Peter Hass

IPSOS Industrial Consulting GmbH, Berlin,

Germany

1. Introduction

The increasing number of biogas plants which is favored now as a part of the energy concept of the German Government and the European Union has major impact on traditional gas distribution and transmission systems. In addition, synthetic methane gas or hydrogen injections must be considered in the near future which will originate from wind power generation (conversion of excess capacities). The main aspect of this change is the resulting calorific value which may be subject to changes in a short time which must therefore be measured, calculated and permanently surveyed.

This chapter describes the basics of gas mixing and the various situations which may be encountered and must be handled in the transportation or distribution process. There are some limitations which must be considered for industrial consumers and power plants. Measurements and simulations are required to survey and control the process of gas distribution and finally generate figures for accounting and billing. Some typical examples are presented to give an insight into real situations and projects.

The problems and limitations of the gas distribution process in heterogeneous networks and biogas injections are discussed with respect to the IT-structure and organizational environment. The final benefit that can be achieved is an individual calorific value for each consumer in the grid enabling a fair billing despite the variations of many gas injections from many sources.

As mentioned previously, the temperature and substrate compostion have a high effect on biogas production. Their effects are confirmed by the study published by several researchers. As an example the results, obtained by Derbal et al. (Derbal & al., 2011) can be cited.

The obtained values of different parameters of the (co)-digestion experiments under mesophilic and thermophilic conditions are presented (see figure 2, 3, 4, 5, 6). It should be noted that the volume of the mesophilic co-digester which is 2000 m3 is 20 times larger than pilot scale digesters 500 l. Therefore, the absolute biogas volume produced is different from the other cases and no comparison can be made. However, a comparison for different parameters is presented as follows:

0,5

0,45

0,4

0,35

0,3

CO

■E 0,25 0,2 0,15 0,1 0,05 0

Fig. 2. Comparison of gas production (GP)

The use of gas production rate GPR as a comparison parameter led us to include the data from the industrial scale digester. The results shown on Figure 3 confirm that the combined effect of temperature and solid waste addition is positive and considerable. Moreover, thermophilic co-digestion presents the best GPR results wich are confirmed by values of

□ A. D. T=35°C

□ A. D. T=35°C

□ A. Co-D. T=35°C

□ A. Co-D. T=55°C

Fig. 3. Comparison of gas production rate (GPR)

SGP of Figure 4. SGP is in relation with the biodegradability of the substrate and with anaerobic process reaction. SGP increased from 0.14 to 0.33 for digestion of wastewater sludge alone when temperature increased from mesophilic conditions (35°C) to thermophilic ones (55°C), whereas for a wastewater sludge mixed with solid waste this parameter increased from

0. 31 to 0.51. Adding solid waste under mesophilic comditions results in an increase of SGP from 0.14 to 0.31, whereas under thermophilic conditions SGP increased from 0.33 to 0.51. The combined effect of increasing temperature from mesophilic conditions to thermophilic ones and adding solid waste to wastewater sludge increased SGP from 0.14 to 0.51. Figure 5 presents the comparison of COD removal in the different studied cases. It increased from 24% for wastewater sludge alone under mesophilic conditions to 49.35% for wastewater sludge mixed with solid waste under thermophilic conditions. Moreover, for TVS thermophilic, co-digestion presents the best removal rate, 52.93%, as shown in Table 5. As a treatment system, anaerobic co-digestion under thermophilic conditions presents the best removal rates as well as specific gas production. It should be noted that changing working conditions from mesophilic to thermophilic ones increases anaerobic kinetic rates and as such the treatment capacity of a known volume will be increased as well. Adding solid waste contributes to the increase of biodegradable organic matter in the substrate (Figure 6).

