Alternatives for Micropower Generation Processes - American

Currently, the predominant technologies for autonomous portable power supply are ... micropower generation processes based on a process superstructure...
0 downloads 0 Views 169KB Size
74

Ind. Eng. Chem. Res. 2004, 43, 74-84

Alternatives for Micropower Generation Processes Alexander Mitsos, Ignasi Palou-Rivera,† and Paul I. Barton* Department of Chemical Engineering, Massachusetts Institute of Technology, 66-464, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139

Currently, the predominant technologies for autonomous portable power supply are batteries. Alternatives in the range 0.1-10 W are explored in this work, focusing on the combination of fuel processing with fuel cells. A methodology for the comparison of different alternatives for micropower generation processes based on a process superstructure, including hundreds of different designs, is formulated, and the first implementations of system simulation are presented. A comparison between a variety of processes under different constraints is presented, and the influence of heat losses, scale, fuel cell efficiency, and conversion as well as recycling on the performance of the processes is discussed. Conditions under which the technologies considered are a promising alternative to batteries are identified. Introduction The widespread use of portable electric and electronic devices increases the need for efficient autonomous man-portable power supplies.1,2 Portability limits the mass of the power generation system to a few kilograms and the volume to a few liters at most and consequently to power supplies of up to 50 W. Currently, batteries are the predominant technology in most applications. However, batteries have a large environmental impact, high cost, and relatively low gravimetric (Wh/kg) and volumetric (Wh/L) energy density. State-of-the-art primary batteries reach up to 1300 Wh/L and 700 Wh/kg and rechargeable batteries reach up to 400 Wh/L and 300 Wh/kg3,4, and the upper limit on performance is now being reached as most of the materials that are practical for use as active materials in batteries have already been investigated and the list of unexplored materials is being depleted.2,3 Many alternatives are in theory possible, such as electrochemical conversion of fuels in fuel cells, thermophotovoltaic cells,5,6 a microturbine driving a generator,7 or even exploiting nuclear power, e.g., with thermoelectrical elements.8 The electrochemical conversion of common fuels and chemicals, such as hydrocarbons or alcohols, in fuel cells has the potential to yield much higher energy densities than state-of-the-art batteries, provided that the power generation equipment can be miniaturized to such an extent that the weight/volume of the fuel dominates. This approach is very promising because on one hand the above-mentioned fuels have very high energy contents (Figure 1) and on the other hand fuel cells can in principle achieve very high efficiencies. Direct fuel cells running on methanol, formic acid, or medium-sized hydrocarbons are currently associated with many technological problems including coking, low catalytic activity, fuel crossover, and polarization losses.9,10 An alternative is fuel processing for hydrogen or syngas generation and subsequent oxidation of the hydrogen or syngas in a fuel cell. This paper analyses different * To whom correspondence should be addressed. Tel.: (617) 253-6526. Fax: (617) 258-5042. E-mail: [email protected], [email protected], [email protected]. † Current address: Applied Materials, 3050 Bowers Ave, Santa Clara, CA 95054.

Figure 1. Comparison of state-of-the-art batteries with theoretical energy density of fuels in a perfect fuel cell at ambient temperature, in which all the Gibbs free energy of reaction is used to produce power.

alternatives for syngas generation in combination with electrochemical conversion in fuel cells. A number of different fuels are being considered: hydrocarbons, alcohols, ammonia, as well as combinations of fuels. Fuel processing alternatives include cracking, steam reforming, oxidative reformation, and partial oxidation. To achieve portability the use of microfabricated devices, as opposed to conventional devices, is necessary. In recent years, it has become possible to fabricate many new unit operations at the microscale, and this number rises rapidly. However, only careful integration of these components can lead to a design that is competitive with existing technologies. Direct miniaturization of conventional systems is either impossible with current technology or leads to low energy densities, large parasitic losses, and large start-up times. While systematic process synthesis and design is a mature field at the macroscale, microsystems exhibit a unique set of new challenges for process systems engineering. For example, at the microscale heat losses to the environment are a critical design consideration. The portability requirement, as well as the fact that the devices need to work fully automatically without the intervention of operators, also gives rise to many design constraints and safety issues. New design tools and evaluation meth-

10.1021/ie0304917 CCC: $27.50 © 2004 American Chemical Society Published on Web 11/26/2003

Ind. Eng. Chem. Res., Vol. 43, No. 1, 2004 75

Figure 2. Process superstructure.

