197. inorganic-organic nano composite hybrid membrane...

4th International Conference on

Energy, Environment and Sustainable Development 2016 (EESD 2016)

197. Inorganic-Organic Nano Composite Hybrid Membrane Based on Titania and Polystyrene for High Temperature

PEM Fuel Cell

Muhammad Raza Shah, Muzammal Zulfqar, Zuhair S. Khan*

US-Pakistan Center for Advance Studies in Energy(USPCAS-E) NUST, Islamabad 44000,Pakistan E-mail address: [email protected]

Abstract

Low temperature PEM Fuel cells have limitations such as CO catalyst poisoning effect, Water and heat management, etc. These can be reduced by using high temperature PEM fuel cell (>90˚C). Therefore, it is need of hour that high temperature PEMFC must be focused. Inorganic-Organic Nano composite hybrid materials are among the top contenders to be utilized as membranes for high temperature PEMFCs. In this research, we have synthesized titania nanoparticles using TTIP precursor. For hybrid membrane, we have used polystyrene Mw 35000 and Poly (styrene-co-maleic anhydride), cumene terminated as polymers and Titanium dioxide Nano particles as inorganic filler. Wet chemistry route is used for Nano particle and hybrid membrane preparation. Synthesized membranes were characterized by using X-ray Diffraction and Scanning Electron Microscopy. The results showed that Titania based impregnated Polystyrene/PS-co-ma blend membranes exhibited good characteristics for its utilization as membrane for HTPEMFCs. © 2016 Muhammad Raza Shah, Muzammal Zulfqar, Zuhair S.Khan Selection and/or peer-review under responsibility of Energy and Environmental Engineering Research Group (EEERG), Mehran University of Engineering and Technology, Jamshoro, Pakistan. Keywords: HT-PEMFC; Hybrid membrane; Polystyrene; Nano Particles;

1. Introduction

Proton exchange membrane / polymer electrolyte membrane Fuel cell (PEMFC) is the promising fuel cell, which has application in portable devices, transport vehicles as well as in stationary power generations[1]. Power is generated in PEMFC through an electrochemical reaction in which oxygen reacts with hydrogen.

At anode: 2H2 � 4H+ + 4e-

At cathode: O2 + 4e- + 4H+ � 2H2O

Overall reaction:2H2 + O2 � 2H2O

The transfer of electron in this reaction is given an alternate path and which is collected as source of power while the H+ is passed through electrolyte membrane from anode to cathode. The membrane plays an important role, that it may let pass maximum of protons through itself while blocking the passage of electron.

Currently Nafion is used as PEMFC membrane which has high durability and operate well at temp below 90˚C, but it has some disadvantages like water and heat management, CO catalyst poisoning effect, high cost of membrane as well as Platinum Pt catalyst [2-4]

PEMFCs which can operate between 100˚C to 200˚C are known as HT-PEMFCs. HT-PEMFC can overcome above mentioned issues and it can also utilize the waste heat for cogeneration process[3].

Sample output to test PDF Combine only


Energy, Environment and Sustainable Development 2016 (EESD 2016) Advantages of HT-PEMFC[2] includes fast reaction fast reaction kinetics, where Oxygen Reduction Reaction (ORR) is slow in LT-PEMFC which results in power losses due to the over potential at cathode, but in HT-PEMFC ORR reaction rate is high which results in improved efficiency.

Carbon monoxide CO tolerance issue is a serious issue in operation of LT-PEMFC. LT-PEMFC uses Platinum catalyst, which has strong affinity for CO, thus a little amount CO can cause degradation. The CO poisoning effect decreases with increase in temp, thus HT-PEMFC can overcome this effect. Heat management is another issue with LT-PEMFC operation, as half of energy produced is heat, which require its removal continuously because such heat above operating temp causes degradation of cell and require special costly management for its removal. HT-PEMFC can overcome these issues. the increased temperature can be controlled by existing Colling systems available in vehicles or in cogeneration as well as on-board reforming facility. Water management also remain a striking issue when operating at low temp, as both gaseous as well as liquid phase of water is present at low temperature. which cause it difficult to maintain the membrane humidification level maintained for efficient process. At high temperature operation only gaseous phase of water is present thus simplifying water management.

At high temperature the simpler heat and water management along with more CO tolerance and fast reaction kinetics made possible a simpler design of flow field and thus decreasing the overall cost of cell.

Currently Research is carried to develop electrolyte membrane for HT-PEMFCs which can operate above 100˚C near 120˚C as in accordance with US department of Energy guidelines for automotive applications[1]. Different polymers as well as organic-inorganic composite membranes had been developed and studied as alternate membrane for HT-PEMFC electrolyte applications[2,5].

Research work has also been carried on polystyrene and titania interaction like polystyrene encapsulation of TiO2 nanoparticles[6] and Titania impregnation into polystyrene resulted in better mechanical properties[7],also its interaction for photo catalyst environment resulted better[8]. In this research we have synthesized cost effective novel inorganic-organic composite membrane in which polystyrene and Poly (styrene-co-maleic anhydride), cumene terminated has been selected as polymers while titania TiO2 nano particles as inorganic fillers. For structural characterization XRD has been successfully performed, morphological study of membrane has also been performed using SEM.

2. Materials and Methods

2.1. Materials

The materials used in this experiment are Polystyrene Mw 35000 and Poly (styrene-co-maleic anhydride), cumene terminated Mn 19000 from Sigma Aldrich, THF (Tetra hydro Furan) from Fisher Scientific, TTIP Titanium (IV) Isopropoxide from Sigma Aldrich.

2.2. Methodology

Wet chemistry route has been used for TiO2 nano particles as well as membranes. For synthesis of TiO2

nano particles 5ml of TTIP was slowly added into solution of 75ml ETOH, 300ml deionized water and 1ml HCL. Kept the solution on slow stirring for 48 hours at room temperature. The precipitated TiO2 was filtered and dried and after grinding it the powder were calcinated at 400˚C for 3 hours in furnace. For membrane preparation 1.5gram Polystyrene (PS) and 0.5gram PS-co-ma 10% solutions were prepared respectively in THF. After stirring for 3 hours, both solutions were mixed and kept further for 3hour at magnetic stirring. Prepared PS/PS-co-ma solution was then poured into glass petri dish and let the solvent to evaporate at room temperature. PS/PS-co-ma blend membrane was obtained by placing the petri dish in distilled water. For PS/PS-co-ma/TiO2 membrane preparation, 10% solution of Titania nano particles in THF is kept for 1-hour sonication. Mix titania solution with PS/PS-co-ma solution prepared earlier and keep it for two hours at magnetic stirring. Prepared PS/PS-co-ma solution was then poured into glass petri dish and let the THF to evaporate. Smooth composite membrane was obtained after placing Petri dish in distilled water.



Energy, Environment and Sustainable Development 2016 (EESD 2016) 3. Results and Discussion

3.1. X-Ray diffraction (XRD) analysis

XRD studies were conducted to study the crystallinity of composite membrane. Fig.1(a). shows the pattern of TiO2 Nano particles Maximum Peak for pure Titania dioxide nano particles was observed at 2#= 25.6˚ while others peaks were observed at 27˚, 37˚and 48˚. All peaks of titania nano particles were matched with PDF card # 75-1537. The broader peaks of titania is due to smaller crystallite size. Pure titania shows the tetragonal structure and anatase form. Fig.1(b) shows the pattern of composite hybrid membrane. The maximum peak for composite membrane was observed at 2# =20˚and at 2#=24.66˚. The composite hybrid membrane peak at angle 20˚ shows the polystyrene peak while that at 24.6˚ is of impregnated Titania nano particles. The composite membrane peaks were similar to the PDF card # 13-0843.

20 30 40 50 60 70

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nsit

y (a

.u)

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Fig. 1. XRD pattern of TiO2 Nanoparticle and PS/PS-co-ma/TiO2 composite membrane

3.2. Surface Morphology

Both pure and hybrid membrane were examined for morphological analysis via SEM. Morphology of Pure PS/PS-co-ma and titania doped PS/PS-co-ma has been shown in fig 2(a) and 2(b) respectively. Fine looking morphology was observed for pure PS/PS-co-ma membrane which shows smooth surface with almost no pores, thus non favourable for proton exchange purpose. On the other hand, morphology of composite membrane surface reveals that hybrid membrane has irregular morphology and Titania nano particles has been successfully impregnated. The morphology at high resolution shows very fine and dense distribution of nano sized pores in surface of composite membrane. The average pore size found to be 3-4µm. This distribution of fine pores provides a good pathway for conduction of protons throughout the electrolyte membrane between the electrodes.




Fig. 2(a): SEM morphology of PS/PS-co-ma blend membrane

Fig. 2(b) SEM morphology of PS/PS-co-ma/TiO2 composite hybrid membrane Further characterization like proton conductivity measurement and thermal stability of this membrane can also be performed which may give us more insight of its behaviour.

4. Conclusion

TiO2 nano particles and Organic-Inorganic composite hybrid electrolyte membrane for PEM fuel cell were successfully synthesized. From XRD analysis it was found that impregnation of inorganic Titania nano particles to the polystyrene blend has been done successfully. From SEM analysis it was concluded that The impregnation of titania has resulted in very fine and increased number of holes on surface of composite membrane for H+ transfer. The average hole size was found to between 3-4µm.

References

[1] D. J. Kim, M. J. Jo, and S. Y. Nam, “A review of polymer-nanocomposite electrolyte membranes for fuel cell application,” J. Ind. Eng. Chem., vol. 21, no. JANUARY 2015, pp. 36–52, 2015.

[2] Q. Li, R. He, J. O. Jensen, and N. J. Bjerrum, “Approaches and Recent Development of Polymer Electrolyte Membranes for Fuel Cells Operating above 100 ??C,” Chem. Mater., vol. 15, no. 26, pp. 4896–4915, 2003.

[3] A. Chandan, M. Hattenberger, A. El-kharouf, S. Du, A. Dhir, V. Self, B. G. Pollet, A. Ingram, and W. Bujalski, “High temperature (HT) polymer electrolyte membrane fuel cells (PEMFC) – A review,” J. Power Sources, vol. 231, no. May 2016, pp. 264–278, 2013.

[4] E. Bakangura, L. Wu, L. Ge, Z. Yang, and T. Xu, “Mixed matrix proton exchange membranes for fuel cells: state of the




art and perspectives Mixed matrix proton exchange membranes for fuel cells: state of the art and perspectives,” Prog. Polym. Sci., vol. 57, pp. 103–152, 2015.

[5] O. Savadogo, “Emerging membranes for electrochemical systems: Part II. High temperature composite membranes for polymer electrolyte fuel cell (PEFC) applications,” J. Power Sources, vol. 127, no. 1–2, pp. 135–161, 2004.

[6] Y. Rong, H. Z. Chen, G. Wu, and M. Wang, “Preparation and characterization of titanium dioxide nanoparticle/ polystyrene composites via radical polymerization,” Mater. Chem. Phys., vol. 91, no. 2–3, pp. 370–374, 2005.

[7] T. P. Selvin, J. Kuruvilla, and T. Sabu, “Mechanical properties of titanium dioxide-filled polystyrene microcomposites,” Mater. Lett., vol. 58, no. 3–4, pp. 281–289, 2004.

[8] S. Singh, P. K. Singh, and H. Mahalingam, “A novel and effective strewn polymer-supported titanium dioxide photocatalyst for environmental remediation,” J. Mater. Environ. Sci., vol. 6, no. 2, pp. 349–358, 2015.

[9] A. Mehrizad, P. Gharbani, and S. M. Tabatabii, “Synthesis of nanosized TiO2 powder by Sol-Gel method in acidic conditions,” J. Iran. Chem. Res., vol. 2, pp. 145–149, 2009.


4th International Conference on Energy, Environment and Sustainable Development 2016 (EESD 2016)

199. Investigations on Gadolinium doped Ceria (GDC) electrolyte prepared via sol-gel and co-precipitation routes

for intermediate temperature solid oxide fuel cell (IT-SOFC) applications

Muzammal Zulfqar, Muhammad Raza Shah, Zuhair S. Khan*

US-Pakistan Center for Advance Studies in Energy(USPCAS-E) NUST, Islamabad 44000,Pakistan E-mail address: [email protected]

Abstract

Yttria Stabilized Zirconia (YSZ) is the common material used as an electrolyte for high temperature solid oxide fuel cells (SOFC). Due to high operating temperature, various design issues arise. Therefore, low to intermediate temperature solid oxide fuel cells (SOFCs) are actively being developed. Ceria based materials are among the best options for intermediate temperature SOFC (500-800˚C). We have carried out successful synthesis of Gadolinium doped Ceria (GDC) electrolyte material with a formula Ce1-

xGdxO2-x/2 (x=0.15) by two different techniques namely sol-gel and co-precipitation. Both techniques have the advantages of high phase purity, homogeneity and low processing temperatures along with strong control on crystallite size. The synthesized materials were characterized by X-ray Diffraction, Scanning Electron Microscopy with EDX etc. We have detected a cubic fluorite structure for both synthesized compounds. The co-precipitation synthesis resulted in better control on crystallite size in comparison to that by sol-gel route. The average particle size was found to be in the range of 40-70 nm. The electrical conductivity of the GDC pellet was measured in the temperature range of 220-660 ˚C in air by using two probe LCR meter. GDC pellet synthesized by sol-gel method was found to has highest conductivity value of 2.17 # 10-4 S/cm at 600 ˚C with activation energy of 0.31 keV.

© 2016 “Muzammal Zulfqar, Muhammad Raza Shah, Zuhair S. Khan” Selection and/or peer-review under responsibility of Energy and Environmental Engineering Research Group (EEERG), Mehran University of Engineering and Technology, Jamshoro, Pakistan. Keywords: IT-SOFC;sol-gel;co-precipitation

1. Introduction

SOFC working at high temperature causes many issues like sealing, long start up time etc., which results in high cost and maintenance problems[1]. There is a need to synthesize a low temperature electrolyte to overcome these problems. Ceria is the best option for low to intermediate temperature SOFC electrolyte. Pure ceria has low ionic conductivity and mechanical strength[2]. But, it can be increased when it is doped with some rare earth or alkaline earth materials[3]. Among various rare earth elements reported as dopant, gadolinium is one of the most suitable dopant[4]. Conductivity value mainly depends on the ionic radius, material that has closed the ionic radius with ceria exhibit high conductivity value[5]. According to literature a smaller mismatch in size between host and dopant ion gives maximum value of conductivity[6]. A critical ionic radius for ceria is 1.038$. Gadolinium Gd3+ has the ionic radius of r3+

Gd,

VIII = 1.053$. As the Gd3+ ionic radius is very close to critical ionic radius of ceria, so GDC gives maximum value of conductivity and it is a suitable dopant for ceria[7]. GDC electrolyte prepared by solid state method showed the conductivity value of 0.1 S/cm at 1023 K and activation energy Ea of 0.9 eV[8]. Similarly GDC synthesized by a citrate-nitrate combustion method showed very promising results at low temperatures. GDC pellet sintered at 1300 ˚C had relative density of 97 % and conductivity value of 1.27 # 10-2 S/cm at 600 ˚C[9]. Numerous techniques have been used for the preparation of GDC electrolyte such as hydrothermal, conventional solid state, co-precipitation, spray and freeze drying and sol-gel[10], [11]. Among various synthesis techniques wet chemistry route mainly sol-gel and co-precipitation shows


4th International Conference on Energy, Environment and Sustainable Development 2016 (EESD 2016) very promising results with low processing temperature, homogeneity and purity[12]. The present study deals with the synthesis of GDC electrolyte by two different methods namely sol-gel and co-precipitation. The detailed analysis of morphological, structural and electrical properties of prepared GDC electrolyte was carried out.

2. Experimentation

2.1. Sol-gel method

The sample with a general formula of Ce₁₋ₓGdx O2-x/2 (x=0.15) was synthesized by sol-gel method. The precursor of cerium nitrate hexahydrate and gadolinium nitrate hexahydrate were used as starting materials. Stoichiometric amounts of Gd (NO3)3.6H2O and Ce (NO3)3.6H2O were dissolved in de-ionized water separately. Then Gd (NO3)3.6H2O was added in Ce (NO3)3.6H2O drop wise with continuous stirring. Stoichiometric amount of anhydrous citric acid was also dissolved in de-ionized water. The composition of total oxide to citric acid was 1:1. For better results, both solutions were mixed drop wise in a separate beaker with continuous stirring. To get homogenizing mixture, the sample was stirred for 10 hours. After complete mixing, the temperature was raised to 80˚C with continuous stirring to remove extra water and to form a gel. As the temperature increases, the solution become more viscous and after 4 hours a transparent gel was formed. Then put beaker in a dry place for 24 hours. Because, during aging poly-condensation continues which increase the thickness and decrease porosity[13]. The gel was then dried in an oven at 120 ˚C for several hours for complete drying. After drying, the sample was ground using agate mortar to get a fine powder. The fine powder was than calcined at 600 ˚C for 4 h.