As a conclusion of this sludy, the obtained results show that thermophilic co-digestion gives the best results. Although the temperature has an effect on the biogas production, it remains however quite relative compared to the effect of solid waste. These results confirm that the combined effect of the temperature and solid waste improves considerably the biogas production rate (GPR). The moving from mesophilic to thermophilic conditions, for waste sludge alone makes GPR pass from 0.18 to 0.39 m3/m3*d and for the waste sludge mixed with solid waste from 0.29 to 0.96 m3/m3*d.

The analysis of produced biogas showed that the percentage of biomethane is very high 60.37 and 64.44 for the digestion of sludge waste in mesophilic and thermophic phases, respectively and 65.8 and 60.61 for the co-digestion of solids waste with sludge waste in mesophilic and thermophilic cases, respectively.

Hydrogen generation in microbiological processes can be realized both by eucariota (green algae), procariota (cyanobacteria) in direct or indirect splitting of water under illumination, as well as in the fermentation and photofermentation reactions in presence of organic substances and numerous strains of bacteria. Due to very low yields of hydrogen obtained in presence of algae and cyanobacteria this paper will concentrate only on fermentative processes.

Dark fermentation process towards hydrogen is performed in presence of organothrophic bacteria. Large variety of microorganisms is involved in these reactions, therefore this paper will focus only on the description of three groups of microorganisms.

The first group belongs to anaerobic, gram-negative, mesophilic bacteria of Clostridium and Bacillus type. C. acetobutylicum (Chin, 2003), C. butyricum (Masset, 2010, Cai, 2010) C. pasterianum, C. bifermentants (Wang, 2003), C. beijerinckii (Skonieczny, 2009), C. tyrobutyricum (Jo, 2008), C. saccharoperbutylacetonicum ( Alalayaha, 2008), B. lichemiformis (Kalia, 1994), B. coagulans (Kotay, 2007) are the most popular representatives of this group. This strains of bacteria can form spores capable to survive in extreme conditions such as low and high temperature, different pH, irradiation, extreme dry conditions or presence of deadly chemical compounds (eg. NaCl). Bacteria cells under these conditions goes to anabiosis: complete reduction of metabolic processes. The separation of already divided DNA occurs at this stage with simultaneous surrounding by two cytoplasmic membranes. The endospore formed under unfavourable conditions can return to normal activity under appropriate conditions. In this process the external protection of outer coating is destroyed. Appropriate temperature, pH and presence of feed compounds facilitate formation of vegetative cells and their growth (Setlow, 2007). In some cases presence and increase of concentration of specific compounds is the biochemical signal to stop the endospore phase. Presence of alanine, serine, cysteine together with lactic acid accelerate germination C. botulinum bacteria (Plowman, 2002).

The second group of fermentative bacteria active in hydrogen generation belongs to anaerobic gram-negative bacteria. The best activity in biohydrogen generation via dark fermentation was found for the following strains: Enterobacter asburiae (Jong-Hwan, 2007), Enterobacter cloacae (Mandal, 2006), Enterobacter aerogenes (Jo, 2008), Escherichia coli (Turcot, 2008), Klebsiella oxytoca (Wu, 2010) or Citrobacter Y19 (Oha, 2003). These strains of bacteria can tolerate oxygen in environment. Here, in aerobic condition the oxygen respiration can occurs. The change of metabolic pathway provides method for survival under variable conditions of environment. These bacteria show better biological activity in comparison with those active only in completely anaerobic conditions. However, in aerobic conditions no hydrogen formation is observed. This effect is caused by inhibition of hydrogenase, enzyme catalyzing hydrogen generation.

Thermophilic bacteria operating at 60-85 oC belongs to the third group of bacteria generating hydrogen in fermentative processes (Zhang, 2003). The following strains of thermophilic bacteria of Thermoanaerobacterium thermosaccharolyticum (Thonga, 2008) and hyperthermophilic of Thermatoga neapolitana (Mars, 2010, Eriksen, 2008), Thermococcus kodakaraensis (Kanai, 2005), or Clostridium thermocellum (Lewin, 2006) can generate hydrogen in presence of organic substrates at relatively high temperatures. It was established that thermophilic bacteria are the most effective from all those already described.

