification of the oil,6 the main difference is that in the results presented in this paper show that, due to the high cost for producing methanol, only that required to operate the facililty is produced. By scaling that facility to mach the biodiesel production capacity of 261—106 L/yr, the production cost results in 0.20€/L and the investment adds up to 122M€. Thus, the investment cost is one third lower, 122M€ vs. 180 M€, but the production costs are 50% higher in case of producing the methanol via CO2 hydrogenation. The second interesting comparison is against the use of algae for the production of both, the oil and the alcohol, ethanol in this case.1 This facility has a production capacity of 288—106 L/yr of biofuels, of which 261—106 L/tyr are biodiesel. These values have been computed by scaling down the facility presented in Martín and Grossmann.1 The production cost results in 0.08€/L. The investment required for such a facility is 134M€. Thus, the investment cost is 30% lower as well as the biofuels production cost. Conclusions In this paper we have optimized an integrated facility to use renewable sources, algae and switchgrass, for the sustainable production of biodiesel, FAME. We obtain the oil from algae and the methanol from switchgrass. We formulate the problem as an MINLP to evaluate the optimal integrated topology among the alternatives for switchgrass processing, (gasification, reforming, composition adjustment) and biodiesel synthesis. The best integrated flowsheet involves indirect gasification, steam reforming and the need to generate more hydrogen to meet the requirements on the methanol synthesis reactor. The system suggests to fully use of the available biomass, and thus, only a small fraction of the methanol produced is used within the facility while the rest can be sold. For a plant of 776ML/yr (205 Mgal/yr) of biofuels, 261 ML/yr (69Mgal/yr) of biodiesel, the investment cost is 180 M€ and the production cost of biodiesel is 0.53€/gal (0.14€/L).

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The comparison with the production of methanol from CO2 and electrolytic hydrogen results in the need for a far larger investment compared to the facility evaluated in this work. Furthermore, by using switchgrass and algae, the production capacity of biofuels is almost 5 times, reducing the production costs by one half. Nomeclature Cp: Constant heat capacity (kJ/kg ºC) CO2: Cost of oxygen 0.021 €/kg CE: Cost of electricity 0.06€/kWh CsteamHP: Cost of high pressure steam (0.019 €/kg) CsteamLP: Cost of Low pressure steam, (0.0077 €/kg) k: Polytropic coefficient. kp: Equilibrium constants f(i): Mass flow rate of species i (kg/s) MW Molecular weight (kg/kmol) Pi : Partial pressure of component i (kPa) T: Temperature (ºC) Q(unit): Thermal energy flow in unit (kW) W(unit): Electric power in unit (kW) λ: Latent heat (kJ/kg) Z: Objective function (€/s) Acknowledgment The authors appreciate Salamanca Research for software licenses and the CAPD center. References [1]Martín, M.; Grossmann, I.E.. Optimal engineered algae composition for the integrated simultaneous production of bioethanol and biodiesel AIChE J. 2013, 59 (8)m 2872–2883 [2] Martín, M.; Grossmann, I.E. ASI: Towards the optimal integrated production of biodiesel with internal recycling of methanol produced from glycerol. Environ. Prog. & Sust. Energ. 2013, 32 (4), 791-801 [3] Trudewind, C.A.; Schreiber, A.; Haumann, D. Photocatalytic methanol and methane production using captured CO2 from coal power plants. Part I a Life Cycle Assessment. J. Clean. Prod. 2014, 70, 27-37 [4]Trudewind, C.A.; Schreiber, A.; Haumann, D. Photocatalytic methanol and methane production using captured CO2 from coal power plants. Part II – Well-to-Wheel analysis on fuels for passenger transportation services, J. Clean. Prod. 2014, 70, 38-49 [5] Van-Dal, E.S.; Bouallou, C. Design and simulation of a methanol production plant from CO2 hydrogenation. J. Clean. Prod. 2013; 57, 38-45. [6] Martín, M.; Grossmann, I.E. Optimal integration of a self sustained algae based facility with solar and/or wind energy. Submitted Energy, 2016. [7] Peduzzi, E.; Tock , L.; Boissonnet, G.; Maréchal, F. Thermo-economic evaluation and optimization of the thermo-chemical conversion of biomass into methanol. Energy 2013, 58, 9-16