odologies are needed to address the challenges of microchemical systems. In larger scale power production, including the electrical car, emphasis is placed on efficient utilization of the fuel. This is because the fuel cost is of the same or higher order of magnitude as the fabrication cost of the power production system. In portable power production, the economical and ecological operating costs are insignificant compared to the fabrication costs of the systems. Typically different man-portable power generation systems are compared using the energy density of the system as a metric. The gravimetric energy density, or specific energy (Wh/kg), is expressed as the electrical energy produced per unit mass of system3 and the (volumetric) energy density (Wh/L) is defined as the electrical energy produced per unit volume of the system. Depending on the application, either of the densities is of greater importance. It is essential to define the system appropriately including the power generation devices as well as the fuel containers. In addition to high energy densities an adequate power production process must be insensitive to transportation, and ideally work under changing orientation (upside-down) as well as in a variety of ambient conditions, including low and high temperatures. Especially for military and space applications extreme ambient conditions are possible, such as immersed in water or vacuum. Since most power consuming devices are not operated constantly and have rapidly changing power demands, the dynamics and automated operation of portable power production are very important. The processes must operate fully autonomously, automatically, and without any safety concerns, such as the use or generation of toxic or dangerous materials. It is paramount in computing energy density to have a process that operates independently of external heat sources, despite, for example, the use of endothermic fuel processing reactions. For most applications the life cycle price is a serious consideration, especially for devices with relatively high power consumption, such as portable computers. The life cycle price includes manufacturing and refueling or recharging and eventual disposal/recycling of devices. Because of the widespread use of portable power production its environmental impact is substantial. In contrast to the macroscale, the impact is not associated with the power production per se, but rather with the materials used in devices and the fabrication and recycle/disposal processes. From a

consumer point of view, the process must have a relatively simple way of recharging, refueling, or replacing. In this work, a superstructure of possible processes for portable power generation by electrochemical conversion of fuels is formulated and fairly detailed steadystate models of the process alternatives are constructed, including heat integration and heat losses to the environment. This methodology gives a tool for the comparison of different alternatives. Model Description Superstructure. The superstructure is a notion employed in process design that contains all the alternatives to be considered in the selection of an optimal process structure.11 An actual process design is a subset of the units and connections in the superstructure. While in the macroscale there are few limitations for process synthesis, in the microscale only relatively simple processes are possible.12,13 In this study, a superstructure (Figure 2) was formulated with the constraint that the realization of the processes is either currently possible or foreseeable in the short term future (next years). The resulting superstructure contains hundreds of different basic design alternatives that can be combined to create thousands of processes. The superstructure contains design choices, which in Figure 2 are represented with hexagons and mathematically are represented with binary (0-1) variables. The symbols used in Figure 2 are explained in Figure 6 in Appendix 1. The various units (reactor, burners, etc.) should not be interpreted in the traditional unit operation design paradigm, but rather as closely interconnected parts of an integrated process. The superstructure is only conceptual and does not include any information about the physical layout of the units. In this section the superstructure is described conceptually, while the equations used to model the units are detailed in the appendix. A basic requirement for a fuel is that it is compressible at relatively low pressures, so that it occupies a small volume. Ideally, the fuels used should be nontoxic and inherently safe, but this requirement can be relaxed by allowing fuels that pose health and safety concerns similar to chemicals used in common consumer applications. From the vast choice of fuels and chemicals ammonia, methanol, and propane/butane mixtures were chosen in this study.

76

Ind. Eng. Chem. Res., Vol. 43, No. 1, 2004

Ammonia can be thermally cracked at high temperatures producing hydrogen and nitrogen

2NH3 f N2 + 3H2 Ammonia is extremely toxic and corrosive and therefore could only be used in special applications, such as remote sensors, but it has the advantage that it does not contain any carbon and its thermal cracking does not produce carbon monoxide, which has deleterious effects on proton exchange membrane (PEM) fuel cell performance. Because of this fact, it is often regarded as a fuel alternative, and was included in our superstructure for generality. Methanol was included as a representative of the class of alcohols. Methanol is liquid at ambient conditions, but has a high vapor pressure, so that it can be easily vaporized. Methanol is flammable and overexposure can have detrimental effects on health, but the risk associated with it is comparable to chemicals in common use, such as isopropyl alcohol, which is used as rubbing alcohol. There are three idealized ways of processing methanol for syngas generation:

cracking: CH3OH f CO + 2H2 reforming: CH3OH + H2O f CO2 + 3H2 H 2O

oxidation: 2CH3OH + O2 98 2CO2 + 4H2 Methanol can be either stored as a pure component or in solution with water. Propane/butane are gaseous at ambient conditions, but can be liquefied at moderate pressures (0.99