Application of C. saccharolyticus and Thermatoga elfii thermophilic bacteria results in 80 % yield of the theoretical one (theoretically 4 moles of glucose can be transformed into acetic acid with 100% yield) while applying saccharose or glucose (Vardar-Schara,2008), respectively. High yield in hydrogen generation is explained by Guo et al. (Guo, 2010) who assumes that high temperature can accelerate hydrolysis of substrates engaged in this process. At the same time Valdes-Vazquez et al. (Valdes-Vazquez, 2005) demonstrates that such results are not surprising, because optimal activity of hydrogenase is 50-70 °C. Unfortunately, the high yield of hydrogen generation with thermophilic bacteria is not equivalent to total amount of generated gas (Hallenbeck, 2009). In this situation the construction of bigger reactors is required what in consequence increase total costs. Moreover, reaction performed at higher temperatures require additional thermal energy supplied to the bioreactor.

Photofermentation in hydrogen generation is the process which requires appropriate strain of bacteria, organic substances (mainly VFA) and light with appropriate intensity. The following strains of bacteria indicate activity in photoproduction of hydrogen: Rhodobacter sphaeroides (Koku, 2002), Rhodobacter capsulatus (Obeid, 2009), Rhodovulum sulfidophilum (Maeda, 2003), or Rhodopseudomonas palustris (Chen, 2008). The research of new strains active in photogeneration of hydrogen is performed in numerous laboratories all over the world. These efforts were recently awarded by discovery of activity in Rheudopseudomanas faecalis (Ren, 2009).

Rhodobacter sphaeroides belong to the group of bacteria the best recognized in hydrogen generation. These gram-negative bacteria belongs to the purple non-sulfur (PNS) Proteobacteria subgroup (Porter, 2008). The morphology is different because the shape of these bacteria as well as their dimensions strongly depends on the medium (see Fig. 3). In medium containing sugars the dimensions are limited to 2.0-2.5 x 2.5-3.0 pm, whereas under other conditions they can vary from 0.7 to 4.0 pm (Garrity, 2005).

Rhodobacter spheroides indicate strong chemotaxis with certain sugars, aminoacids and several organic acids (Packer, 2000). They are also capable to accept molecular nitrogen. Their metabolism is very elastic because they can germinate both in aerobic conditions (with or without light) as well as in anaerobic environment, in presence of light.

Under aerobic conditions this strain is used in purification of animal wastes (Huang, 2001) and biotransformation of toxins present in plant extracts (Yang, 2008). In the absence of oxygen Rhodobacter spheroids can be used in synthesis of carotenoides (Chen, 2006) and the most of all in hydrogen generation (Kars, 2010).

The measured results of the total accumulated temperature of each treatment were shown in table 4-8.

Analysis of variance of the total accumulated temperature of each treatment was shown in table 4-9.

Multiple comparisons of the total accumulated temperature of different soil depths among treatments were shown in table 4-10.

Table 4-10 showed that there were significant differences between plastic film and three kinds of biogas fibre residue film, black film and control while the soil depth was 0cm and 10cm. There were significant differences between the black film and control; there were significant differences between A, B treatment of biogas residue fibre film and control; there were no significant differences between C treatment of biogas residue fibre mulch and control; there were significant differences between black film and C treatment of biogas residue fibre film. While the soil depth was 5 cm, there were significant differences between plastic film and three kinds of biogas fibre residue film, black film and control; there were significant differences between A, B treatment of biogas fibre residue film, black film and control. While soil depth was 15 cm, there were significant differences between plastic film and three kinds of biogas fibre residue film, black film and control; there were significant differences between the black film and C treatment of biogas residue fibre film and control.