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[8] Holmgren, K.M.; Berntsson, T.; Andersson, E.; Rydberg, T. System aspects of biomass gasification with methanol synthesis process concepts and energy analysis Energy, 2012. 45 (1), 817–828 [9] Phillips, S.D:, Tarud, J.K.; Biddy, M.J.; Dutta A. Gasoline from Wood via Integrated Gasification, Synthesis, and Methanol-to- Gasoline Technologies NREL/TP-5100-47594 January 2011 [10] Pate, R. Biofuels and the Energy-Water Nexus AAAS/SWARM April 11, 2008 Albuquerque, NM. 2008 [11] Sazdanoff, N. Modeling and Simulation of the Algae to Biodiesel Fuel Cycle. Undegraduate Thesis. The Ohio State University, Columbus, OH, 2006. [12] Martín, M.; Grossmann, I.E. Simultaneous optimization and heat integration for biodiesel production from cooking oil and algae. Ind. Eng. Chem Res. 2012, 51 (23), 7998–8014 [13] Martín, M.; Grossmann, I.E. Energy optimization of lignocellulosic bioethanol production via gasification AIChE J. 2011, 57(12),3408- 3428. [14] Vidal, M.; Martín, M. Optimal coupling of a biomass based polygeneration system with a concentrated solar power facility for the constant production of electricity over a year . Comp. Chem. Eng., 2015, 71, 273283 [15] Biegler, L.T.; Grossmann, I.E.; Westerberg, A.W. Systematic Methods of Chemical Process Design, New Jersey: Prentice Hall, 1997. [16] Eggeman, T. Updated Correlations for GTI Gasifier – WDYLD8. Technical memorandum for Pam Spath, National Renewable Energy Laboratory, Golden, Colorado. June 27, 2005. [17] Zhu, Y.; Gerber, M.A.; Jones, S.B.; Stevens, D.J. Analysis of the effects of compositional and configurational assumptions on product costs for the thermochemical conversion of lignocellulosic biomass to mixed alcohols- FY 2007 Progress Report. U.S. DOE. PNNL 17949, 2009 [18] Brenes, M.D. Biomass and bioenergy Nova Science Publishers, Incorporated ISBN-13: 9781594548659, 2006 [19] Vernon, P.D.F.; Green, M.L.H.; Cheetham, A.K.; Ashcroft, AT. (1990) Partial oxidation of methane to synthesis gas. Catalysis Letters, 1990, 6 (2), 181-186 [20] Deutschmann, O.; Schmidt, L.D. Two-dimensional modeling of partial oxidation of methane on rhodium in a short contact time reactor Twenty-Seventh Symposium (International) on Combustion/The Combustion Institute, 2283–2291 [21] Olofsson. I.; Nordin, A.; Söderlind, U. Initial Review and Evaluation of Process Technologies and Systems Suitable for Cost-Efficient Medium-Scale Gasification for Biomass to Liquid Fuels Ingemar ISSN 1653-0551 ETPC Report 05-02 [22] Martelli, E.; Kreutz, T.; Consonni, S. Comparison of coal IGCC with and without CO2 capture and storage: Shell gasification with standard vs. partial water quench. Energy Procedia, 2009, 1, 607–614. [23] Killmeyer, R.; Rothenberger, K.; Howard, B.; Ciocco, M.; Morreale, B.; Enick, R., Bustamante, F. Water-Gas Shift Membrane Reactor Studies Hydrogen, Fuel Cells, and Infrastructure Technologies FY 2003 Progress Report 2003 http://www1.eere.energy.gov/hydrogenandfuelcells/pdfs/iia9_killmeyer.pdf. (last accessed February 2013) [24] Roh, H-S.; Lee, D.K.; Koo, K.Y., Jung, U.H., Yoon, W.L. Natural gas steam reforming for hydrogen production over metal monolith catalyst with efficient heat-transfer. Int J Hydrogen. 2010; 35 (3), 1613-1619

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[33] Almena, A. Martín, M . Techno-economic analysis of the production of epiclorhidrin from glycerol. Ind. Eng. Chem. Res., 2016, 55 (12) , 3226-3238 [34] Matche http://www.matche.com/prod03.htm (last accessed Feb. 2014).

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Figure 1.- Integration of switchgrass and algae for the production of methanol and biodiesel. Figure 1 130x68mm (300 x 300 DPI)

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Figure 2.- Algae oil production Figure 2 150x65mm (300 x 300 DPI)

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Figure 3.-Oil transesterification. Figure 3 199x107mm (300 x 300 DPI)

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Figure 4.- Methanol synthesis section Figure 4 119x68mm (300 x 300 DPI)

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Figure 5.- Relative objective function (F stands for Ferco, R Renugas, S Steam reforming and O, partial oxidation) Figure 5 90x55mm (300 x 300 DPI)

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Figure 6.- Breakdown of production costs Figure 6 90x46mm (300 x 300 DPI)

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Figure 7.- Share of the different sections to the equipment cost Figure 7 90x48mm (300 x 300 DPI)

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Optimal integration of algae – switchgrass facility for the production of methanol and biodiesel . Mariano Martín, Ignacio E. Grossmann . An integrated process that uses switchgrass, to obtain methanol, and algae for the production of fully renewable biodiesel TOC 69x33mm (300 x 300 DPI)

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