2.2. Co-precipitation method

The ceramic electrolyte with the formula of Ce1-xGdxO2-x/2 (x=0.15) was synthesized by co-precipitation method. The precursor of Cerium nitrate hexahydrate and gadolinium nitrate hexahydrate were used. Stoichiometric amounts of gadolinium nitrate hexahydrate and cerium nitrate hexahydrate were dissolved in de-ionized water separately. The concentration of the precursor solution was 1M. Then mix both the solution in a separate beaker with continuous stirring at hot plate. After homogenizing mixing, added ammonium hydroxide drop wise in the solution with continuous stirring, until precipitation occurred. After precipitation raise the temperature to 200˚C to dry the slurry type sample with continuous stirring at hot plate. Pale yellow matter was obtained after complete drying. Then ground the sample by using agate mortar to obtain a fine powder. The fine powder was calcined at 600 ˚C for 4 hours. Crystal structure and phase formation of the calcined samples were analysed by X-ray Diffraction equipment (STOE Germany). X-ray powder diffractogram of the calcined sample was recorded using CuKα radiation (λ=1.5425$) with 2% values ranging from 20˚ to 80˚. The morphology of the samples was observed by scanning electron microscopy (JEOL Analytical SEM). The average grain size was measured from higher magnification SEM images. For conductivity measurement a pellet with a thickness of 2 mm and diameter of 10 mm was formed using a hydraulic press. The pellet was sintered at 1000 ˚C for 4 hours for conductivity measurement the pellet was sintered at 1050 ˚C for 4 hours. DC conductivity was measured by LCR meter (Wayne Kerr precision analyser 6440B) in the temperature range of 200 – 600 ˚C.

3. Results and Discussion

3.1. XRD Patterns

Fig.1 shows the XRD pattern of Gadolinium doped Ceria (GDC) powder synthesized by two different methods, namely sol-gel and co-precipitation. The XRD pattern revealed the formation of cubic Gd0.15Ce0.85O1.5 in all samples. All peaks are associated to cubic fluorite crystal structure with the space group Fm-3m (225) (PDF Card No. 75-0161). XRD peaks positioned at 2 theta values of 28.40˚, 32.95˚, 47.28˚, 56.16˚, 58.99˚, 69.32˚, 76.51˚, and 78.95˚ corresponding to (111), (200), (220), (311), (222), (400), (331) and (420) crystallographic planes, matching well according to the pattern JCPDS 75-0161. There are no other phases formed in sol-gel and co-precipitation methods. From diffractrogram, it can be seen that the intensity of (111) peak is maximum in all samples. The interplaner spacing d and lattice parameter of all samples are calculated by JADE 6.0 software. The reflection from (111) plane is used to measure the crystallite size D, calculated from the Sherrer formula

D = 0.9 # & / B # cos (%)


4th International Conference on Energy, Environment and Sustainable Development 2016 (EESD 2016) Where ‘%’ is the diffraction angle, ‘&’ is the wavelength of X-rays, and B is the full width at half maximum intensity.

Fig.1. XRD patterns of 15 mol% GDC calcined at 600 ˚C for 4h prepared by sol-gel and co-precipitation methods.

Table 1 shows the crystallite size ‘D’ of GDC prepared by both methods. From table, it can be concluded that, GDC prepared from sol-gel method has crystallite size slightly larger than that of GDC prepared by sol-gel method. There is a good agreement with SEM results of both the samples.

Table 1. Results based on XRD Method Composition Crystallite size (nm) Sol-gel Gd0.15Ce0.85O1.5 53 Co-precipitation Gd0.15Ce0.85O1.5 40

The peaks of sample prepared by co-precipitation are relatively broad as compared to sample prepared by sol-gel, due to small crystallite size. The XRD pattern showed that GDC electrolyte prepared by two different methods have same phase and structure. 3.2. Surface Morphology

Fig. 2 shows the micrographs of GDC electrolyte synthesized by sol-gel and co-precipitation. SEM micrograph shows the particles are well dispersed and in a round shape. In fig. 2a the particles prepared via sol-gel method have nearly homogeneous size distribution without definite big agglomerate. The particles prepared by co-precipitation have high rate of agglomeration, but all the particles forming agglomeration are highly uniform. The particles size ranges from 50 to 70 nm by sol-gel and from 40 to 60 by co-precipitation. So by co-precipitation method, the particles are larger, fewer and denser then by sol-gel method [14]. It can also be concluded that the Ostwald’s ripening is increased by increasing the pH of the solution [15].

(a)

(a) (b) Fig.2. SEM Images of Gd0.15Ce0.85O1.5 by sol-gel (a) and by co-precipitation (b)


4th International Conference on Energy, Environment and Sustainable Development 2016 (EESD 2016) Fig. 2 shows the EDS analysis of the prepared samples. There is no other element found in EDS analysis except O, Ce and Gd. The intense peaks of Gd, Ce and O are present, which confirms the purity of GDC powders. The atomic percentage of cerium and gadolinium are higher in the sample prepared by co-precipitation method as shown in Fig. 3(a, b). 3.3 DC Conductivity Measurement: The DC conductivity was measured by two probe method with LCR meter (Wayne Kerr precision analyser 6440B) in the temperature range of 200 – 600 ˚C. Fig.4. shows the typical Arrhenius plots of ln ('T) versus 1000/T. The changes in dc conductivity calculated from the bulk resistance and sample dimensions with temperature. The dc conductivity obeys the Arrhenius behaviour

'dc = 'o exp (- Ea / kT) Where k is the Boltzmann’s constant, T is the absolute temperature, 'o is the pre-exponential factor and Ea is the activation energy [13].

(a) (b)

Fig.3. EDS spectra of Gd0.15Ce0.85O1.5 by sol-gel (a) and by co-precipitation (b)

Conductivity curve of both the samples consist of two linear parts. Initially the conductivity value is very low form 200 to 280 ˚C in the sample prepared by co-precipitation method. At 280 ˚C, the conductivity value becomes higher.

1.0 1.2 1.4 1.6 1.8 2.0 2.2

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ln ( σ

T) (S

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Fig.4. DC conductivity curves of Gd0.15Ce0.85O1.5 by sol-gel (a) and by co-precipitation (b)

because the electrons move fast due to low resistance. After 280 to 600 ˚C, the conductivity curve is almost linear and it increases with the temperature increases. Similarly, GDC prepared by sol-gel method

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4th International Conference on Energy, Environment and Sustainable Development 2016 (EESD 2016) showed very low conductivity from 200 to 240 ˚C and from 240 to 600 ˚C the conductivity curve is almost linear. GDC prepared by sol-gel method showed the conductivity value of 2.17 # 10-4 (S/cm) at 600 ˚C with activation energy Ea value of 0.31 keV. And GDC prepared by co-precipitation showed the conductivity value of 1.03 # 10-4 (S/cm) at 600 ˚C with activation energy of 0.36 keV slightly lower than by sol-gel method.

4. Conclusion

GDC electrolyte was successfully synthesized by sol-gel and co-precipitation methods. It was found that both the prepared samples have single phase with cubic fluorite structure. The co-precipitation synthesis resulted in better control on crystallite size in comparison to that by sol-gel route. DC conductivity results showed that GDC prepared by sol-gel method has slightly higher value of conductivity and lower activation energy.

Acknowledgement:

The authors would like to thank School of Chemical and Materials Engineering (SCME), National University of Science and Technology (NUST) Islamabad and COMSATS for their support in carrying out the experiments. References [1] N. Mahato, A. Banerjee, A. Gupta, S. Omar, and K. Balani, “Progress in material selection for solid oxide fuel cell

technology: A review,” Prog. Mater. Sci., vol. 72, pp. 141–337, 2015. [2] M. Mogensen, N. M. Sammes, and G. A. Tompsett, “Physical, chemical and electrochemical properties of pure and

doped ceria,” Solid State Ionics, vol. 129, no. 1, pp. 63–94, 2000. [3] V. V Kharton, “Ceria-based materials for solid oxide fuel cells,” vol. 6, pp. 1105–1117, 2001. [4] E. For, I. Temperature, S. Oxide, and F. Cells, “) and grain boundary (D,” 2015. [5] S. (Rob) Hui, J. Roller, S. Yick, X. Zhang, C. Decès-Petit, Y. Xie, R. Maric, and D. Ghosh, “A brief review of the ionic

conductivity enhancement for selected oxide electrolytes,” J. Power Sources, vol. 172, no. 2, pp. 493–502, 2007. [6] S. Omar, E. D. Wachsman, and J. C. Nino, “A co-doping approach towards enhanced ionic conductivity in fluorite-based

electrolytes,” Solid State Ionics, vol. 177, no. 35–36, pp. 3199–3203, 2006. [7] M. G. Chourashiya, J. Y. Patil, S. H. Pawar, and L. D. Jadhav, “Studies on structural, morphological and electrical

properties of Ce1-xGdxO2-(x/2),” Mater. Chem. Phys., vol. 109, no. 1, pp. 39–44, 2008. [8] X. Li, Z. Feng, J. Lu, F. Wang, M. Xue, and G. Shao, “Synthesis and electrical properties of Ce 1-xGd xO 2-x/2 (x =

0.05-0.3) solid solutions prepared by a citrate-nitrate combustion method,” Ceram. Int., vol. 38, no. 4, pp. 3203–3207, 2012.

[9] C. Veranitisagul, A. Kaewvilai, W. Wattanathana, N. Koonsaeng, E. Traversa, and A. Laobuthee, “Electrolyte materials for solid oxide fuel cells derived from metal complexes: Gadolinia-doped ceria,” Ceram. Int., vol. 38, no. 3, pp. 2403–2409, 2012.

[10] F. Aydin, I. Demir, and M. Dursun, “Engineering Science and Technology , an International Journal Effect of grinding time of synthesized gadolinium doped ceria ( GDC 10 ) powders on the performance of solid oxide fuel cell,” Eng. Sci. Technol. an Int. J., vol. 17, no. 1, pp. 25–29, 2014.

[11] D. Wattanasiriwech and S. Wattanasiriwech, “Effects of Fuel Contents and Surface Modification on the Sol-gel Combustion Ce0.9 Gd0.1O1.95 Nanopowder,” Energy Procedia, vol. 34, pp. 524–533, 2013.

[12] L. Fan, C. Wang, M. Chen, and B. Zhu, “Recent development of ceria-based (nano)composite materials for low temperature ceramic fuel cells and electrolyte-free fuel cells,” J. Power Sources, vol. 234, pp. 154–174, 2013.

[13] L. L. Hench and J. K. West, “The sol-gel process,” Chem. Rev., vol. 90, no. 1, pp. 33–72, 1990. [14] C. Frayret, A. Villesuzanne, M. Pouchard, and S. Matar, “Density functional theory calculations on microscopic aspects

of oxygen diffusion in ceria-based materials,” Int. J. Quantum Chem., vol. 101, no. 6, pp. 826–839, 2005. [15] J. L. M. Rupp, E. Fabbri, D. Marrocchelli, J. W. Han, D. Chen, E. Traversa, H. L. Tuller, and B. Yildiz, “Scalable

oxygen-ion transport kinetics in metal-oxide films: Impact of thermally induced lattice compaction in acceptor doped ceria films,” Adv. Funct. Mater., vol. 24, no. 11, pp. 1562–1574, 2014.


4thInternationalConferenceonEnergy,EnvironmentandSustainableDevelopment2016(EESD2016)

The impact of using hydrogen to upgrade pyrolysis oils

Diana N. Vienescua, Prof Dr Jian Wanga, Dr Adam Le-Gresleya, and Dr Jonathan D. Nixonb* a Kingston University, Friars Avenue, London, SW15 3DW, UK

b Coventry University, Priory Street Coventry, CV1 5FB, UK

Abstract

This study aimed to investigate the hydrogen requirements and environmental impacts for producing synthetic transportation fuels via pyrolysis and different upgrading pathways. Several life cycle assessment (LCA) models consisting of biomass collection, transportation, pre-treatment, processing and upgrading were defined and analysed in GaBi ecoinvent®. The pyrolysis oil upgrading methods included esterification, ketonisation, single-stage hydotreating, two-stage hydrotreating and hydrocracking. Furthermore, the most optimistic scenarios were evaluated, and alternative sources of hydrogen were considered: hydrogen obtained from an external source, through steam reforming 50% of the bio-oil aqueous phase and steam reforming 100% of the bio-oil aqueous phase. Single-stage hydrotreating and two-stage hydrotreating contributed between 18.8-32.2% and 28.3-45.5%, respectively, to the total CO2 equivalent emissions. However, two-stage hydrotreating reduced the oxygen content by a further 18-25%. The hydrocracking process contributed 6-15% to the total CO2 emissions. For the entire pyrolysis oil upgrading process, 12-24% of the total environmental impact resulted from the use of hydrogen. It was found that the hydrogen GWP emissions ranged from 840 to 1110 gCO2/kg of upgraded pyrolysis oil produced. In the most optimistic scenario, the CO2 emissions caused by hydrotreating were decreased by up to 26.5% for single-stage processing and up to 36.6% for a two-stage process. In terms of different hydrogen sources, it was found that the energy requirement for producing hydrogen internally from the aqueous phase of the pyrolysis oil through steam reforming was between 33.7% to 40.1% higher. Total CO2 emissions were 19.9-27.8% higher when producing hydrogen only for the upgrading process, and over 50% higher when co-producing hydrogen. To obtain synthetic transportation fuels from upgrading pyrolysis oils, the total CO2 emissions are expected to range from 3510 - 9650 gCO2/kg of biofuel. In comparison, the emissions for producing diesel are 4230 gCO2/kg. Therefore, as more and more companies seek to commercialise the production of synthetic transportation fuel, great care must be taken to ensure that environmental gains over convention fossil fuels are being achieved. Determining a trade-off between GHG emissions, cost and product quality has to be carried out in further work.

© 2016 "Insert names of Authors here." Selection and/or peer-review under responsibility of Energy and Environmental Engineering Research Group (EEERG), Mehran University of Engineering and Technology, Jamshoro, Pakistan. Keywords: biofuel; synthetic fuel; sustainable technologies; environmental impact.

1. Introduction

Most biofuels currently used for the transportation industry are derived from food crops or crops that require vast

* Corresponding author. Tel.: +44-02477653135 / +44-7879020701; fax: +0-000-000-0000 . E-mail address: [email protected] (Please check)



expanses of land; this has raised fears of increasing food prices and causing food shortages. The second-generation of biofuels are obtained from agricultural residues, grasses and other waste feedstock, and are considered to be more sustainable and environmentally friendly. However, producing second-generation biofuels can be challenging as it involves complex and energy intensive conversion processes. The research in producing sustainable transportation fuels from second-generation biofuels is rather limited. A significant number of studies research the thermochemical process for converting waste biomass bio-oil via pyrolysis, but just a few researches the upgrading pathway of pyrolysis bio-oils into viable transportation fuels. Highly oxygenated, unstable and acidic bio-oils have to be improved before they can be used as transportation fuels. There are various upgrading methods which are being investigated to improve pyrolysis oils, but in order to be sustainable it has to offer environmental benefits in comparison to conventional fossil fuels. The environmental impact of converting waste biomass into bio-oil from the pyrolysis process, and obtaining biofuels from different upgrading pathways, can be analysed by conducting life cycle assessments (LCA).