While the soil depth was 0 cm, 5 cm, 10 cm, the total accumulated temperature of A, B treatment of biogas residue film obviously increased than control, and C did not significantly increase; while the soil depth was 0cm, the total accumulated temperature of A treatment increased 31.8 °С, B increased 28.5 °С, and C increased 15.3°C than control; while the soil depth was 5cm, the total accumulated temperature of A treatment increased 17°C, B increased 17.3C, and C increased 15.2°C than control; while the soil depth was 10cm, the total accumulated temperature of A treatment increased 18.2 °С, B increased 15.8 °С, and C increased 10.2 °С than control. While the soil depth was 15 cm, the total accumulated temperature of three kinds of biogas fibre residue film nearly closed to control, and was less than the black film and plastic film. There was no significant difference between the three kinds of biogas residue fibre film.

Chitosan is available commercially in three forms: solution, flake and powder. The prices of chitosan in the forms of solution, flake and powder range between 50 to 70 baht/L, 700 to 900 baht/kg and 750 to 2,300 baht/kg, respectively. Chitosan in the form of freely moving polymeric chains has previously been found to enhance sludge granulation and shorten the start-up period of UASB systems (El-Mamouni et al., 1998; Lertsittichai et al., 2007; Liu et al.,

2002; Thaveesri et al., 1995).

The effectiveness in enhancing granulation of different forms of chitosan, i. e. solution, bead and powder, has also been studied by Nuntakumjorn et al. (2008). They prepared chitosan solution by dissolving chitosan in acetic acid solution (1% w/v). In preparing chitosan powders, they used a spray dryer to spray-dry chitosan solution (1% w/v). In preparing the chitosan beads, they dropped the chitosan solution (4% w/v) into a solution of KOH and ethanol. The chitosan beads were found to have spherical shape, white color and looked like glutinous pellets. The appearance of the chitosan beads is shown in Fig. 6.

Nuntakumjorn et al. (2008) used two identical reactors, with a working volume of 5.3 L, running in parallel. A sludge suspension with an initial VSS concentration of 12 g VSS/L was inoculated into the reactors. The acclimation of the sludge was carried out until the COD removal was approximately 80%. The reactors were run with a HRT of 1.5 day corresponding to an OLR of 1.45 g COD/L-d. Chitosan in the different forms was introduced into the reactors on the second operating day of the start-up period at dose rates of 2 mg chitosan/g suspended solids.

A summary of the results of Nuntakumjorn et al. (2008) is as follows. When comparing between the UASB with no chitosan addition and the UASB with chitosan addition in the solution form, the UASB with chitosan addition was found to have a 9 to 59% lower effluent COD, 5 to 7% higher COD removal, up to 25% higher biogas production rate, 21 to 39% lower biomass washout, 37% larger particle size and 4 day longer sludge retention time.

When comparing between the UASB with chitosan addition in the solution form and with addition in the bead form, the UASB with chitosan solution was found to have 5 to 17% lower effluent COD, 16 to 45% higher COD removal, 7 to 20% lower biomass washout and 3 to 17% higher biogas production than the UASB with chitosan beads. The reduced effectiveness of chitosan in the bead form might be caused by a lower amount of chitosan in the bead form and by insufficient contact between the chitosan beads and biomass.

When comparing between the UASB with no chitosan addition and the UASB with chitosan addition in the powder form, no differences were found in terms of COD removal, biogas production and biomass washout. The average COD removal of the UASB with chitosan addition was approximately 80% and that without chitosan was approximately 81%. The biogas production rate was 9.85 L/d and 10.23 L/d for the UASB with and without chitosan addition, respectively. Both UASB reactors had biomass washout in the range of 0.6 to 1.5 g VSS/L. Although chitosan powders have net positive charge, the electrostatic interaction between the negatively charged bacteria was not significantly reduced. Nuntakumjorn et al. (2008) concluded that chitosan powders does not enhance the granulation process and UASB performance.