C3H8/C4H10 reforming

1100

>0.99

CH3OH cracking

600

>0.99

CH3OH reforming CH3OH oxidation CH3OH oxidation with H2O NH3 cracking

500 500 400 900

0.93 0.95 >0.99 >0.99

1100 1600 1100 1500 600 1600 1300 1200 1000 900

0.7 >0.99 0.6 >0.99 0.01 0.98 0.73 0.65 0.8 >0.99

nonnegative (ni g 0). We are considering a total of 16 components: NH3, N2, N2O, NO, NO2, O2, H2, H2O, CO, CO2, CH3OH, CH4, C2H6, C2H4, C3H8, and C4H10. Table 1 contains the summary of the equilibrium yields for the reactions considered. For the initial mole numbers, stoichiometric mixtures with atmospheric air were used for all cases. In addition, for the methanol oxidation the effect of water presence was also studied, with a mixture of 2 mol of methanol, 1 mol of oxygen, and 4 mol of water. The yield is defined as the amount of hydrogen at equilibrium divided by the amount achieved with the idealized reaction. The study of chemical equilibria shows that the reactions considered are not significantly equilibrium limited, provided catalysts that suppress the formation of undesired components can be developed. As a consequence the inclusion of equilibrium based calculations in the reactor and fuel cell modeling would not significantly improve the quality of the models and was therefore not pursued. The chemical equilibria also show that at temperatures e 1100 K and at moderate air excess e 20% the formation of nitrogen oxides is insignificant from the perspective of mass and energy balances. As a consequence, it is legitimate not to include those components in our calculations. Case Study. In this case study, we are reporting energy density based only on the fuel mass/volume. This is done because we do not have accurate estimates of the total device sizes and because the energy density depends on the cycle time between fuel cartridge

replacement. As a rule of thumb, the size of the devices can be estimated at the worst case as equal to the fuel cartridge size. For the same reasons, the mass of the empty cartridges was not considered either. While this is a valid assumption for the liquid fuels, it is probably a bad assumption for the compressed air and oxygen. We want to emphasize that the reported results depend on the values of the parameters. The strength of our methodology is that the formulated models retain their validity for the whole range of parameters and can be used as a tool for the evaluation and comparison of the different technologies. Maximal Densities. Because in the considered processes the fuels are chemically converted to hydrogen or syngas the maximal achievable energy density can be estimated assuming atmospheric air and calculating the production of hydrogen and carbon monoxide per kilogram of the fuel or fuel/water. In Table 2 a power production of 64 Wh/(mol H2) and 71 Wh/(mol CO) is assumed and the heat of reaction ∆rH is reported for T ) 298. The maximal densities differ from the theoretical values for direct fuel cells (Figure 1), since in the processes considered the chemical potential of the fuel processing does not contribute to the power production. Comparison of Processes. In this base case a small subset of the possible process configurations is considered with conservative estimates for the operating parameters. For the partial oxidation (HC-POX) and reformation (HC-REF) of hydrocarbons an equimolar mixture of propane/butane is used with no excess of air or water in the reactor. Pure methanol is used as a fuel for all methanol processes, while the reactor inlet is pure methanol for cracking (CH3OH-CR), equimolar mixture of water and methanol for reformation (CH3OH-REF), and oxidation (CH3OH-OX), with no oxygen excess. Pure ammonia is used for the ammonia cracking (NH3-CR). The feasibility of recycling is controversial and therefore is not included in the base case. For the PEM-based processes purification of the fuel cell inlet stream is performed, with the exception of the ammonia cracking. No membrane is used for the SOFC-based processes. The values used for the operating conditions and the model parameters are summarized in Table 3. For each process, different reactor (R) and burner (B) temperatures were used. Different heat integration options were

Table 2. Ideal Energy Densities reaction

power from H2 [Wh/kg]

power from CO [Wh/kg]

total power [Wh/kg]

∆ rH [Wh/kg]

C3H8 + 1.5O2 f 3CO + 4H2 C4H10 + 2O2 f 4CO + 5H2 C3H8 + 3H2O f 3CO + 7H2 C4H10 + 4H2O f 4CO + 9H2 CH3OH f CO + 2H2 CH3OH + H2O f CO2 + 3H2 2CH3OH + O2 f 2CO2 + 4H2 2NH3 f 3H2 + N2

5630 5460 4480 4380 3960 3800 3960 5590

4770 4930 2170 2200 2230 0 0 0

10400 10400 6640 6580 6190 3800 3960 5590

-1400 -1500 1180 1390 790 275 -1670 745

Table 3. Process Parameters for the Case Study parameter

value

parameter

value

ambient temperature conversion in reactor residence time in reactor conversion in burners residence time in burners air excess in burners overall heat loss coefficient emissivity (incl view factor) air excess in fuel cell