Several authors have used LCA to investigate the environmental impacts of producing fuels from pyrolysis. Irribaren et al. [1] conducted a life cycle assessment of pyrolysis of poplar followed by hydrotreating, and found that over 40% of the total CO2 emissions result from using steam reforming to obtain hydrogen. Peters et al. [2] simulated a pyrolysis plant and biorefinery (hydrotreating, hydrocracking, distillation and steam reforming) for fast pyrolysis of hybrid poplar and hydroupgrading. It was found that the energy demand from steam reforming natural gas was 30% from the total energy demand of producing an upgraded biofuels. Reducing electricity consumption was considered one of the key factors in reducing the overall environmental impact. Swan et al. [3] looked into biomass conversion to biofuels through pyrolysis and upgrading (hydrotreatment and hydrocracking) where hydrogen was produced through steam reforming; the conversion accounted for 63% from the total CO2 emissions for hybrid poplar and 72% for forest residue. Electricity was considered the main contributor to the conversion process, so the study focused on reducing the electricity consumption. Hsu et al. [4] conducted a life cycle assessment of gasoline and diesel produced through fast pyrolysis and hydroprocessing; it showed that hydroprocessing highly contributed to the total CO2 emissions: around 55% in diesel production and 60% in gasoline production. Dang et al. [5] carried out a life cycle assessment of bio-fuel production from corn stover feedstock focusing on the GHC impact, but the study did not consider the contribution of each process to the total environmental impact. These studies show that there has been a tendency to focus on considering pyrolysis with hydrotreating [1-5]. Only a few take into consideration hydrocracking or other upgrading methods [2,3]. However, the structural complexity of lignocellulosic bio-oil requires a synergy of technologies to upgrade bio-oils into synthetic fuels. Therefore, this study, aims to analyse the environmental impacts of the main emerging combinations of pyrolysis and upgrading methods to obtaining sustainable transportation fuels from pyrolysis. This will enable a combination of upgrading methods which give good fuel yields and quality, whilst offering sustainable environmental impacts in comparison to fossil fuels.

2. Materials and methods

Various bio-oil upgrading methods were reviewed to identify the most promising combination of processes, resulting in six possible scenarios to be analysed and compared in terms of their environmental impact. Life cycle assessment of each scenario was conducted conforming to ISO14040 and ISO14044 standards [6]. GaBi Professional software and Ecoinvent database were used to perform the LCA analysis. The study considers the inputs of materials, energy and resources at each stage from collection of the waste feedstock to biofuel production and distribution.

The inventory data for each stage is outlined and any assumptions are explicitly stated. Where possible, along with the most commonly reported values, optimistic values have been obtained from the literature. The impacts associated with electricity and transport have been taken from Ecoinvent and GaBi databases, and correlated with inventory data. This enabled the most likely values to be obtained in terms of the global warming potential (GWP) for each stage.

To enable the different upgrading scenarios to be compared, the same feedstock (corn stover) was taken into consideration, and the pyrolysis processing technology has been considered throughout. Corn stover was used in this study, as it has been considered as a suitable waste feedstock in a range of life cycle assessment studies [5,7]. For the pyrolysis process, the fluidised bed reactor was considered as it is a popular option due to its ease of operation, stability and high oil yields [8]. To investigate the alternative options for sourcing hydrogen, each scenario was modelled for hydrogen obtained from steam reforming of methane, 50% of the bio-oil aqueous phase. Steam reforming of 100% of the bio-oil aqueous phase which resulted in hydrogen co-production was not considered for this study.



3. Definition of the bio-oil upgrading case scenarios

Pyrolysis bio-oil can be upgraded into biofuels using a number of physical and chemical methods [9]. However, this study focuses on the pyrolysis process and catalytic and chemical upgrading methods: hydrotreating, hydrocracking, esterification and ketonisation; the physical upgrading is assumed to be incorporated in the pyrolysis process, and gasification with Fischer-Tropsch is considered beyond the scope of this study. Hydrotreating involves the use of hydrogen and catalysts to reduce levels of oxygen, sulphur and nitrogen. The oxygen level is reduced by rejecting it as water through a catalytic reaction with hydrogen, and the process takes place at relatively low temperatures (150oC – 400oC). This process is also referred to as hydrodeoxygenation. Hydrotreated oil can be hydrocracked to break carbon-carbon bonds to produce shorter-chain hydrocarbons, which are more suitable as fuels [10]. To obtain higher degrees of hydrodeoxygenation, two-stage hydrotreating processes can be used. In two-stage hydrotreatment, mild hydrotreating is followed by a more severe hydrotreating step. Single stage-hydrotreating can generate a tar-like product, but two-stage processing overcomes the reactivity of the bio-oil. A promising process for improving bio-oil quality prior to hydrotreating, is esterification. This process reduces acidity and oxygen content of the bio-oil, thus improving the stability. Esterification reduces the acid concentration through neutralising the carboxylic acids in bio-oil [11]. Another upgrading method is ketonisation, which is a condensation reaction that enables the partial reduction of oxygen in form of water [11]. Ketonisation transforms two carboxylic acids into ketone, carbon dioxide and water [12]. Ketonisation also increases the size of the carbon chain, resulting in a more stable product with higher energy content, and prevents the smaller molecules to be eliminated in the form of light gases [13].

Based on the different upgrading methods, six upgrading scenarios are considered in this study: i) hydrotreating and hydrocracking – considered to be the minimum requirement to obtain transportation fuels [10,14]; ii) estification, hydrotreating and hydrocracking [10,11,14,15]; iii) estification, ketonisation, hydrotreating and hydrocracking [10,11,14-16]; iv) two-stage hydrotreating and hydrocracking [10,17]; v) estification, two-stage hydrotreating and hydrocracking [10,11,14,15,17]; and vi) estification, ketonisation, two-stage hydrotreating and hydrocracking [10,11,14-17]. The bio-oil upgrading scenarios to be analysed are outlined in Figure 1.

Figure 1: Alternative bio-oil upgrading scenarios to produce upgraded liquid fuels from pyrolysis

4. Inventory data

4.1. Pyrolysis oil production: Biomass production, Feedstock transport, Feedstock pre-treatment, Pyrolysis process

The LCA biomass production stage consists of biomass collection. It also includes fertilisers as phosphate, potassium oxide and nitrogen are used in cultivation. The assumption is made that the corn stover will be transported from the biomass collection point to the bio-oil production plant. A 9.3t heavy-duty truck from the ecoinvent database has been used. Pre-treatment of the feedstock prior to pyrolysis is required, and involves grinding and drying. Feedstock particle size reduction is necessary because pyrolysis Bubbling fluidized bed reactors are designed to use very small particle sizes - from 2-3 mm [18]. Grinded corn stover with a moisture of 25% is dried to a moisture of 7% [19,20]. Pyrolysis plant capacity was assumed to be of 2000 metric tons / day of dry corn stover [7,20]. Corn stover average

Scenario 6

Scenario 5

Scenario 4

Scenario 3 33 3

Scenario 2

Scenario 1

Pyrolysis

Hydrotreating Hydrocracking

Esterification Two-stage

hydrotreating Hydrocracking

Esterification B

IOFU

ELS Ketonisation

Ketonisation



LHV was considered to be 15.6 MJ/kg [5]. Pyrolysis was performed at 500oC and bio-oil yields through fast pyrolysis of corn stover ranged from 62 – 75 wt% [5,18], and up to 80% under optimised conditions [21].

4.2. Pyrolysis oil upgrading to biofuels: Esterification, Ketonisation, Hydrotreating, Hydrocracking, Transportation and distribution of biofuel

Esterification is required to reduce the bio-oil high oxygen content (20-50wt %) and acidity (pH=2.5-3). This improves the lower heating value and other proprieties, such as viscosity and corrosiveness [11,15]. Esterification was performed at temperature values between 70 - 170oC [15]. Zeolite catalyst was assumed to be used for 12 hours (2 hours and then reused for 10 hours) [11,22], and the yield of upgraded bio-oil was found to be up to 63wt% [23]. The optimum ethanol to oil ratio was assumed to be 5:1 [24]. The optimistic ethanol to oil ratio was assumed to be 3:1 [21]. Ketonisation can be performed at around 400oC [25] and the quantity of electricity required in the process was assumed to be 0.44 kWh/kg. Through ketonisation, yields of 75 - 98% [12] have been reported and an average conversion rate of 90% was assumed [26].

Hydrotreatment is required to reduce the high content of oxygen in pyrolysis oils (around 40wt%) [27] in order to upgrade them to synthetic transportation fuels. Hydrotreating can be performed either in one or two stages, and different degrees of deoxygenation can be achieved. Hydrotreatment of corn stover bio-oil can be performed using noble metal catalysts (Ru/C and Pd/C) at 125bar, 200°C or 300°C and 4 hour reaction time in a batch catalytic reactor. Results show that ruthenium can accomplish 25–26wt% deoxygenation and yields between 54–67 wt% [28]. It was also found that Ru/C for the hydrotreatment of fast pyrolysis oils at 180-240 °C and hydrogen pressures of 133-142 bar resulted in a reduction of the oxygen content from 41.3 %-wt. down to 20 - 27wt% [29]. Bio-oil yields of 30% [20], 55.6% (PNNL) [30], 40.8% (UOP) and 42% [31] have been reported. Through mild hydrotreating under Ru/C catalyst (5 wt%) at 250°C and a hydrogen pressure of 130bar for 4 h, the oxygen content is significantly decreased to 20 – 26wt% [14]. For temperatures of 250-350oC and hydrogen pressure of 100 – 200 bar, Ru/C was found to be superior to common catalysts in yield (60%wt) and deoxygenation (90wt%) [9]. The highest oil yield (65%wt) was obtained after 4h, using 5 wt% catalyst to bio-oil ratio, a temperature of 350oC and 200 bar [29]. The two-stage hydrotreating involves performing mild hydrotreating at 150-270oC, 80-100 bar, followed by moderate processing at 350-425oC, 140-200 bar [32]. Brown et al. assumed that the first-stage hydrotreatment was performed at 125oC and 100 bar pressure, by using Ru/C catalysts, while the second-stage hydrotreatment was carried out at 250oC and 100 bar pressure, by using Pt/C catalysts [10]. The total residence time for the two-stage hydrotreating ranges from 2-4 hours [32], [29]. The levels of deoxygenation for the two-stage hydrotreating tend to be 2% oxygen or less [17]. In stage one a Ru/C is used, whereas a Pt/C or NiMo catalyst is normally used in stage two. Catalyst quantities are normally around 3 - 5wt% of bio-oil, with a better performance of the catalyst loaded with 5wt% [29], and with lifetimes of around 700 - 1752 hours (Ru/C) catalyst lifetime is of one year with a value of 5 wt%) [33]. The overall yield of deoxygenated bio-oil for two stage hydrotreating is expected to range from 30% [34] to 38-44% [35], and the yield of upgraded oil is assumed to be up to 90% of first-stage hydrotreatment [34].

Hydrocracking involves cracking bio-oil into short-chain hydrocarbons in the presence of a catalyst and H2. Hydrocracking is performed at more severe condition than hydrotreating: at temperatures between 400-450oC and pressures of 100-140 bar [20]. The catalysts used in the hydrocracking process to obtain transportation biofuels were assumed to be Ni-HZSM-5 zeolites [36]. Hydrocracking is expected to produce a liquid yield up to 75% [37]; the average was assumed to be 70%.

The liquid biofuel transportation was assumed to be via trucks travelling a distance of 100-150 km/kg of biofuel. Heavy-duty truck transportation and heavy-duty truck distribution were found to be between 55 – 80 km/kg and respectively 48 - 53 km/kg [5,7].

The inventory data is summarised in Table 1.

Table 1: Inventory data for each stage of the life cycle assessment processes, including references and calculated values.



Inputs Average Optimistic Unit REF

Biomass production

Diesel used in the production of corn stover 0.22 0.219 MJ/kg of corn stover [5] [7] [38]

Phosphate 2.21 g/kg of corn stover [5] [7] [38]

Potassium oxide 13.23 g/kg of corn stover [5] [7] [38]

Nitrogen

8.5 g/kg of corn stover [5] [7] [38]

Biomass Transportation

Diesel 0.20 MJ/kg of biofuel [5]

Heavy-duty truck

75 50 km/kg of biofuel Calc.

Biomass pre-treatment

Electricity used for grinding 0.057 0.011 kWh/kg of corn stover [5] [7] [19] Electricity used for drying

0.176 0.046 kWh/kg of corn stover [5] [7] [20]

Biomass pyrolysis

Electricity used in pyrolysis

0.487 0.252 kWh/kg of corn stover [5] [7]

Esterification

Electricity used by heater 0.259 0.217 kWh/kg of bio-oil [15]Calc.

Zeolite powder 5wt% 3wt% Kg of bio-oil [11] [11,22] [23]

Ethanol

5 3 kg/kg of bio-oil [24] [21]

Ketonisation

Electricity used by heater 0.440 kWh/kg of bio-oil Calc.

Ru/TiO2/C Catalyst 5wt% kg of bio-oil [13,39]

Pd/ZrOx – ZrO2

0.25wt% kg of bio-oil [26]

One stage hydrotreating

Hydrogen consumption 74 69 g/kg of bio-oil [5,40]

Electricity consumption 0.255 0.23 kWh/kg of bio-oil [5] [7] Calc.

Ru/C (Pd/C) Catalyst

0.3 0.1 g/kg of bio-oil [14] [9] [29] [33]

Two-stage hydrotreating (mild+moderate)

Overall hydrogen consumption 69 58 g/kg of bio-oil [32] [5] [35]

Overall Electricity consumption 0.75 0.569 kWh/kg of bio-oil [1] Calc.

Ru/C Catalyst (mild stage) 0.3 0.1 g/kg of bio-oil [14] [9] [29] [33] Pt/C/ Pd/C

0.3 0.1 g/kg of bio-oil [29] [33]

Hydrocracking

Electricity used by heater 0.451 kWh/kg of bio-oil [20]

Hydrogen 0.02 0.015 kg/kg of bio-oil [41]

Zeolite powder 5wt% kg of bio-oil Calc.

Transportation and distribution of biofuel

Diesel 0.28 MJ/kg of biofuel [5]

Heavy-duty truck

150 100 km/kg of biofuel Calc.

5. Environmental results



Figure 2 shows the results obtained for scenario 1 making use of: an outside source of H2; hydrogen produced in the plant through steam reforming by using 50% of the aqueous phase bio-oil (based on [5] and H2 ratios of hydrotreating and hydrocracking); hydrogen produced through steam reforming all the aqueous phase bio-oil, in which case it also produced H2 as a co-product. To calculate the real amount of CO2 emissions from the GaBi results, the life span absorption of the corn stover was deducted. It was assumed that 1kg of corn stover can uptake during its lifespan 0.57 kgCO2 [7], and this was considered to evaluate the overall environmental impact of biofuel production from corn stover.

The results show that making use of an outside source of H2, where conventional steam reforming of methane has been performed, the CO2 emissions were lower than by using hydrogen produced in the plant through steam reforming using 50% (based on [5] and H2 ratios of hydrotreating and hydrocracking) of the aqueous phase bio-oil (Figure 2). Steam reforming of 100% of the bio-oil aqueous phase which resulted in hydrogen co-production showed a high increase in CO2 emissions and therefore was not considered for this study.

Figure 2 – Scenario 1 with different H2 sources, showing feedstock biomass, and H2 produced life span absorption

The six scenarios were simulated using the inventory data, and the results for both average and optimistic data are illustrated in Figure 3. The LCA results show that the CO2 emissions could be as high as three times more than the CO2 emissions associated with convention transportation fuels; however, favourable net emissions are achieved when considering the CO2 absorbed during plant growth. The most likely net CO2 emissions based on average values from the inventory data provide only small environmental gains (1130 – 3494 gCO2/kg) in comparison to diesel fuels; however, in the most optimistic scenario, CO2 reduction is significant ranging from 78 - 121% for scenarios 6 and 2 respectively. In all six scenarios, the mass of corn stover used for obtaining 1 kg of biofuel with internal hydrogen is approximately 20% higher than if external hydrogen was used. Also, the emissions of average scenarios increased with 19.9-27.8% when external hydrogen was used and the emissions of optimistic scenarios increased with 25-33% in optimistic scenarios when external hydrogen was used. In Average scenarios biofuel showed the overall emissions between of 3510 gCO2/ kg and 9650 gCO2/ kg of biofuel produced (Figure 3). In the optimistic Scenarios the CO2 emissions decreased by up to 48%, but the life span absorption also decreased by up to 31%. Different transportation fossil fuels can vary with 3% of the total emissions.

-4000

-2000

0

2000

4000

6000

8000

Biofuel- outsideH2 Biofuel- internalH2 Biofuel- internalH2+co-prod

gCO2/kgbiofuel

BiomassAbsorption

Transport

Bio-oilHK

Bio-oilHT

H2Production

Bio-oilProduction

BiomassPre-treatment

BiomassProduction



Figure 3 – Average and Optimistic GWP gross and net emissions for all six scenarios (with internal and external H2 sources)

Unlike previous studies, this study took into consideration the catalysts and solvents involved in the upgrading processes. The result showed that the electricity and hydrogen have the main impact on the CO2 emissions (68-87% respectively 12-24%), and catalysts contribute up to 3% to the total CO2 emissions. Bio-solvents showed a reduction in CO2 emissions of 8-9 %, and synthetic solvents showed an increase in CO2 emissions of 9-11%.