The conditioning with air and / or liquid gas to adjust the technical combustion characteristics may influence both the methane number and the condensation of higher hydrocarbons in the combustion gas mixture.

The methane number — equivalent to the octane number of petrol — is a statement of the anti­knock properties of fuel combustion in a engine, where the term anti-knock refers to the tendency to uncontrolled and undesirable self-ignition. Methane has by definition a methane number of 100, hydrogen a methane number of 0. A methane number of 80 for example means that the gas mixture associated with this methane number has the same anti­knock properties as a mixture of 80% vol. methane and 20 vol. -% hydrogen. Some inert mixture components such as CO2 increase the methane number, higher hydrocarbons, reduce it. The calculated methane numbers (Gascalc, E. on Ruhrgas) of L gases are generally greater than those of H gases (nitrogen not factored out). As a lower limit for the smooth operation of modern engines, a methane number of MZ > 70 is considered necessary (DIN 51624, 2008).

For multi-component mixtures such as natural gases, the condensation and boiling curves do not lie together, but span a conditional area, where different gas-liquid compositions are possible. Between the critical pressure and the cricondenbar point with increasing temperature, and between the critical temperature and the criconden therm point with falling pressure, condensate (retrograde condensation) can form when the throttle curve touches the dew line, intersects or the final state lies in the two-phase region (Honer zu Siederdissen & Wundram, 1986).

An admixture of propane / butane to natural gas and processed biogas generally manifests itself in a shift of the dew curve to higher temperatures. According to (Oellrich et al., 1996), in the case of Russian H gas, condensation is only to be expected at temperatures of -35 ° C, while it will occur with Dutch L gas already at -5 ° C. If liquid gas/air is admixed within the limits described in DVGW worksheet G 260, the criconden therm point moves toward +15 ° C or +45 ° C, but at higher pressures. For mixtures of natural gas and processed conditioned biogas, this is to be expected to a lesser degree, since the concentrations of propane / butane are correspondingly smaller.

It should be noted that the calculation of the condensation curves of natural gases requires an analysis that takes into account the higher hydrocarbons, since even small amounts in the ppm range result in a significant shift. Furthermore, the process of condensation is not in itself critical, but the quantity of condensate is the decisive criterion. For large flow rates, a seemingly low volume of condensate can therefore lead to problems (Oellrich et al., 1996).

The following Table 10 and Figure 13 show cases of condensation in conditioning by the addition of LPG, in order to meet the North Sea I specification. The lowest and the highest admixtures were selected for the diagrams. It should be noted that at the highest level of admixing, the restrictions imposed by G 486 were not observed.

Kondensationslinien (SRK-Gleichung)

Fig. 13. Condensation curves for mixtures of the North See I H gas specification

In summary, it can be said that the criconden therm points of the H gases in Germany lie below temperatures of -20 ° C. An exception to this are the higher caloric mixtures of the North Sea quality — here, 0 ° C is also possible. However, the mixtures were ignored in the calculation of the limits in G 486 and DIN 51 624, so that it applies mainly to the higher LPG quantities added. Generally, this means that process procedures, in which pressure and temperature lie in the two-phase region, should be avoided.

5. Conclusion

This section shows a summary of all the mixing rates of LPG and / or air to attain the base gas properties under consideration.

The use of biogas has a potential improve the quality of life in the rural areas through reduced drudgery in women and children, reduced indoor smoke, improved sanitation and better lighting (Amigun and Blottnitz, 2011). Wood fuel gathering is a hard and time consuming duty for women. For instance, it is estimated that women can spend 2-6 hours in collecting wood fuel (DFID, 2002) depending on the country and region. For instance, one study in Limpopo, South Africa found that the rural women spend 5-6 hours (Masekoameng et al., 2005), while another study in a different region of South Africa report that the women spend over two hours. This takes away time that could be better utilized in other productive activities such as income generation or education particularly for girls who have to be absent from school to undertake such task. Biogas plants thus can help in reducing the workload of women and girls in collecting firewood.