Tamb ) 298 K ζ ) 0.9 τ ) 1 ms ζ ) 0.95 τ ) 1 ms Φ ) 1.2 U ) 3 W m-2 K-1  ) 0.2 Φ ) 1.2

power output SOFC temperature discard temperature from SOFC PEM temperature discard temperature from PEM conversion in fuel cell residence time in fuel cell efficiency of fuel cell membrane efficiency

PW ) 1 W Top ) 950 K Tout ) 750 K Top ) 410 K Tout ) 410 K ζ ) 0.8 τ ) 20 ms ηFC ) 0.7 ηM ) 0.8

Ind. Eng. Chem. Res., Vol. 43, No. 1, 2004 79 Table 4. Process Comparison for Atmospheric Air fuel

FC

TR,op

TR,out

TB,op

TB,out

[Wh/kg]

[Wh/L]

Qloss

Qex

HC-POX HC-POX HC-REF HC-REF CH3OH-CR CH3OH-CR CH3OH-REF CH3OH-REF CH3OH-OX CH3OH-OX NH3-CR

PEM SOFC PEM SOFC PEM SOFC PEM SOFC PEM SOFC PEM

1100 1100 1100 1100 600 600 500 500 400 400 900

800 1100 800 1100 500 600 500 500 400 400 700

1200 1200 1200 1200 700 1000 700 1000

900 900 900 900 700 700 600 700

1000 1200

700 900

1890 3070 1490 1740 1330 1820 1350 1160 890 930 1620

1010 1621 1070 1140 1070 1460 1160 980 770 800 990

1.0 1.7 1.2 1.7 0.6 1.1 0.5 1.2 0.5 1.5 1.0

0.1 0 0.2 0 1.2 0 0.0 0 0.5 0 0

TB,op

TB,out

[Wh/kg]

[Wh/L]

Qloss

Qex

730 990 640 840 590 910 745 740 565 580 865

130 150 120 145 115 170 170 150 144 130 170

0.8 0.5 0.9 0.7 0.6 0.5 .6 0.6 0.5 0.7 0.8

0.2 0.35 0.4 0 1.2 0.0 0.0 0.0 0.4 0.1 0.0

Table 5. Process Comparison for Compressed Oxygen fuel

FC

TR,op

TR,out

HC-POX HC-POX HC-REF HC-REF CH3OH-CR CH3OH-CR CH3OH-REF CH3OH-REF CH3OH-OX CH3OH-OX NH3-CR

PEM SOFC PEM SOFC PEM SOFC PEM SOFC PEM SOFC PEM

1100 1100 1100 1100 600 600 500 500 400 400 900

800 1100 800 1100 500 600 500 500 400 400 700

1200 1200 700 1000 700 1000

900 900 700 700 600 700

1200

900

studied and only the best energy density is reported. The reported heat losses Qloss include the heat produced in the PEM, while the heat excess Qex includes only the heat available at high temperatures. The heat excess is nonzero for processes in which the reaction exothermicity is greater than the heat losses and no burners are needed, or for processes in which the burning of waste produces more heat than needed. The results for atmospheric air with an energetic penalty for the air flow of KP ) 10 J mol-1 K-1 are summarized in Table 4. While these results depend on the numerical values of the parameters chosen, and only relatively rough estimates are available, it becomes obvious that the processes considered can lead to much higher energy densities than state-of-the-art batteries. The most promising option is partial oxidation of propane/butane in combination with an SOFC. This is due to the higher maximal achievable density of this process as well as to the fact that this is an exothermic reaction, and the heat excess of the reaction can partially compensate for the heat load. The heat losses are of the same order of magnitude as the power generation. The calculations are repeated for the case of compressed oxygen, available at 100 bar, instead of atmospheric air, and the resulting energy densities are much lower (Table 5), because the oxygen mass and volume must also be accounted for. In particular, the volumetric energy density is an order of magnitude lower, because of the significant volume that the oxygen needs. It should be noted that the gravimetric energy density is overestimated because the mass of the empty cartridges would be significant for this case. As expected, processes requiring great amounts of oxygen, such as partial oxidation of hydrocarbons are most influenced, and the differences between the processes are smaller than in the case of atmospheric air. Heat Losses and Scaling. To study the influence of scale and heat losses, the power output as well as the overall heat transfer coefficient and the emissivity were varied for the case of partial oxidation of propane/

Figure 3. Influence of heat losses and scale on the energy density.

butane with the SOFC. Varying the residence time would have a similar effect with a different dependence function. The results are shown in Figure 3. If no heat losses are taken into account, the process is invariant to scale for the considered level of model detail. Small scale (