The ratios of hydrogen to the total CO2 emissions were evaluated to analyse the contribution to the total CO2 emissions of each process, as shown in Figure 4. Bio-oil Hydrotreating process had a share of 19-46% of the total CO2 emissions with single-stage hydrotreating and two-stage hydrotreating contributed between 18.8-32.2% and 28.3-45.5%, respectively, to the total CO2 equivalent emissions . In the optimistic scenarios, bio-oil hydrotreating and hydrocracking decreased by 26-37% and 33-37% respectively.

Figure 4 – Hydrogen impact on total GWP

-500

1500

3500

5500

7500

9500

11500

13500

Ext.H2

SteamRef.

Ext.H2

SteamRef.

Ext.H2

SteamRef.

Ext.H2

SteamRef.

Ext.H2

SteamRef.

Ext.H2

SteamRef.

Ext.H2

SteamRef.

Ext.H2

SteamRef.

Ext.H2

SteamRef.

Ext.H2

SteamRef.

Ext.H2

SteamRef.

Ext.H2

SteamRef.

Transp.

Av. Opt. Av. Opt. Av. Opt. Av. Opt. Av. Opt. Av. Opt.

Scenario1 Scenario2 Scenario3 Scenario4 Scenario5 Scenario6 Fuels

TotalC

limateCh

ange(g

CO2/kgbiofuel)

Lifespanabsorption

Netemissions

0

2000

4000

6000

8000

10000

12000

14000

Ext.H2

SteamRef.

Ext.H2

SteamRef.

Ext.H2

SteamRef.

Ext.H2

SteamRef.

Ext.H2

SteamRef.

Ext.H2

SteamRef.

Ext.H2

SteamRef.

Ext.H2

SteamRef.

Ext.H2

SteamRef.

Ext.H2

SteamRef.

Ext.H2

SteamRef.

Ext.H2

SteamRef.

FossilDiesel

Av. Opt. Av. Opt. Av. Opt. Av. Opt. Av. Opt. Av. Opt.

Scenario1 Scenario2 Scenario3 Scenario4 Scenario5 Scenario6 Fuel

TotalC

limateCh

ange(g

CO2/kgbiofuel)

ExternalH2ratiotogrossHT&HK H2Production Bio-oilHT Bio-oilHK Otheremissions



6. Discussion

This study aimed to investigate the hydrogen requirements and environmental impacts for producing synthetic transportation fuels via pyrolysis and different upgrading pathways. Several LCA models with upgrading processes such as esterification, ketonisation, single-stage hydotreating, two-stage hydrotreating and hydrocracking were defined and analysed. However, to draw a comparison with other LCA studies in the literature, upgrading corn stover into a fuel using only pyrolysis and hydrotreating was also considered. Using pyrolysis and hydotreating to turn corn stover into a fuel was found to release 54.74 gCO2/MJ. This is comparable with other studies with values ranging from 39.1–55 gCO2/MJ [5,7]. Similar values of 39, 54 and 34 gCO2/MJ have been obtained for hybrid poplar [2,3], wood [4] and southern pine [32]. Hydrotreating alone is not sufficient to upgrade pyrolysis oils into high quality fuels, so this study modelled six additional upgrading scenarios. The fuels obtained through pyrolysis, hydrotreating and hydrocracking (Scenario 1) showed and environmental impact was 41% higher than pyrolysis and hydrotreating.

For the six different scenarios, the total CO2 emissions ranged from 3510 to 9650 gCO2/kg of biofuel (2365 – 6156 gCO2/kg absorbed during feedstock life span). In comparison, the emissions for producing diesel are 4230 gCO2/kg. When taking into account the CO2 absorption, the gross carbon emissions were reduced by 57-109% (Figure 3). Similar findings are presented by Zhan’s [7], Iribarren et al. [1], Peters et al. [2] and Hsu [4], where the total effect of the CO2 emissions were reduced by 100 to 200% amount when considering the carbon dioxide absorbed during the feedstock’s total lifespan. In comparison with obtaining hydrogen from an external source, producing hydrogen internally was found to increase the CO2 emissions by 20% when using a steam reforming process and 53% when hydrogen was produced for both upgrading and co-production processes. Specifically, the emissions increased to 4380 - 12980 gCO2/kg (2958 – 7695 gCO2/kg considering feedstock life span). The increase in emissions can be attributed to the high energy demand for the production of hydrogen through steam reforming, as it was found that the energy requirement for producing hydrogen internally from the aqueous phase of the pyrolysis oil through steam reforming was between 33.7% to 40.1% higher than obtaining hydrogen from steam reforming of methane. Another reason for the increase in emissions is the decreased biofuel yield due to the process of producing internal hydrogen.

Figure 4 shows that that hydrogen usage (hydrotreating and hydrocracking) contributed between 45-66% of the total CO2 emissions (1670 gCO2/ kg of biofuel to 3270 gCO2/ kg of biofuel). When the hydrogen was produced internally through steam reforming, the emissions increased by up to 40% (2080 gCO2/ kg of biofuel to 5410 gCO2/ kg of biofuel) due to hydrogen production and usage (hydrotreating and hydrocracking). In the optimistic scenarios the hydrogen usage decreased with up to 37% (1190 gCO2/ kg of biofuel to 2090 gCO2/ kg of biofuel) when external hydrogen was used, and increased with up to 26% (1640 gCO2/ kg of biofuel to 3810 gCO2/ kg of biofuel) when internal produced hydrogen was used. Single-stage hydrotreating and two-stage hydrotreating contributed between 18.8-32.2% and 28.3-45.5%, respectively, to the total CO2 equivalent emissions. This is due the lower amount of hydrogen required for two-stage hydrotreatment, but also because the yields reported for two-stage hydrotreatment were also lower (see Table1). The mass of biomass required to get 1 kg of biofuel through two stage hydrotreating was 32% higher compared with single-stage hydrotreating. However, two-stage hydrotreating reduced the oxygen content by a further 18-25%. The hydrocracking process contributed 6-15% to the total CO2 emissions.It could be also noticed that the environmental impact resulted from the usage of hydrogen was between 12-24% (840 to 1110 gCO2/kg). From the total hydrogen up to 63% of the hydrogen used in the process was used in the hydrotreating process and the rest for hydrocraking.

7. Conclusions

This study investigated the global warming potential of upgrading pyrolysis oils in synthetic transportation fuels. Six alternative upgrading scenarios were considered and depending on the amount of upgrading performed, the gross GHG emissions were found to range from 3510 to 9650 gCO2/kg of upgraded bio-oil; 12-24% of the CO2 equivalent emissions were associated with the use of hydrogen. The processing stages that had the highest impact on the environment were found to be bio-oil production (up to 33%) and hydrotreating (up to 46%). Overall net emissions, which take into account CO2 absorption during feedstock lifespan, were significantly lower at 1130 to 3494 gCO2/kg. This suggests favourable CO2 emission reductions can be achieved in comparison to conventional diesel fossil fuels, which emit approximately 4300 gCO2/kg. A combination of esterification, ketonisation, two-stage hydrotreating and hydrocracking processes to upgrade pyrolysis oil’s, can still reduce CO2 emissions by as much as 82%. This value is



highly dependent on the efficiency of the individual upgrading stages and R&D needs to focus on reducing the use of electricity and hydrogen to upgrade pyrolysis oils. One option to be pursued is to use hydrogen produced internally through steam reforming; however, this could actually result in the emissions being increased by up to 26%. Further research on techno-economics will reveal if two-stage hydrotreatment, esterification and ketonisation can be sustainable in terms of costs.

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1

237. Compatibility Issues of HHO Cell With Internal Combustion Engine

Kishore Kumara, Zeeshan Alib, Javed Rahman larikb

aPostgraduate Student, Department Manufacturing Engineering,MUET Jamshoro. bFaculty Member, Department of Mechanical Engineering, MUET, Jamshoro.

Email: [email protected]

Abstract

This study presents the analysis of hydrogen (H2) gas, gasoline (octane), and their mixture using a nonlinear vehicle dynamic model. These fuels, with their corresponding A/F ratios, are used to generate the engine torque and fuel flow rates. The vehicle model is based on the continuous-time domain and simulates the real dynamics of the sub-vehicle models for steady-state and transient operations. The heat of combustion and A/F ratios for both fuels and their mixture are determined using the combustion stoichiometry and Hess’s Law. The simulation results show that the pure H2 gas generates more torque and consumes less fuel than pure octane fuel. The A/F of H2 gas is fuel-lean mixture while for octane it is fuel-rich mixture. Using the H2 gas as an additive fuel with octane (mixture of both fuels) improves the torque generation and reduces the octane consumption from 37% to 45%. These fuels are not tested on a stationary test rig but in a dynamic (moving) model which means the simulation results can be highly useful for developing the experimental model, its detailed testing, and implementation.

© 2016 “Kishore Kumar” Selection and/or peer-review under responsibility of Energy and Environmental Engineering Research Group (EEERG), Mehran University of Engineering and Technology, Jamshoro, Pakistan. Keywords: “HHO; IC-Engine; Torque; Vehicale dynamics;”

1. Introduction

It is a very well-known fact that fossil fuels are used as the source of energy for the internal combustion engines. However, due to their higher depleting rates and increasing prices, a number of researchers have dedicated their research work on investigating alternative sources of energies for the internal combustion engines. Some of the researchers have focused on the methanol and organometallic (MnO2) fuels [1], vegetable oil [2], natural gas [3], neem oil methyl ester [4], HHO gas [5-6], etc. as alternative fuels or additive fuels. Water is most abundant element on this earth and recently used as a free energy source and has been introduced to the automobile industry as a new source of energy named as Brown Gas (HHO). It is used as a supplementary fuel in petrol, diesel, CNG [7-9] engines etc. to improve the power production and to reduce the hazardous gases such as CO2, HC, NOx, CO, [10-11] etc. in the emission.

Hydrogen is widely acknowledged as a non-polluting, renewable, and recyclable fuel. The major dissimilarity between hydrocarbon fuels and hydrogen fuel is the absence of carbon. Moreover, as compared to other hydrocarbon fuels, hydrogen has greater flame speed, faster burning velocity and wider flammability limits [12]. This helps the engine to complete the combustion process and to run on very lean mixtures which results in less unburnt fuels and reduced pollutants in the emission. Hydrogen could become an important element, allowing us to accumulate and transfer energy in a clean way. Hydrogen can be used in cars as a fuel additive which increases the combustion efficiency of the fuel-air mixture. H2 gas ensures noteworthy ability as a supplemental fuel to rally the emissions and performance of SI and CI engines. Some of the characteristics which justify the use of hydrogen as fuel are as follows [12].

1.1 Wide Range of Flammability

The flammability limits are very wide for hydrogen, which ensures that by using an appropriate air-fuel ratio the engine load can be controlled. The engine can be run all time using a wide open throttle which




2

results in increased efficiency.

1.2 Low Ignition Energy

The quantity of energy required to ignite H2 gas is about one order of magnitude less than that required for gasoline. This allows H2 engines to burn lean mixtures and guarantees swift ignition.

1.3 Small Quenching Distance

Hydrogen flames travel closer to the cylinder wall than other fuels before they extinguish.

1.4 High Auto Ignition Temperature:

The high auto ignition temperature of hydrogen allows larger compression ratios to be used in a hydrogen engine than in a hydrocarbon engine.

1.5 High Flame Speed

Hydrogen has high flame speed at stoichiometric ratios. This means that hydrogen engines can more closely approach the thermodynamically ideal engine cycle.

1.6 High Diffusivity

It facilitates the formation of a uniform mixture of fuel and air.

2. Schematic Diagram of HHO Dry Cell Integration with I. C. Engine

The schematic diagram of HHO dry cell is shown in Fig. 1. It consists of a 12 volts battery connected to a 20 amperes fuse. The fuse is generally joined to a switch. An ammeter is used to determine the amount of current flowing from battery to the HHO dry cell. The negative wire is connected to the car grounding and the positive wire from the ammeter is connected to the HHO dry cell. Once the system is started then HHO is generated and fed to the carburettor with the help of a silicon pipe as shown in Fig. 1.

Fig.1. Schematic Diagram of HHO Dry Cell Integration with IC Engine

Numerous attempts have been demeanour all around the world for using hydrogen as supplementary fuel to improve combustion efficiency of engine. Y. Hacohen and E. Sher [13] found, for the operation conditions used, the brake specific fuel consumption was reduced by 10 to 20% by addition of hydrogen to gasoline mass ratio of 2 to 6%. Shrestha and Narayanan [14] proposed that under fuel-lean mixture conditions adding 3% hydrogen to a spark ignited engine running on landfill gas increased the thermal efficiency of that engine by 15.07% and the power output by 12.5%. Saravanan and Nagarajan [15] suggested that under optimized diesel engine operating conditions, addition of 7.5 liters/min of hydrogen produced a brake thermal efficiency increase of 9% as compared to normal diesel operation.




3

Core intimation of this research study is to focus on automobile industry. This research focuses on the integration of HHO (brown gas) generator and to study the problems arises during the integration of HHO gas generator with the petrol engine. There has been a rising global interest towards the HHO integration with the existing internal combustion engines. Supplementing a certain quantity of Hydrogen gas to the intake manifold of a petrol engine may decrease the consumption of fuel and can substantially improve the emissions. Continuous generation of H2 gas from water electrolysis can resolve numerous potential difficulties of using hydrogen as a supplement fuel to increase combustion of fuel. This study mainly focuses on the integration of HHO gas generator with petrol engine without any physical modification in the overall system. It is essential to figure out various factors when integrating the HHO gas generator with the petrol engine. The most important problem is to find out the air-fuel ratio of air, gasoline, and HHO gas. The vehicle cannot be analyzed by hit and trial methods to find out this air-fuel ratio. Therefore, a detailed mathematical analysis is mandatory for the appropriate solution. In order to reduce the fuel consumption it is essential to investigate that how much fuel supply should be reduced and how much HHO gas should be added to get the same torque and speed as from gasoline. Moreover, the compression ratio for this new combination and spark plug timings have not been addressed in the previous studies. These all factors should be properly addressed so the proposed HHO generator model can be utilized effectively. The bottom line of this study is to investigate the A/F ratio associated with the integration of HHO generator with the petrol engine to generate the optimum torque and its corresponding fuel consumption.

3. Aims and Objectives of the Research Study

Objective of this research is to integrate the HHO gas generator with petrol engine as a supplementary fuel, and the measureable steps under consideration to resolve these issues are as follows:

Key aims and objectives of this research include:

• Investigate the amount of gasoline and hydrogen required to acquire the same torque and speed as from gasoline.

• Determination of heat of combustion and A/F ratio of both fuels. • Determination of vehicle millage with and without of HHO generator.

In this study, a nonlinear vehicle model is tested under realistic dynamic load conditions and it is capable of finding out the required A/F ratio of any fuel for the desired power generation. The investigation of hydrogen fuel and its mixture with gasoline for a nonlinear vehicle dynamic model have not been conducted in previous studies. This study will help in understanding the impact of hydrogen gas as a supplementary fuel on the automobile industry.

4. Methodology

The HHO generator is the heart of the system that produces the HHO gas and cools down the engine. Mounting position of HHO cell is very important for smooth operation, as no any physical modification is required inside the chamber, as well as in the compartment of vehicle. After the proper placement of HHO cell, the HHO gas will be injected through the air intake manifold of the engine using the appropriate tubing, after that it would be mixed with the existing air-fuel mixture for the combustion inside the engine during power stroke of the engine cycle. It is important to mention here that existing air-fuel ratio must be altered for the complete combustion of the Hydrogen along with the existing fuel.

For the purpose of investigation, a nonlinear vehicle dynamic model has been adopted from [16] for the detailed and realistic investigations. The vehicle dynamic model includes the engine dynamics, automatic transmission dynamics, wheel dynamics, and vehicle’s longitudinal dynamics.




4

Fig. 2. Block Diagram of the Nonlinear Vehicle Dynamic Model [16]

A 3.8L spark-ignition engine model with six cylinders and a five-speed automatic transmission for a typical front-wheel-drive passenger car is used where the input to the engine model is the throttle angle (α). The engine model is used as a torque-producing device with one inertia where the engine torque is

the function of the throttle angle (α), mass flow rate of fuel ( fm& ), and the engine speed (eω ). The

vehicle model is based on the physical principles and captures the power train dynamics in the continuous-time domain. For the details of the nonlinear vehicle model the readers are referred to the PhD thesis [16].

Fig. 3. Block diagram for the Engine Model [16].