health problems caused by the smoke inherent to traditional ways of cooking and heating, particularly open fires include: sneezing, nausea, headache, dizziness, eye irritation and respiratory illnesses (Onguntoke et al., 2010). Biogas improves health of the rural people by providing a cleaner cooking fuel thus avoiding these health problems. Women and children have the greatest risk of these health problems and children under 5 years are at high risk of contracting acute respiratory illnesses such as, pneumonia. Often, the rural population are also faced with lack of sanitation, resulting in water borne diseases affecting mainly women and children. Operating a biogas plant implies that manure is directly fed to the plant keeping the kitchen smoke free and farmyard cleaner.

Anaerobic microorganisms, especially methanogens are highly susceptible to changes in environmental conditions. Many researchers evaluate the performance of an anaerobic system based on its methane production rate because methanogenesis is regarded as a rate — limiting step in anaerobic treatment of wastewater. Methanogens are highly vulnerable and extremely low growth rate in an anaerobic treatment system require careful maintenance and monitoring of the environmental conditions. A temperature change in the substrates or substrates concentration can lead to shutdown of gas production (Novaes, 1986).

The microbial metabolism processes are dependent on many parameters, so that for an optimum fermenting process, numerous parameters must be taken into consideration and be controlled. Some of these environmental conditions are shown in the Table 1 (Deublein and Steinhauser, 2008). A brief discussion of the factors more reported in literature is shown follows.

Building a network model is a complex task. It starts first with data extraction from the geographical information system (GIS) via a special interface. This will include and deliver all pipe data, node geographic coordinates and equipment forming the basic network structure. Control equipment such as valves and controlling regulators are read or derived from GIS data; regulator devices often must be connected manually or corrected afterwards.

Next the inputs and outputs of the network have to be introduced. Aside from feeder points or underground gas storage the outputs — better said the outflows — are modeled by consumers. Each consumer (up to hundreds of thousands) has his individual set of data, static or dynamic. Static data are used for long term planning for a certain scenario, dynamic data is used for short term planning (i. e. some days). When the simulation finally starts the correct pressure data — at least for the most important points — must be given to the simulator. Consumer data, valve position and pressure data must be taken from different IT-systems: Energy Data Management (EDM) system and Process Control system (SCADA).

To prove plausibility of the optimum PNS structure two scenarios were carried out, both for minimum as well as for maximum substrate cost situations. In the first case the maximum structure was reduced by taking away corn availability. With that only five substrate mixtures could be used for biogas production. The second scenario was set up to get an idea how feed — in tariffs can influence the outcome of an optimization. Therefore it was not allowed that a network set-up results e. g. in two 250 kWel CHPs if a 500 kWel instead could be taken.

4.3.1 Scenario I — No corn silage

As already mentioned in the beginning corn is currently a dominating substrate for biogas production. To show the potential of intercrops no corn is available in this scenario. Not to lose the comparability the amount of corn was compensated with an additional availability of intercrops. The calculation was based on the CH-outputs and adds up to additionally 904 t intercrops. With that 2,170 t/yr intercrops, about 1.7 times more than in the basic maximum structure shown in Figure 2, are available in the maximum structure of this scenario. Under these conditions PNS could choose between five different substrate feeds.

The optimization results in a technology network including two locations using the whole amount of available intercrops as shown in Figure 4.

location 1 and with same efficiency is supplied with substrate feed 2 consisting of 70 % intercrops and 30 % manure. It turned out that with this structure the outcome has yearly revenue of approx. 208,000 €. Compared to the optimum structure it is higher, but the basic conditions are different. Therefore this solution did not come up in the optimization of the maximum structure in the beginning. But it clearly shows that intercrops have a great potential to produce electricity and heat within a highly profitable biogas network without being in competition with food or feed production. But the precondition would be that in the case study a higher amount of intercrops is available as feedstock.