The vehicle dynamic model is very useful for the comparison of various fuels, the comparison of the torque generated by each fuel, and the fuel consumption of each fuel in the simulated environment. There are many other variables which could be measured using the same vehicle dynamic model which will be discussed in the results and discussion Section of this paper. The types of fuel used for the investigation and comparison are gasoline (Octane, C8H18) and Hydrogen (H2) gas. For the purpose of investigation, both fuels are used separately and as a mixture for the comparison purpose.

The vehicle model used requires the heat of combustion or calorific values of each fuel and its corresponding air/fuel ratio for the required torque generation. Heat of combustion is the measure of the heat released during complete combustion whereas, the air/fuel ratio defines amount of air required for the complete combustion of the fuel. Therefore, it is necessary to determine the heat of combustion and the air/fuel ratios of each fuel and their mixture.




5

5. Combustion Stoichiometry

5.1 Heat of combustion and A/F ratio of Octane and Hydrogen gas

During the complete oxidation of hydrocarbon fuels carbon dioxide (CO2) and H2O along with the heat of combustion are formed. The general chemical equation for the oxidation of a hydrocarbon fuel is as follows [17].

OHm

nCOO)m

n(HC mn 222 44+→++ (1)

Eq. (1) can be used for the computation of the heat of combustion generated during the complete oxidation of a fuel. For example, heat of combustion of Octane (C8H18) from its chemical stoichiometric equation can be determined as

OHCOOHC 222188 18162

25 +→+ (2)

Using the standard enthalpies from Table 3.2 [17], heat of combustion for C8H18 comes out as

mol/KJ.

...

).().()().(

375471

562572163148035249

842852

1852393

2

160

2

2535249

−∴−−→+−∴

−+−→+−

Since the molecular mass of one mole of C8H18 is 114 grams, therefore, there are 8.77 moles of C8H18 in one kilogram of fuel. The heat of combustion of C8H18 per kilogram is 47.98 MJ/kg. Similarly, using Eq. (1) and standard enthalpies from Table 3.2 [17] the heat of combustion of hydrogen gas per mole can be computed as -241.83 KJ/mol. Since the molecular mass of one mole of H2 is 2 grams, therefore, there are 500 moles of H2 in one kilogram of fuel. The heat of combustion of one kilogram of H2 is 120.1 MJ/kg.

Eq. (1) can be used for finding out the heat of combustion of any fuel and it uses pure oxygen for the complete combustion. Since air is composed of N2 (79.1%), O2 (20.9), and small amounts of other gases, therefore, for the purpose of this study it is perfectly reasonable to consider as a mixture of nitrogen and oxygen in mole basis. As per this percentage, for every one mole of oxygen required for combustion, 3.78 mol of nitrogen must be introduced as well. Under this condition the Eq. (1) can be revised as

22222 4783

2783

4N)

mn(.OH

mnCO)N.O)(

mn(HC mn +++→+++ (3)

Using Eq. (3) for the C8H18, we get

22222188 254798783512 N.OHCO)N.O(.HC ++→++ (4)

It is obvious from Eq. (4) that for each mole of C8H18 burned, 59.75 mol of air is required for the complete combustion. The air/fuel ratio for C8H18 can be computed as

115114

2878332512.

).(.

m

m

f

a =×+×=

Similarly, the air/fuel ratio for H2 can be computed as 34.46. The calorific values and air/fuel ratios of both fuels are used to simulate the response of the nonlinear vehicle dynamic model.

5.2 Heat of combustion and A/F ratio of the mixture of Octane and Hydrogen gas

One of the objectives of this study is to determine the heat of combustion and A/F ratio of the mixture of both fuels, i.e. octane and hydrogen gas. It should be noted that Eq. (3) cannot be simply used for to find out the heat of combustion and A/F ratio of the mixture of both fuels. Since both fuels are mixed for the combustion and in turn for the power generation of the engine, therefore, according to the Hess’s Law the




6

chemical equation of both fuels should be added to compute the heat of combustion and A/F ratio of their mixture as follows.

22222188 2547778977887787832

25778778 N..OH.CO.)N.O(.HC. ×+×+×→+×+ (5)

22222 88715005007832

500500 N.OH)N.O(H ×+→++ (6)

Adding above two equations we get

222222188 88251357935781670783625359500778 N.OH.CO.)N.O(.HHC. ++→+++

(7)

2500114778

2878332625359

×+××+=

.

).(.

m

m

f

a

2000

7149570.=

785324.m

m

f

a = A/F ratio

According to the Hess’s Law, when two chemical equations are combined algebraically then their heat of enthalpies can be added algebraically. Since both reactions in Eq. (5) and Eq. (6) are exothermic, therefore, their heat of combustion will be added. The total heat of combustion of both fuels determined as 168.08 MJ/kg.

6. Simulations Results and Discussion

This section presents the simulation results of the nonlinear vehicle model for octane fuel, hydrogen gas, and their mixture. The required calorific values and their corresponding A/F ratios are used for the nonlinear vehicle model. The objectives of these simulation results are to investigate the response of vehicle model for H2 gas separately and then its mixture with octane fuel. These results will be then compared with the simulation results of the vehicle model when running on pure octane fuel. The aim of this comparison is to find the differences in torque generated and the fuel consumption in all conditions. For the purpose of comparison, the nonlinear vehicle model is tested for various cases as follows.

• Pure H2 gas with its actual stoichiometric A/F ratio, i.e. 34.46.

• Pure Octane fuel with its actual stoichiometric A/F ratio, i.e. 15.1.

• Pure H2 gas with the A/F ratio to be computed to generate the same torque as for pure octane in case 2. This will help to find the required A/F ratio and H2 flow rate for the required torque generation.

• The mixture of H2 and octane fuel with their correspondent A/F ratio computed using the Hess’s Law.

Table 1 shows the vehicle and power train parameters used for these simulations. The initial velocity of the vehicle is 10m/s. The corresponding initial engine speed, throttle input, and gear ratio for the vehicle model are 1967 rpm, 70◦, 2nd gear respectively.

The vehicle response has been simulated in Fig. 4 which shows the (a) engine speed, (b) engine torque, (c) fuel flow rate, (d) gear shifting pattern, (e) vehicle velocity, and (f) vehicle position. The Fig. 4 shows that for the case 1 (blue curve) for pure H2 gas with 34.46 A/F ratio the engine speed (Fig. 4(a)) is higher than the octane fuel (red curve) with 15.1 A/F ratio. The torque generated is also higher in the case of H2 gas. The A/F ratio for case 1 and case 2 shows that for H2 a fuel-lean mixture while for the gasoline a fuel-rich mixture is required. This is also evident from Fig. 4(c) that the fuel consumption of pure H2 is far less than pure octane. This kind of comparison is not evident in the previous studies. This finding is one of the important contributions of this study.




7

In case 3 pure H2 is used and then using the hit-in-trail method the required A/F ratio is determined which can generate the same torque as generated by pure octane fuel with its actual stoichiometric A/F ratio. It was observed from case 3 that a further fuel-lean mixture i.e. from 34.46 to 41 A/F is required to run the vehicle at its optimum torque. Fig. 4(c) shows that fuel flow rate of H2 is just below 3 g/s (black curve) which is the minimum fuel flow rate among all simulation results. The simulation results of this nonlinear vehicle model shows that if the A/F ratio of around 41 can be maintained for the H2 gas then it could be highly economical to run the vehicle. This is another significant finding of this study.

Table 1. Vehicle and Powertrain Parameters

Engine displacement Vd 0.0038 m3 Intake manifold volume Vman 0.0027 m3 Universal gas constant R 287 Manifold temperature Tman 293 K Max. Flow rate of air in the intake manifold MAX 0.1843 kg/s Air/fuel equivalence ratio λ 1 Stoichiometric air/fuel mass ratio for gasoline (Octane fuel) Lth 15.1 Fuel energy constant [MJ/kg] (for Octane) Hu 47.98 MJ/kg Thermal efficiency ηi

0.32

Moment of inertia of engine Ie 0.1454 kg.m2 1st gear speed reduction ratio R1 0.3424 2nd gear speed reduction ratio R2 0.6379 Final drive speed reduction ratio Rd 0.3521 1st gear speed reduction ratio R1 0.3184 2nd gear speed reduction ratio R2 0.505 3rd gear speed reduction ratio R3 0.73 4th gear speed reduction ratio R4 1 5th gear speed reduction ratio R5 1.3157 Final drive speed reduction ratio Rd 0.3257 Moment of inertia of wheel Iw 2.8 kg.m2 Effective radius reff 0.3 m Longitudinal tyre stiffness (for both tyres) Cσf 80000 N Air density ρ 1.225 kg/m3 Aerodynamic drag coefficient Cd 0.4 Wind velocity Vwind 10 m/s Mass of the vehicle m 1644 kg

(a)

(b)

(c)

0 5 10 15 20 25 301500

2000

2500

3000

3500

4000

4500

5000

5500

time [s]

En

gin

e sp

eed

[rp

m]

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0 5 10 15 20 25 300

100

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Net

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e [N

m]


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1

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7

8x 10

-3

time[s]

Fu

el F

low

Rat

e [K

g/s

]





8

(d)

(e)

(f)

Fig. 4. Vehicle Response for H2 Gas, Gasoline, and their Mixture (a) Engine Speed (b) Engine Torque (c) Fuel Flow Rate

(d) Gear Shifting (e) Vehicle Velocity (f) Vehicle Position

Using Eq. (5) to Eq. (7), both fuels are added with their corresponding amount of air required for the stoichiometric combustion. The A/F ratio for the mixture of octane and H2 gas is then determined which turns out as 24.7853 for both fuels. Their combined heat of combustion is computed as 168.08 KJ/kg. The A/F mixture is an important feature for the complete combustion of a fuel. The green curve in Fig. 4 shows the vehicle response for the H2 gas and octane mixture. Fig. 4(b) shows that the engine generates the highest torque (green curve) for the mixture of both fuels and a fuel-lean mixture is required for the combustion with the A/F ratio of 24.7853. The engine generates higher engine speed (Fig. 4(a)), less fuel consumption then pure octane (Fig. 4(c)), rapid gear shifting (Fig. 4(d)), higher longitudinal speed which is more than 120 Km/h (Fig. 4(e)), and covers more distance (Fig. 4 (f)) than other cases. It can be clearly seen in Fig. 4(e) that the vehicle millage with H2 gas is lot higher than without H2 gas.

It was observed and computed from Fig. 4(c) that the 37% to 45% of octane consumption is reduced when used in addition with H2 gas with the computed A/F ratio. Octane consumption can be further reduced if a fuel-lean mixture is used for the same vehicle. This is the paramount finding of this study. Using the advanced technology and efficient sensing devices, the required mixture of octane and H2 gas with their corresponding A/F ratio can be achieved which can solve many problems of automobile industry, power production units using heat sources, and in general the energy crises.

7. Conclusion

A nonlinear vehicle dynamic model is used to investigate the torque generated and fuel consumption using the A/F ratios and heat of combustion of H2, gasoline (octane), and their mixture. The heat of combustion and required A/F ratio for mixture is determined using the combustion Stoichiometry and Hess’s Law. The nonlinear vehicle model includes the engine dynamics, transmission dynamics, wheel dynamics, and vehicle longitudinal dynamics which capture the vehicle response in continuous time-domain. The simulation results show that the H2 gas is far more economical than pure octane and if the required size of dry cell HHO generator with the given A/F ratio is used then it will significantly reduce the reliance on the fossil fuels which are depleting rapidly and at the same time the emission of the gasoline can be reduced which produce a large amount of pollutants. The mixture of both fuels with their required A/F ratio can reduce the octane consumption up to 37% to 45%. It is, therefore, recommended that H2 gas as a supplement fuel should be used to improve the vehicle efficiency and to reduce the

0 5 10 15 20 25 302

2.5

3

3.5

4

4.5

5

time [s]

Gea

r sh

ifti

ng


0 5 10 15 20 25 3020

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60

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120

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Veh

icle

sp

eed

[M

PH

]

time [s]


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time[s]

Po

siti

on

[m]





9

combustion emissions. Moreover, the simulation of the nonlinear vehicle dynamic model using the H2, gasoline, and its mixture can be useful for developing the experimental model, its testing, and its implementation.

Acknowledgements

The author would like to express his sincere thanks to Mehran University of Engineering & Technology, Jamshoro, Pakistan, for giving him an opportunity to pursue this master’s study in Manufacturing Engineering.

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[13] Y. Hacohen and E. Sher, “An internal combustion SI engine fueled with hydrogen enriched gasoline”, Israel Journal of Technology 25:41-54 (1989).

[14] B. Shrestha and Narayanan, “Landfill gas with hydrogen addition – A fuel for SI engines”, Fuel 87:3616-3626 (2008). [15] N. Saravanan and G. Nagarajan, “An experimental investigation on optimized manifold injection in a direct-injection diesel

engine with various hydrogen flowrates”, ProcInstMechEng D J Auto Eng. 2007;221:1575-84. [16] Ali. Z, “Transitional Controller Design for Adaptive Cruise Control Systems”, PhD thesis, Mechanical and Mechatronics

Engineering, University of Nottingham, UK, (2011). [17] Internal Combustion Engine Fundamentals, McGraw-Hill, John-Heywood, (1988).



301. Prediction of pseudo-retrograde hydrate phenomenon for ternary systems Ethane (C2H6) + propane (C3H8) + water (H2O) and Ethane

(C2H6) + i-butane (i-C4H10) + water (H2O) in hydrate-forming region

Khan Muhammad Qureshia*, Saima Khanb aChemical Engineering Department Mehran University of Engineering and Technology Jamshoro Sindh, 76062, Pakistan..

bUniversiti Teknologi PETRONAS, 31750, Malaysia.

Abstract

Gibbs energy minimization method is used to calculate the phase equilibria of ternary ethane (C2H6) + propane (C3H8) + water (H2O) and ethane (C2H6) + i-butane (i-C4H10) + water (H2O) systems. CSMGem prediction software is used for flash calculations. Various concentrations of ethane were used for the evaluation of (Lw-V-H) phase equilibrium of two pure gases. It is commonly termed as the dissociation of H cant happened by increment of pressure but in case of ethane (C2H6) + propane (C3H8) + water (H2O) systems at 277.9K, flash calculations showed that hydrate may dissociate and this phenomena termed as pseudo-retrograde hydrate behavior may exist but this is not necessary in all cases. In case of ethane (C2H6) + i-butane (i-C4H10) + water (H2O system no pseudo-retrograde behavior was predicted by considerably increasing pressure at various temperatures 275K, 278K and 280K. Phase diagram for ethane + propane + water and ethane + i-butane + water systems were plotted for pressure as a function of mole fractions of ethane. Predictions of ternary mixtures equilibria for aqueous (vapor–liquid equilibria) systems reveal satisfactory predictions for ternary mixtures. This study will contribute to solve the problems of petroleum products during exploration and its production in offshore and onshore condition.

© 2016 "Insert names of Authors here." Selection and/or peer-review under responsibility of Energy and Environmental Engineering Research Group (EEERG), Mehran University of Engineering and Technology, Jamshoro, Pakistan. Keywords: Hydrate, Pseudo-retrograde, Flash calculation

1. Introduction

Clathrate or also known as gas hydrates belong to the group of physical crystal like compounds. Water is the major part of crystal structure forming component in cavity of gas hydrate formation. Water molecules can form a hydrogen bonding network, with defined cages or known as cavities, in which gas serves as guest and water serves as host molecule to form hydrate. Until more than 100 types of important hydrate-formers have been recognized and reported by Jens et al., [1]. Among them are NG components such as CH4 hydrates (or gas hydrates, etc.) are water based solid crystals look like ice like structure in which very small tiny non-polar molecules (typically gases), polar molecules, low molecular weight gases or volatile liquids are trapped inside the "cages", known as cavities in the crystalline structure of H2 joined water molecules at particular temperature and pressure condition. Presently structure I (sI), structure II (sII) and structure H (sH) are well established and studied. Hydrate structure sI and sII can be formed with addition of a single guest component while structure H requires minimum two different guest molecules (large and small) to form sH hydrate. Most components of natural gas mixtures are (CH4, C2H6, C3H8, CO2, N2 and H2S etc.) can form gas hydrates. The recent development on the use of clathrate hydrates in industrial process requires knowledge in the phase behaviour of hydrate forming system. Phase behaviour of simple hydrate systems have been thoroughly investigated mostly based on hydrocarbons and carbon dioxide system. In hydrate phase behaviour, pseudo-retrograde hydrate behaviour in which by increasing pressure solid phase dissociates and form liquid phase this phenomena occurs in hydrate forming region. Still reported data on these phenomena is not sufficient in current literature to see the phase behaviour of single, binary and multi component systems. This article talk about the predicted results for hydrate phase behaviour for the gas mixture of ethane (C2H6) + i-butane (i-C4H10) + water (H2O) at specific temperature and pressures conditions. Hydrate formation conditions were predicted. Sabil et al., [2] has reported the experimental evidences in his research work occurrence of pseudo-retrograde behaviour of CO2 and tetrahydrofuran system. Ballard et al., [3] has assumed that pseudo-retrograde may appear, but this is not restricted only for system having binary components those having structure I (sI) and structure II (sII) hydrate formers are present and having very low pressure. The research work is streamlined to find more evidences on the occurrence of pseudo-retrograde hydrate behaviour in mixed hydrate systems especially in natural gas components and CO2 based systems to validate the Ballard et al., [3] hypothesis.

2. Methodology



The prediction of phase equilibria is performed by flash calculations taking 30% overall gas composition and 70% in excess water. The predictions of phase equilibria points were calculated in respect of ethane (C2H6) + propane (C3H8) + water (H2O) at 277.9K. Similar prediction method was also used by Ballard et al., in 2001[3]. For Ethane (C2H6) + i-butane (i-C4H10) + water (H2O) system were studied with three different temperatures 275K, 278K and 280K with various gas compositions taken in mole fractions and studied to see the effect of concentration on phase equilibria. The pressure of the system is increased at a selected value keeping iso-thermal condition until hydrate solids are detected through flash calculations. The pressure is slowly increased by 1atm until the hydrate solid is completely eliminated from the system. A series of these equilibrium points were produced for selected equilibrium lines. By measuring a series of these equilibrium lines, the phase behaviour of the system is constructed in Excel sheet using equilibrium points at various mole fractions of Ethane (C2H6) + i-butane (i-C4H10) + water (H2O) system.

A flash calculation based method is also reported by Bishnoi and Gupta [4] based on Gibbs energy minimization is adopted in this work. This prediction can report the phases present at various gas mole fractions, temperature, and pressure conditions. This prediction method is used to for the determination of the number of phases present due to changing the pressure. Applying flash calculations the possible phases comprise V, Lw, Lhc, structure I hydrate, and structure II hydrate. SRK Eos [5] is used to model the fugacities in (V, Lhc, and Lw)

𝑙𝑛𝑓F𝑦FH

=𝑏F𝑏𝑍 − 1 − ln 𝑍 − 𝐵 −

𝐴𝐵×

2 𝑖QFRFS𝑎

−𝑏𝑘𝑏

ln𝑍 + 𝐵𝑍

(1)

A famousKrichevsky–Kasarnovsky [6]equation isplasticized to findout thesolubilityofhydrocarbons in theLwphase. Van der Waals and Platteeuw theory [7] used to calculate the “f “fugacity of water in hydrate phase. This main equation can foretell the chemical potential of water in hydrate structure; where in the 𝜇c

d shows the chemical potential of water, in empty hydrate structure, Vmshowsthenumberofcagesoftypem/water moleculeispresentinthehydratephase.

𝜇dg

= 𝜇hd + 𝑅𝑇 𝑚𝑉𝑚𝑙𝑛 1 − 𝑗𝜃op

2

StructureandθJm isused to calculate the Jth occupancyof guestmolecule in themthhydrate cage.This fractionaloccupancycanbewrittenas, 𝜃

tpuvwxywx

z{ vSxySxS

(3)

Where, 𝑓tpand 𝐶tp shows the fugacity and Langmuir constant of component J present in m cage. The constant value depending on temperature and can be described as the interaction parameters in between the gas molecule and the H2O can be assessed by arrogant a circular structure with correct proportion potential can be written as,

𝐶tpu 4𝜋𝑘𝑇

exp[−𝜔tp(𝑟)𝑘𝑇

�x�Rw

�]𝑟�𝑑𝑟(4)

Where ωJm (r) used to calculate the cell potential of gas molecule J in cavity m and 𝑎t stand for the spherically inner radius of J and Rm value stands for the radius of cavity m. In this work, the Kihara cell potential parameters [8] can be applied for the calculation of water-gas effect upon one another in every cavity. The H2O chemical potential in Lw phase is obtained by Marshall et al,[9] and after some time it was simplified by another researcher Holder et al.,[10] and Menten et al.,[11] and his co-workers which can be simply defined as in (Eq.(5),

𝜇h� = 𝜇hd − ∆𝜇h� + T

∆h�T�

�

��dT − ∆V�

�

�dp + 𝑅𝑇ln α� (5)



Where, ∆𝜇h� shows the variation in the chemical potential of H2O in the unoccupied hydrate structure and pure Lw at a (273.15 K) and absolute zero pressure, ∆hw and ∆Vw are presented. α� shows the activity of water. To obtained the fugacity of water in hydrate phase, Eqs. (1) and (4) can be applied. Hydrate fugacity depending on the chemical potential of water in liquid water phase mentioned in Eq. (5).

f�� = fw� expµ�� −µ��

RT(6)

All predictions have been taken in the presence of excess water due to liquid water phase.

3. Results and Discussion

Table. 1. Predicated CSMGem values for the system ethane (C2H6) + propane (C3H8) + water (H2O) at 274K. __________________________________________________________________________ Lw -V Lw-sII-V Lw-sI-V Lw-sII _________ _________ _________ ________ P(atm) P(atm) P(atm) P(atm) Mole fraction ___________________________________________________________________________ 0.1 2.595 2.133 2.514 0.2 2.780 2.175 4.891 0.3 2.889 2.360 6.672 0.4 3.400 3.410 0.5 4.372 3.460 0.6 5.267 3.815 0.7 6.609 5.410 0.8 5.267 7.406 6.410 0.9 4.521 6.730 5.257 ____________________________________________________________________________



Fig.1. Pressure as a function of mole fraction for ethane (C2H6) + propane (C3H8) + water (H2O) system at 274 K.

Fig.1 Shows the hydrate formation phase diagram when ethane (C2H6) + propane (C3H8) are added together at 274K. Here ethane behaves like an inhibitor for sII hydrate because of occupancy in large cavity of sII. Propane (C3H8) can serve as an inhibitor to sI hydrate formation when it added in ethane (C2H6) + water (H2O) system. Nevertheless propane may not enter in the sI cages because the fugacity of ethane is much lower when the Propane C3H8 is subjected, subvert the sI hydrate. Holder [12] reported the inhibiting effect as an “antifreezing” agent. The P v.s mole fraction for ethane (C2H6) + propane (C3H8) + water (H2O) system is mentioned in Fig. 2. From (0.0-0.5) mole fraction of ethane (C2H6) sII hydrate is predicted. If the pressure is increased up to 9.5 atm, from (0.23-0.5) mole fraction of ethane, sII hydrate is predicted to dissociate and to form three phase Lw–V–Lhc equilibrium line. The point at which the hydrate dissociates is predicted through flash calculation is termed as pseudo-retrograde pressure at constant temperature. It can be defined as the changing of a solid phase to liquid phase by increasing the considerable pressure keeping low temperature conditions.

Table.2. Predicated CSMGem values for the system ethane (C2H6) + propane (C3H8) + water (H2O) at 277.9K. ____________________________________________________________________________

Lw -V Lw -sII-V Lw -sI-Lhc Lw -sI-V _________ __________ __________ __________ P(atm) P(atm) P(atm) P(atm) Mole fraction ____________________________________________________________________________ 0.1 4.910 5.205 0.2 5.247 7.000 9.810 0.3 5.355 9.500 10.216 0.4 5.273 9.500 13.103 0.5 8.734 9.500 13.100 0.6 13.236 13.100 0.7 14.110 13.100 13.100 0.8 12.137 13.100 10.000 0.9 9.642 13.100 9.45 ___________________________________________________________________________



Fig.2. Pressure vs. mole fraction for the system ethane (C2H6) + propane (C3H8) + water (H2O) at 277.9K. Pseudo-retrograde behaviour can be obtained by vapour liquid equilibria of ethane (C2H6) + propane (C3H8) + water (H2O) system at 277.9 K. The dotted line shows in Fig.2 is Lw–V–Lhc phase envelope. The Lw–sII–V phase area crossing from the Lw–V–Lhc area and meeting at the quadruple point at (9.5 atm) pressure. In terms of Gibbs phase rule, prediction shows that there is one degree of freedom (three components and four phases) are formed at 277.9 K. This point creates a four-phase line, Lw–sII–V–Lhc. If the considerable pressure is increased, one of the phases may disappear. In this situation, the predicted results show that sII phase dissociates with increasing pressure and Lw–V–Lhc appears which shows uncertainty because upon pressurization hydrate phase has to remain. The validity of the predicted results of Fig.2 reported in literature similar data taken by Ballard et al.,[3], Holder and Hand [13] for ethane (C2H6) + propane (C3H8) + water (H2O) shows pseudo-retrograde behaviour upon pressurization.

Table. 3. Predicted CSMGem values for the system ethane (C2H6) + i-butane (i-C4H10) + water (H2O) at 275K.

Lw -V Lw -sII-V Lw -sI-Lhc V-Lhc-sI Lw -Lhc-V ________ ________ ________ ________ ________ P(atm) P(atm) P(atm) P(atm) P(atm) Mole fraction 0.1 1.782 2.580 1.740 0.2 2.004 2.082 5.424 0.3 2.289 2.445 7.294 19.978 0.4 2.663 7.294 19.650 0.5 3.155 7.294 9.819 0.6 3.869 7.294 7.500 0.7 4.993 7.294 10.357 0.8 7.310 7.289 14.032



0.9 6.510 14.492

Fig.3. Pressure vs. mole fraction for the system Ethane (C2H6) + i-butane (i-C4H10) + water (H2O) at 275K By considering all data Fig.3 is plotted between pressure and mole fractions of Ethane (C2H6) + i-butane (i-C4H10) + water (H2O) system at 275K and 35 atm. Behaviour of ethane is observed using CSMGem simulation software by flash at various pressure and range mole fractions. Predicted results show that sII hydrate of ethane is predicted at 0.1 mole fraction and found stable after considerable increase in pressure, it is observed that it may not dissociate, where sI is formed at 0.6 mole fraction of ethane by same manner by increasing the considerable pressure the prediction shows that sI do not dissociate. Calculation are taken at 30% overall gas composition in presence of excess water. Phase behaviour is observed by the amount of V-Lw equilibrium condition for ethane (C2H6) + i-butane (i-C4H10) + water (H2O) system. Prediction shows that no dissociation is observed in both structures sI and similarly in sII by increasing the considerable pressure, in the light of these observations no evidence of pseudo-retrograde behaviour is predicated in ethane (C2H6) + i-butane (i-C4H10) + water (H2O) system using CSMGem.

Table .4. Predicted CSMGem values for the system Ethane (C2H6) + i-butane (i-C4H10) + water (H2O) at 278K.



Lw -V Lw -V-Lhc Lw -Lhc V-Lhc -sI Lhc -sI V-sI Lw-Lhc _______ ________ _______ _______ ______ ______ _______ P(atm) P(atm) P(atm) P(atm) P(atm) P(atm) P(atm) Mole fraction

0.1 2.009 3.788 50.000 45.000 10.187 0.2 2.253 5.833 50.000 25.000 22.000 0.3 2.558 7.962 50.000 25.435 23.000 0.4 2.958 10.036 18.790 20.000 0.5 9.800 10.036 10.100 0.6 7.699 10.036 12.000 45.000 0.7 5.800 10.036 14.600 50.000 0.8 5.600 10.036 17.492 54.000 0.9 5.800 20.000 31.000

Fig.4. Pressure vs. mole fraction for the ethane (C2H6) + i-butane (i-C4H10) + water (H2O) system at 278K

Pressure versus mole fractions of ethane (C2H6) + i-butane (i-C4H10) + water (H2O) system at 278K is shown in Fig.4 overall gas composition is taken as 30% with excess water. Three phase hydrate equilibrium line V-Lhc-sI is observed at 10 atm pressure. Phase behaviour of hydrocarbon at various pressure and mole fractions of ethane (C2H6) and i-butane (i-C4H10) is observed using Predication Software CSMGem is used by evaluation through flash calculation. Phase behaviour is observed by assessment of the V-Lw equilibria of ethane (C2H6) + i-butane (i-C4H10) + water (H2O) system. No dissociation is observed up to 25 atm and above pressures, so no pseudo-retrograde behaviour is predicated in ethane (C2H6) + i-butane (i-C4H10) + water (H2O) system .

Table.5 Predicted CSMGem values for the system ethane (C2H6) + i-butane (i-C4H10) + water (H2O) at 280 K.



Lw -V Lw -V-Lhc Lw - Lhc Lw -Lhc -sI _______ ________ _______ ________ P(atm) P(atm) P(atm) P(atm) Mole fraction 0.1 2.156 3.992 40.000 0.2 2.414 6.118 40.000 0.3 2.741 8.331 40.000 0.4 3.169 10.634 40.000 0.5 3.755 12.531 24.485 0.6 4.603 12.531 24.485 0.7 5.935 12.531 0.8 8.320 12.531 0.9 12.308 12.531

Fig.5. Pressure vs. mole fraction for the system ethane (C2H6) + i-butane (i-C4H10) + water (H2O) at 280K

Fig.5 is plotted between pressure and mole fraction of ethane (C2H6) + i-butane (i-C4H10) + water (H2O) system at 280K and 30 atm for the system. Behaviour of hydrocarbon at various pressure and mole fractions of ethane is observed by using prediction software CSMGem through Flash calculation. Phase behaviour is observed for the V-Lw equilibria of ethane (C2H6) + i-butane (i-C4H10) + water (H2O) system. The Lw-V-Lhc phase area passes through and intersects the V-Lhc-sI area. No dissociation is occurred in sI by further pressurization, so no pseudo-retrograde behaviour is predicted.

The overall gas composition is taken as 30% with excess water at various temperatures and pressure ranges by establishing the isothermal condition and Gibbs energy minimization hydrates equilibria are studied. The predicted values show that, for a range of temperature approximately 0.5 K, it is possible that hydrate may dissociate in case of sII hydrate of ethane (C2H6) + i-butane (i-C4H10) + water (H2O) system by increasing considerable pressure. In case of Ethane (C2H6) + propane (C3H8) + water (H2O) system, pseudo-retrograde behaviour may help in solving industrial related transportation problems. The three phase in fig: 4 & 5 Lw-Lhc-sI and in fig: 3 two phase V-sI are observed. It is found that Ethane (C2H6) + i-butane (i-C4H10) + water (H2O) system do not show pseudo retrograde behaviour of ternary system at the studied temperature and pressure conditions. Further efforts are needed to confirm the results by performing a series of experiments for the validity of pseudo-retrograde behaviour in different systems and also to verify the predicted results.

4. Conclusion

Pseudo-retrograde phenomena is predicted containing ethane (C2H6) + propane (C3H8) + water (H2O) system at (9.5 atm) and 277.9K, similar results were also predicted by Ballard. In case of ethane (C2H6) + i-butane (i-C4H10) + water (H2O) no Pseudo-retrograde phenomena is predicted. Existence of sI and sII hydrates has great importance in transmission of gas



pipelines Experimental results are required for validation of predicted results generated through CSMGem prediction software



Acknowledgements

I am highly thankful Saima Khan who helped me in this research and in the preparation of this paper.

References

[1] N.Jens , Lothar R. Oellrich . Fluid Phase Equilibria Volume 139, (1997) 325-333. [2] K. M., Sabil, Witkamp, G.J.J. Chem. Thermodynamics, 42,8-16, 2010. [3] A.L., Ballard, Jager, M.D., Nasrifar, K., Moojier- van den Heuvel , M.M., Peters,C.J., E.D., Sloan. Fluid Phase Equilib. 185, 77-87, 2001. [4] A.K., Gupta, P.Raj Bishnoi, Nicolas Kalogeraki, ”Simulta- neous multiphase isothermal / isenthalpic flash and stability calculations for

reacting/non-reacting systems”Gas Separation & Purification, Volume 4, Issue 4,December 1990, Pages 215-222. [5] G. Soave, Chem. Eng. Sci. 27 (6) ( 1972) 1197–1203. [6] I.R. Krichevsky, J.S. Kasarnovsky, J. Am. Chem. Soc. 57, 2168–2171, 1935. [7] J.H. van der Waals, J.C. Platteeuw, Adv. Chem. Phys. 2 ,1-57, 1959. [8] V. McKoy, O. Sinanoglu, J. Chem. Phys. 38 (12), 2946–2956, 1963. [9] D.R. Marshall, S. Saito, R. Kobayashi, AIChE J.10 (2),202–205, 1964. [10] G.D. Holder, G. Corbin, K.D. Papadopoulos, Ind. Eng. Chem. Fundam. 19 (3) 282– 28,1980. [11] P.D. Menten, W.R. Parrish, E.D. Sloan, Ind. Eng. Chem.Proc. Des. Dev. 20, 399401, 1981. [12] G.D. Holder, J.H. Hand,AIChE J. 28 (3), 440– 447,1982. [13] G.D. Holder, Ph.D. Thesis, University of Michigan,nn Arbor, MI, 1976.

List of symbols appendix A

a guest core radius Greek letters C Langmuir constant µ chemical potential (J/mol) F fugacity coefficient ν number of hydrate cavities / water molecule h enthalpy (J/mol K) θ occupancy of gas in the hydrate cavity k Boltzmann’s constant (J/K) ω( ) cell potential P pressure ∆ difference between H structure and water r integration variable R gas constant T temperature in (K) v volume in (cm3/mol) Subscripts 0 properties at reference conditions J guest component m hydrate cavity w water Superscripts β unoccupied hydrate phase H solid hydrate Lw liquid water Lhc liquid hydro carbon




303. Synchronization of Hydrogen Energy with Diesel Engine for Distributed Generation Applications

Syed Zulqadar Hassana,*, Hui Li a, Tariq Kamalb, Umair Younasc, Qasim Awaisd aState Key Laboratory of Power Transmission Equipment and System Security and New Technology, School of Electrical

Engineering, Chongqing University, Chongqing, 400044, China bPower and Energy System Group, School of Information Technology and Electrical Engineering, University of Queensland,

Brisbane, QLD 4072, Australia cDepartment of Electrical Engineering, COMSATS Institute of Information Technology, 22060, Abbottabad

dDepartment of Sensors and actuators, Chongqing University, Chongqing, 400044, China E-mail address: [email protected]

Abstract

This piece of work provides modelling, control and synchronization of hydrogen energy (fuel cell system), a super-capacitor with a diesel engine which supplies power to the local grid and domestic load. The developed test-bed works under simple classical based energy management algorithm while all its components are controlled via DC-DC converters embedded with Proportional Integral (PI) controllers. According to the proposed algorithm, hydrogen energy (fuel cell system) is the priority to satisfy the total demand. The diesel engine is added as a back system to increase the reliability of power flow for 24 hours. The slow dynamic response problems of the fuel cell during transient has addressed through a super-capacitor in the proposed architecture. The role of dump load has taken from electrolyzer which produce hydrogen and to decrease power fluctuation during surplus power. Matlab/Simulink has been used in the designing of proposed test-bed. Simulation results prove the feasibility of proposed test-bed in terms of load tracking and reliability.

© 2016 “Syed Zulqadar Hassan, Hui Li, Tariq Kamal, Umair Younas, Qasim Awais” Selection and/or peer-review under responsibility of Energy and Environmental Engineering Research Group (EEERG), Mehran University of Engineering and Technology, Jamshoro, Pakistan. Keywords: Distributed generation, Hydrogen energy, Super-capacitor, Load tracking

1. Introduction

Energy has an imperative role in the wheel of technology evolution and modernization of different communities. However, today’s power systems experience issues such as deregulation when they have no back-up system. To take much benefit from Distribution Generation (DG), generation and load must be integrated as a subsystem. Such system may utilize any combination of generation, storage technologies and load and can operate for on-grid and off-grid applications to facilitate the life standard of people in remote areas. Some typical examples of DG or micro-grid are photovoltaic-battery and/or photovoltaic/super-capacitor serving a remote load and wind/micro-turbine system serving an isolated village. DG comprises of electric or thermal load, and any combination of small hydro, Photovoltaic (PV), wind turbines, fuel cells, micro-turbines, reciprocating engine generators, and energy storage systems such as batteries, supercapacitor and hydrogen.

Modern development in Fuel Cell (FC) has established that hydrogen will have a central role in the near future for power system [1]. Key features of FC include modularity, pollution free, high efficiency and quiet operation. Among the various types of FCs, Solid Oxide Fuel Cell (SOFC) has the highest efficiency FC among others [2]. Nevertheless, SOFC has a higher power density with poor dynamic response. When a SOFC is operated under transient, it takes several seconds to track the load and an instant drop off of the voltage in the I-V curve occur. Furthermore, hydrogen starvation can occur, which decrease the overall performance of FC [3]. Energy storage systems support transient stability during the rapid load variations. Additionally, they are also very convenient for load-smoothing applications.



Energy, Environment and Sustainable Development 2016 (EESD 2016) Various types of energy storage systems such as flywheel energy storage, Super-capacitors (SCs), pumped hydro, and batteries are used for different goals in different applications. Among various types of storage system, SC has high power density and a very fast instantaneous response. Therefore, they can provide better transient stability during the rapid change in power demand. Considering the utilization of higher power density, i.e., SC modules in the SOFC plant can provide the most suitable choice.

Another important and commonly use power source is diesel generator which supply power in remote areas during failure of national grid. Therefore, synchronization of diesel generator with FC and an incorporation of SC can offer highly significant dynamic benefits in term of power reliability for DG. Many FC and Diesel Engine (DE) based power plants have been studied in the literature. For instance, a FC with Electrolyzer (ELZ) and DE hybrid system is designed in [4]. The intermittent nature of wind energy conversion is addressed by DE in [5]. In [6], the poor dynamic response has been solved through SC. Digital control of FC/SC power plant is developed in [7]. In [8], [9], the researchers described FC centred load applications and the combined utilization of FC/micro-turbine. Similarly, the importance of hydrogen energy for hybrid power system is described in [10], [11].

This manuscript presents provides modeling, control and synchronization of hydrogen energy (SOFC), an SC with a DE. The proposed system supports the local grid and domestic load while considering the real load condition at Bahria town Islamabad, Pakistan. The proposed test-bed works under classical based energy management algorithm called Supervisory Control System (SCS) which generates the dynamic references for each subsystem and ensures: (1) to maximize the output power, and (2) proper energy management of storage systems according load conditions and status of utility.

This manuscript is organized as: First, system description is provided in Section 2. Section 3 explains modelling and control of proposed system. Section 4 provides the proposed power sharing and energy management system. Section 5 describes the simulation results. Section 6 concludes the paper.

Fig. 1. Architecture of proposed DGS

+

_

A

B

C

SUPERVISORY CONTROL SYSTEM

SiVR

P*SC

P*G

P*DE

P*ELZ

Si

DO

ME

STIC

L

OA

D

+

_

VD

C-B

US

GSDIESEL ENGINE

ASSEMBLY

SOFC/ELZ SYSTEM

+

_

SC SYSTEM

+

_

BUCK/BOOST & VOLTAGE REGULATORS

RECTIFIER & VOLTAGE REGULATOR

PMSG

MAIN INVERTER UTILITY GRID

S1 S2VR

S3VRS3

S4

S1VR

PDE

PFC

PELZ

PSC

PG

PDL

PFC

PDL

PG

PDE

PELZ

TSC

PSC

S2

AC-Bus



Energy, Environment and Sustainable Development 2016 (EESD 2016) 2. Description of proposed Distributed Generation System

This section briefly explains the proposed Distributed Generation System (DGS). The entire structure of proposed DGS is shown in Fig. 1. It is made up to two-bus system; DC Bus and AC Bus. DC bus is formed by DE, SC and hydrogen system (SOFC) while the AC Bus is structured with utility grid and Domestic Load (DL). DE is mechanically coupled with a Permanent Magnet Synchronous Generator (PMSG). The hydrogen system (SOFC) and SC are connected via buck-boost converter followed by voltage regulator.

3. Modeling and control of proposed DGS components

3.1. Diesel Engine Assembly

In this research, a 40 kW DE is mechanically coupled with a PMSG. A three-phase Pulse Width Modulation (PWM) based inverter is used to transfer power from generator. A boost converter based voltage regulator is used to stabilize the output voltage to DC-bus level.

The governor block diagram is shown in Fig. 2. The generator and engine are operated in torque control and speed control modes via electric governor and PWM inverter. The controllers are constructed in the cascaded manner; and the current regulation loop of the electric governor is the inner loop and the speed regulation loop of the DE is the outer loop. The speed control of DE through Proportional Integral Differentiator (PID) controller is shown in Fig. 3. Then the transfer function of the speed controller can be expressed as follows [12],

( ) ( ) ( )

2

* *

( )

p d d i p d i d

d

K K s K K s Ki

s s

ω ω ωω ω

ω

+ + + + = − +

(1)

Fig. 2. Block diagram of speed controller with electric governor and diesel engine

Fig. 3. Implemented PID speed controller

3.2. SOFC System

The model used in this study is based on the dynamic SOFC model explained in [13]. The effective partial pressures associated with system dynamics is given by:

2 2 2

2 2

1 1( 2 )in

H H H r fcH H

P P q K It K

= − + −

& (2)




2 2

2 2

1 2)H O H O r fc

H O H O

P P K It K

= − + −

& (3)

2 2 2

2 2

1 1( )in

O O O r fcO O

P P q K It K

= − + −

& (4)

Using the above partial pressures, the output voltage can be calculated using the Nernst’s equation given in (5) and complete dynamic model of SOFC is presented in Fig. 4.

2 2

0

2

0.5

0 0 ln2

H Ofc f

H O

P PRTV N E rI

F P

= + −

(5)

Fig. 4. SOFC dynamic model

In order to control the hydrogen system, the PID based DC-DC buck/boost converter is used. The reference voltage is calculated using reference power generated by SCS. The PID generates appropriate output based on the error of reference and actual voltages. The PWM generator encodes output into a square wave pulse of corresponding duty cycle. The control strategy of hydrogen system is shown in Fig. 5.

Fig. 5. Control strategy of hydrogen system

3.3. SC System

In this paper, classical model of SC is used which consists of double layer capacitance, an equivalent series and an equivalent parallel resistances as shown in Fig. 6(a). VSC represents the output voltage of

PID Controller

PWM Generator

DC/DC converter

Duty Ratio +_

Vref

Vout Error



Energy, Environment and Sustainable Development 2016 (EESD 2016) single SC unit. The energy produced/consumed by SC depends upon its capacitance, initial voltage and final voltage, respectively and given as:

2 21( )

2SC i fE C V V= − (6)

The UC is connected to the DC-CPC through DC-DC buck-boost converter. The buck-operating mode is used for charging of UC and vice versa. The DC-DC converter control system work on reference current calculated from reference power generated by SCS. The control diagram of buck-boost converter is shown in Fig. 6(b).

Fig. 6. SC system (a) Model of SC (b) Control system of DC-DC converter

3.4. Main Inverter System

The DC-Bus is coupled with load and grid through three phase inverter. The entire control scheme is shown in Fig. 7. Initially, the PI controller is used to minimize the difference actual and reference power of inverter. Based on error, the PI generates corresponding dq-references. Using dq/abc transformation, current in-terms of abc reference is generated. After taking difference with actual currents, it will passed through hysteresis comparator and it generates the corresponding signals for inverter switches.

Fig. 7. Control schematic of main inverter

4. SCS of proposed DGS

In order to provide uninterruptable power supply to the DL, the SCS is designed. The key role of SCS is to deliver maximum power from available resources (DE/SOFC/SC/UG) to fulfil the DL demand. The power flow between different energy sources are managed by SCS. Based on available resources, the SCS generates required power references. In order to achieve required power, SCS generates the appropriate signals to control power converter. In this case, SCS operates on several inputs: SOFC actual power (PFC), DL power demand (PDL), DE output power (PDE), UG output power (PG), Electrolyzer

PID Controller

PWM Generator

Buck OperationDuty

Ratio +_

IR

Iout Error

Boost Operation

IR<0

IR>0

DC/DC Converter

RP

RS

CVSC

(a) (b)

+_

PINV-R

PINV

PIController

dq/abc

id_r

ia_r

ib_r

ic_r

iq_r

+_

+_

+_UH B

LU B

UH B

LU B

UH B

LU B

ia

ib

ic

Hysteresiscomparator

Main Inverter



S1

S4

S3

S2

S5

S6

AC-Bus



Energy, Environment and Sustainable Development 2016 (EESD 2016) power demand (PELZ), SC output power (PSC) and its SOC (TSC). Using the above variables, the power balance equation, along with excess and deficient power can be written as;

FC DL SC G DE ELZP P P P P P= ± ± − + (7)

( )EX DL FC SC ELZ GP P P P P P= − = − + + (8)

DF DL FC SC G DEP P P P P P= − = + + (9)

where PEX and PDF represents the excess and deficient power inside the system.

Fig. 8. Flow chart of power management algorithm

In order to prevent system from blackouts or synchronization issues, it is needed to develop the power management algorithm for SCS. This algorithm operates on basic seven inputs (i.e., actual powers of each sources and SOC of SC). The developed algorithm for SCS is shown in Fig. 8, and described below.

Yes

PDL=PDE

±PSC +PFC-PELZ ± PG

PDL>PFC

Yes No

PG,PDL,PFC,PSC

PDE,PELZ,TSC

Yes

No

TSC>90%Yes

From 1

No

P*SC=PDL-PFC

TSC>20%No

P*SC=PDL-PFC

PDL>PFC

+PSC

No

Goto 1

Yes

P*DE=PDL

-(PFC+PSC)

Goto 1

No

Yes

Fro

m

2

Fro

m

3

Start

Goto 2

Goto 3

PDL-(PFC

+PSC)<0

If H2 tank is Full

P*G=PDL-

(PFC+PSC)

Yes

P*ELZ=PDL-(PFC+PSC)

No

Goto 1

Goto 1

Peak Load

Yes

Goto 1

P*G=PDL-(PFC+PSC)

Goto 1

No




Algorithm 1: Power Management Algorithm

1: Power output/demand of all energy sources (and SOC of SC) are monitored.

2: if #$% & #'( ) #*% ) #+ , #'- . #-(/,

3: Goto 1, end 4: if #'( 0 #$% ,

5: if 1*% 0 20%,

6: Apply reference power to SC: #*%∗ & #'( , #$%

7: else Goto XX 8: end 9: if #'( 0 #$% . #*%, 10: if #'( 0 5056, 11: Apply reference power to DE: #'-

∗ & #'( , (#$% . #*%) 12: else Apply reference power to UG: #+

∗ & #'( , (#$% . #*%) 13: end 14: else Goto 1 15: end 16: else 17: if 1*% 0 90%, 18: Goto YY

19: else Apply reference power to SC: #*%∗ & #'( , #$%

20: end 21: if #'( 8 #$% . #*%,

22: if 19:5; < 155#9

23: Apply reference power to UG: #+∗ & #'( , (#$% . #*%)

24: else Apply reference power to ELZ: #-(/∗ & #'( , (#$% . #*%)

25: end 26: else Goto 1

27: end 28: end

5. Simulation Results and Discussion

To check the effectiveness and performance of proposed algorithm, a test-bed containing different sources/loads is developed in Matlab/Simulink by means of simpower system toolbox. During development of test bed, the rated power of DE, SOFC, SC, inverter and UG are considered as 40 kW, 50 kW, 100 F an 100 kW and 500 kVA, respectively. The simulation is performed for one day while considering actual domestic load conditions of Behria Town, Islamabad Pakistan.

For better exploration of results, the time interval of one day is divided into four time slots. The power output/demand of different energy sources at different time slots are shown in Fig.s 9 to 12. In these Fig.s, the blue solid represents the actual power of source/load while red dotted line represents the reference power of applied converter for corresponding sourse/load. Before explaining results, it is important to remember that the maximum power output of SOFC is 50 kW.

Fig. 9 shows the simulation results for t=0-6 Hrs. In this time slot, the DL demand gradually increases from 23 kW to 38 kW as illustrated in Fig. 9 (a). From Fig. 9 (c), the UG is at off peak hour and delivers two power peaks (8 kW and 10kW). Therefore, using power balance equation, the power demanded from DC side (i.e., inverter power reference P*

I=P*FC+P*

DE+P*SC) is less than 50 kW as shown in Fig. 9 (e).

Thus, SOFC easily fulfil the entire load demand. However, due to rapid change in load and slow response of SOFC, the SOFC is unable to track the load. In this case, SC hideout SOFC load tracking drawback by providing rapid power at every hour as depicted in Fig. 9 (f).




Fig. 9. Actual and reference powers of energy sources for t=0-6 Hrs (a) DL (b) SOFC (c) UG (d) DE (e) Main Inverter (f) SC

Looking towards Fig. 10 (a), the DL demand gradually increases to 67 kW (peak load) from 43 kW. At t=6-8 Hrs, the DL is 48 kW, which is less the maximum power rating of SOFC. While on same side, the UG delivers 10 kW power. Thus, it is not needed to activate DE (its output power is zero). At t=8-12 Hrs, the DL becomes greater than 50 kW. UG is also at isolated mode due to peak load hours. Hence, using last reserve, the SCS turned on the DE, providing maximum output of 24 kW as shown in Fig. 10 (d). As both SOFC and DE have rapid load tracking drawback, SC overfills the power gap created by them at every hour as illustrated in Fig. 10 (f).

Fig. 10. Actual and reference powers of energy sources for t=6-12 Hrs (a) DL (b) SOFC (c) UG (d) DE (e) Main Inverter (f)

SC

The simulation result for t=12-18 Hrs is shown in Fig. 11. The DL load demand decreases from 68 kW to 48 kW as shown in Fig. 11 (a). Additionally, UG is at peak hours while consuming 15 kW of power. Subsequently, SOFC does not hold off DL burden. In this regard, the SCS keep DE on until (17 Hrs) DL demand decreases 50 kW as shown in Fig. 11 (d). In final hour of this slot, the UG back online, assisting SOFC to overcome load demand as shown in Fig. 11 (c).

As stated earlier, SOFC is the primary energy source. But, due to off peak hours, the load burden is less than 50kW for t = 0-8 Hrs. 50kW is the maximum rating of SOFC. From Fig. 9(a), after 8 Hrs, the load

0 1 2 3 4 5 62

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kW)

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(f)



Energy, Environment and Sustainable Development 2016 (EESD 2016) demand is greater than 50kW (except 17,18Hrs), Therefore, SOFC delivers it maximum available power of 50kW. The output power vs time graph of SOFC is shown in Fig. 9(b) where red dots shows reference power while blue line shows actual power. On other side SC keep tackling with rapid loads.


SC

The simulation results of final time slot is shown in Fig. 12. The peak load of entire day falls in this time slot at 20-21 Hrs (i.e., 70 kW). At t=18-19 Hrs, the DL demand is 52 kW. However, the UG provides 18 kW, so, overall power demanded for SOFC is 42 kW (below 50 kW). Therefore, DE is kept off by SCS. At t=19-24 Hrs, UG is again isolated from the system due to peak load hours. Thus, in order to achieve high DL, the SCS turned on SOFC and DE as shown in Fig.s 12 (b) and (d). At t=20 Hrs, there is a significant change in load is observed. At this time, the SC provides a peak power of 16 kW.


SC

6. Conclusion

This study concludes the modelling, control and an energy management for a SOFC/DE/UC hybrid power plant for DG applications. All the energy sources and storage system are controlled by their

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(a)

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er (kW

)

Time (Hrs)

(f)



Energy, Environment and Sustainable Development 2016 (EESD 2016) respective controllers while the overall coordination among SOFC, ELZ, DE, UC storage system and loads is performed by the developed SCS. The weak load following problems of SOFC has addressed by using UC. The proposed system uses the waste fuel of SOFC in order to maximize the overall system efficiency. The proposed plant can be used with or without grid and/or can be synchronized with multiple DG sources to shave the load power during peak hours. The performance of the proposed model is tested for real load conditions. From the simulation, it is clear that the developed system meets all the conditions required for the stability and power quality of power system.

Acknowledgements

The research work is supported by National Natural Science Foundation of China (No.51377184), International Science & Technology Cooperation Program of China (No.2013DF G61520) and Fundamental Research Funds for the Central Universities (No.CDJZR12150074).

References

[1] T. Kamal, S. Z. Hassan, H. Li, and M. Awais, “Design and power control of fuel cell/electrolyzer/microturbine/ultra-capacitor hybrid power plant,” in 2015 International Conference on Emerging Technologies (ICET), 2015, pp. 1–6.

[2] S. Hoseinnia and S. M. Sadeghzadeh, “A Comparative Study of Fuel Cell Technologies and their Role in Distributed Generation,” in IEEE EUROCON 2009, 2009, pp. 464–469.

[3] T. Das and S. Snyder, “Adaptive control of a solid oxide fuel cell ultra-capacitor hybrid system,” in Proceedings of the 2011 American Control Conference, 2011, pp. 3892–3898.

[4] T. Senjyu, T. Nakaji, K. Uezato, and T. Funabashi, “A Hybrid Power System Using Alternative Energy Facilities in Isolated Island,” IEEE Trans. Energy Convers., vol. 20, no. 2, pp. 406–414, Jun. 2005.

[5] T. K. Saha and D. Kastha, “Design optimization and dynamic performance analysis of a stand-alone hybrid wind–diesel electrical power generation system,” Energy Conversion, IEEE Trans., vol. 25, no. 4, pp. 1209–1217, 2010.

[6] S. Z. Hassan, H. Li, T. Kamal, S. Mumtaz, and L. Khan, “Fuel Cell/Electrolyzer/Ultra-capacitor hybrid power system: Focus on integration, power control and grid synchronization,” in 2016 13th International Bhurban Conference on Applied Sciences and Technology (IBCAST), 2016, pp. 231–237.

[7] J. C. T. Caballero, O. Gomis-Bellmunt, D. Montesinos-Miracle, R. Posada-Gómez, E. Pouresmaeil, and J. A. Aquino-Robles, “Digital control of a power conditioner for fuel cell/super-capacitor hybrid system,” Electr. Power Components Syst., vol. 42, no. 2, pp. 165–179, 2014.

[8] C. Wang, M. H. Nehrir, and S. R. Shaw, “Dynamic models and model validation for PEM fuel cells using electrical circuits,” IEEE Trans. energy Convers., vol. 20, no. 2, pp. 442–451, 2005.

[9] Y. Zhu and K. Tomsovic, “Development of models for analyzing the load-following performance of microturbines and fuel cells,” Electr. Power Syst. Res., vol. 62, no. 1, pp. 1–11, May 2002.

[10] T. Kamal, S. Z. Hassan, M. J. Espinosa-Trujillo, H. Li, and M. Flota, “An optimal power sharing and power control strategy of photovoltaic/fuel cell/ultra-capacitor hybrid power system,” J. Renew. Sustain. Energy, vol. 8, no. 3, p. 035301, 2016.

[11] T. Kamal and S. Z. Hassan, “Energy Management and Simulation of Photovoltaic/Hydrogen/Battery Hybrid Power System,” Adv. Sci. Technol. Eng. Syst. J., vol. 1, no. 2, pp. 11–18, 2016.

[12] S.-H. Lee, J.-S. Yim, J.-H. Lee, and S.-K. Sul, “Design of speed control loop of a variable speed diesel engine generator by electric governor,” in Industry Applications Society Annual Meeting, 2008. IAS’08. IEEE, 2008, pp. 1–5.

[13] T. Kamal, “Adaptive Control of Fuel Cell and Design of Power Management System (PMS) for PHEVs/EVs Charging Station in a Hybrid Power System,” COMSATS Institute of Information Technology Abbottabad-Pakistan, 2014.




94. Utilization of Bio fuel Cell Technology for Power Generation in Pakistan

Danish Qamar Syeda*, Maria Sohailb aFederal Board Of Revenue, Government of Pakistan, Karachi, Pakistan

bNED University of Engineering & Technology, Karachi, Pakistan *Email Address: E-mail address:[email protected]

Abstract

"This research centers around the possible prospects for the utilization of biofuel cell technology in Pakistan for electrical generation. We have speculated the possibility of employing the microbial fuel cells all over the rice fields in Punjab by sowing its anodes with their roots and keeping floating cathodes over the water surface of rice paddies, the rhizodeposits (carbohydrates) or organic matter as substrate in the roots of these plants react with microorganisms coated on anode which produce electrons, protons and CO2, Joining anode with cathode by a wire, electrons reach cathode to combine with oxygen. These electrons can be turned into huge electricity by a useful chemical reaction. Secondly we estimated the use of these cells along the coastal sediments of Karachi that are rich in metals which can be used to fuel these cells and make 1000s of Megawatts."

© 2016"Danish Qamar Syed, Maria Sohail" Selection and/or peer-review under responsibility of Energy and Environmental Engineering Research Group (EEERG), Mehran University of Engineering and Technology, Jamshoro, Pakistan. Keywords: “Biofuel; cell; anodes; react; electricity"

1. Introduction

It goes without saying that at present Power is the need of hour all over the world, but when it comes to Pakistan; our country is in dire need of it. Pakistan, despite being a country rich in coal reserves, natural gas reserves, renewable energy utilization prospects, nothing has substantially ever been done to tap into all the above resources for power generation. For the entire power deficit, no heed is paid to using green energy for energy acquisition. Pakistan being a country rich in agricultural products has a host of prospects for electricity to be got out of its agricultural lands as well apart from conventional renewable energy sources. This research work is based on an estimated analysis for the possible utilization for microbial fuel cell application on the rice fields at large and on the marine sediments along the coastal areas of Karachi, for power generation. These estimations are figured out keeping in view different researches in Europe and different countries on microbial fuel cell utilization along rice plants and marine sediments.

2. Microbial Fuel Cell

A microbial fuel cell is a simple cell like a battery having a positively-charged and a negatively charged electrode. In this cell cathode acts as an electron sink and anode as an electron acceptor. This process taps into the biological action of micro-organisms present everywhere I.e. in water, in soil etc. The micro-organisms perform degradation of organic as well as inorganic compounds for their survival. These degradations are of two types aerobic degradation and anaerobic degradation, 1st one involves oxygen while the second one doesn’t respectively. In anaerobic degradation the micro-organisms consume the substrate that may be an organic or inorganic compound, in the absence of oxygen and consequently carry out oxidation on the compounds to result in electrons protons and carbon dioxide, while speaking about organic substrates. These freed electrons gravitate towards an anode, which takes them up and transport the electrons across to the cathode by means of a wire as shown ion “Fig. 1”. Thereby this process gives rise to an electrical current and between cathode and anode there can be connected as well as wattmeter in series with the load and a voltmeter in parallel with the load. On the cathode electrons



Energy, Environment and Sustainable Development 2016 (EESD 2016) combine with oxygen so a reduction reaction takes place. This phenomenon of electricity generation can be turned into several advantages out of which only a few are assessed in this research.

Fig. 1. Illustration of Microbial fuel cell structu re

3. Application of Microbial fuel cell on Rice Plants

Although microbial fuel cell has a wide area of applicability yet we analyze its application with respect to rice plants, as its applicability is possible only in wetlands. The plant’s leaves are exposed to sun all the day. These leaves form carbohydrates out of carbon dioxide. These carbohydrates trickle down the roots of the plants which are exerted as small low molecular weight compounds by the roots. These carbohydrates are consumed by micro-organisms in the absence of oxygen which gives rise to electrons, protons and carbondioxide. The electrons are gravitated towards an anode sown together with the roots which takes up the electrons and transport them across to cathode, by means of a wire joining both electrodes. At cathode there takes place a reduction reaction when oxygen soaks up the flow of electrons from the anode, and water results as shown in the “Fig. 2”.

Fig. 2. Illustration of Microbial fuel cell with ri ce fields

It’s been noticed by several researchers in Europe that the power produced is directly subject to the area of anode sown with the roots. To speed up these redox reactions its suggestible to use electrochemically active bacteria that may act as catalysts these are Shewanella Puterfaciens [9], Aeromonas Hydrophila [17].

4. Energy Conversion Cycle

To understand this entire phenomenon one must need to comprehend the ins and outs of this whole generation process. The input of generation cycle is the solar energy which is harnessed by the leaves by being exposed to the sun all day long. This solar energy is converted into organic compounds which are a sort of chemical energy and at last this chemical energy deposited into the roots is turned into electrical energy by the interference of bacteria present in the soil by anaerobic degradation of this chemical substrate. In the wake of this process we come to acquire electricity at the output. It’s a three stage conversion process which is elaborated in “Fig. 3”.

Fig. 3. Energy Conversion Cycle



Energy, Environment and Sustainable Development 2016 (EESD 2016) 5. Expected Output Power Generation In Pakistan

Having scrutinized the European researches on the implementation of microbial fuel cell on rice fields we can also assess very well its applicability in Pakistan. As Pakistan has a very rich agricultural land so it has a great potential for such a green energy’s utilization along its lands. Pakistan has rice fields on an area as much as 2.5 million hectares which is almost 20% of the total area of food crops in Pakistan [2]. That’s the reason why Pakistan has been a large exporter of rice too. When we assess for a while the implementation of microbial fuel cell along all these rice fields we are taken aback to speculate the power production that we can reap out of these fields on top of rice. Researchers in Europe came to a conclusion that by the application of these fuel cells on rice plants, at maximum long about 289 to 300W/hectare power could be produced.

Rice Fields Area in Pakistan = 2.5 million hectare

Electrical output power with MFC 300Watts/hectare

Expected Electrical output power = 300 x (2.5 x 106)

Expected Electrical output power = 750 Mega Watts

If we assess the implementation of microbial fuel cells along our field in an area of 2.5 million hectare then we can get 750MW of power in total, on these fields in khareef seasons. This is indeed an enormous amount of power that can work wonders on our annual generation capacity. It’s suggested that graphite-coated electrodes be used for construction of both electrodes. In “Fig. 4”. A comprehensive arrangement can be seen for the deployment of these fuel cells in rice fields.

Fig. 4. Arrangement of Microbial fuel cell in rice fields

6. Implementation of Microbial fuel cells along Marine Sediments

Apart from the implementation of microbial fuel cell on rice fields, they can be used along the marine sediments. Our coastal sediments along the coastal belt are too rich in metallic reserves [15]. The sediments inside the sea have a great deal of hidden reserves of organic and inorganic compounds that keep on undergoing degradation at the hands of bacteria present in the soil. So this degradation of inorganic and organic compounds can also be tapped into for electrical generation by penetrating the anode into the sediments and keeping the cathode on the water surface for reduction reactions. In these cases special catalysts may be used on cathode surface to speed up the redox reactions. In these implementations a platinum anode and a stainless steel cathode is suggested to be used along with appropriate catalysts, for avoiding possible corrosions, which comes to a big expense as well, as the platinum is too expensive to be used.

7. Merits

This research may yield a great deal of benefits at present because of the current power scarcity. Its utilization may shore up the annual power generation capacity. Agricultural sector may be promoted by being integrated with power sector. With an estimated generation of around 750MW, Power dearth could be eliminated to a great extent. An energy that doesn’t consume any fuel to generate electricity.

8. Conclusion

This research is based on a speculation of microbial fuel cell utilization in Pakistan. At this point in time



Energy, Environment and Sustainable Development 2016 (EESD 2016) Pakistan is short of power to meet its demands so in such a situation piecing together the power from even small sources may help us get over the power dearth to a great extent. That’s how implementation of microbial fuel cell on the rice fields as well as on the marine sediments may meet our current power demands and may help us overcome the rising shortage of power day by day. In Europe billions of pounds are invested into such projects. In Pakistan a minute investment into this energy can get us so many advantages that it cannot be imagined.

References

[1] Alexis Madrigal.(June 15,2010), “Microbial Fuel Cells Generate Rice Paddy Power.”[Online].Available:http://www.wired.com/wiredscience/2008/04/microbial-fuel/

[2] Rice of Pakistan. .(June 10,2010) Pakistan Rice Complex ISO 9001-2000 “Rice in Pakistan.”. [Online].Available: http://pakistanricecomplex.com/Pakrice.html

[3] Wikipedia. .(July 1st ,2010), “Microbial Fuel Cell.”, The Free Encyclopedia. Wikimedia Foundation, Inc.[Online].Available: http://en.wikipedia.org/wiki/Microbial_fuel_cell

[4] Plant-MFC Concept. .(May 10,2010), Plantpower concept. Plant Power, Spin-off Company Plant-e 14 Sep. 2009. [Online].Available: http://www.plantpower.eu/

[5] Bond, d. R., D. E. Holmes, L. M. Tender, D. R. Lovley. "Electrode-Reducing Microorganisms That Harvest Energy from Marine Sediments" Science. 295, pp. 483-485.

[6] Franks, A.E, and K.P.Nevin. Microbial Fuel Cells, A Current Review. Energies. 3, pp. 899-919. [7] Holmes, D. E., D. R. Bond, R. A. O’Neil, C. E. Reimers, L. R. Tender, and d. R. Lovley. "Microbial Communities

Associated with Electrodes Harvesting Electricity from a variety of Aquatic Sediments". Microbiology Ecology. 48, pp. 178-190.

[8] Hong, S.W, Y. S. Choi, T. H. Chung, J. H. Song, and H. S. Kim." Assessment of Sediment Remediation Potential using Microbial Fuel Cell Technology". World Academy of Science, Engg. & Tech.. 54, pp. 683-689.

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