Advanced prediction, monitoring and controlling of anaerobic digestion processes behaviour towards biogas usage in fuel cells - target action h (AMONCO) | AMONCO | Project | Results | FP5 | CORDIS

Using a GC-MS methodology with a system of specially sensible detection up to < 0,1 mg/m3. The analysed components are Tetramethylsiloxan, Trimethylsiloxan, Hexamethyldisiloxan (M2), Hexamethylcyclosiloxan (D3), Octamethyltrisiloxan (MDM), Octamethylcyclosiloxan (D4), Decamethyltetrasiloxan (MD2M), DEcamethylcyclopentasiloxan (D5). The results are an average composition of 800 µg/m3 with the samples analysed actually.

Seaborne ERL GmbH has 4 IPR's within advanced treatment of biomass related to anaerobic digestion. A part of these IPR's is chemical removal of Sulphur. This system can - under adaptations - be used with FC's. In order to clean the biogas with special respect to Siloxanes and halogenated hydrogencarbons for usage in FC's, a combined chemical-physical cleaning process has been developed. By the beginning of the project it was focalised upon laboratory investigations of Siloxane analytics and the chemical and physical properties of the isolated compounds. After having identified the best possibility for combination with the SEABORNE biogas-cleaning unit, efforts were made to find a cost-effective solution. SEABORNE finally presents a technical draft for elimination of Hydrogensulphide, Siloxanes and Hydrogencarbons. Costs are calculated for investigations and consumables basing on kWh el.

Economic efficiency is of crucial importance for innovative technical developments in order to gain market access. Therefore, a continuous economic evaluation of AMONCO's technical R&D results has been necessary in order to guide the technical developments towards marketability. The work was based on EBV's vast experience in economic project evaluation and project finance. In this respect EBV has adapted and enhanced its profound calculation tool towards the application for economic evaluation of AMONCO's technological achievements. The Excel based calculation tool has been developed and continuously improved by EBV since the start of the company in 1994. The calculation tool covers all-important financial figures, such as profit and loss statement, cash flow and liquidity analysis, for the entire life cycle of renewable energy projects. Originally developed for wind energy projects the calculation tool has been adapted also to different other types of renewable energy projects, such as small hydropower and biogas plants. Therefore, the result is a calculation tool adapted to the need of the economic evaluation of AMONCO's technical achievements. The potential of this result is a future general application concerning the economic evaluation of upcoming Biogas / Fuel Cell projects.

Collecting and storing of data of the biogas plant like: - Chemical analyses, data collection and editing of input and output; - Daily documentation of data about amount and kind of input and gas yield; - Online-measurement of biogas parameters like CH4 and H2S; - Data about using leftovers in monoculture in a little biogas-digester; - Using gas-sampling device from PROFACTOR for gas measuring (SILOXANS).

The prediction program for the biogas fermentation with neuronal networks has been included in a Client/Server - software solution. The original prediction program is located on a server in the worldwide web, and is waiting for data from the client. With the client version it is possible for the user to select Excel data files, send all necessary data for prediction to the server, and get prediction results back to the front panel of the client program. Advantages: - Data updating and substitution of weights from a new training have been done only for the server software. It is not necessary to send each user a new software version. - Because the user just gets a front panel and not the whole program, it is possible to adapt the front panel for each user individually. - Data from different wastewater treatment plans can be collected on the server, and can directly used for network training. - The IP address of the user has to be listed on the server, so that the program can only be used from authorized workgroups. Changes in the prediction software: - Reducing organic loading rate (Bv) depending on the total volatile fatty acid concentration (VFA) occurs on the end of optimisation; - Prediction results from the last day were not used in the new program; - The allowed maximal Bv value will be calculated from last measured Bv value.

To carry out long-term monitoring of various kinds of the input biomass anaerobic digestion processes in the operational conditions of the industry scaled biogas plants, a pilot fermentor of a 5m3 volume was designed, manufactured and installed. The results of the analyses of various kinds of substrates and produced biogas composition were used in the development and optimising of the Decision Support Tool.

Since the biogas composition is decisive for efficiency of the CHP and the final objective of the entire project is to predict how that composition will result according to the substrate introduced in the digester, a detailed analysis program was established. The following substrates were analysed individually: - Intestine and contents (bovine), Rumen (bovine), Stomach (bovine), Fat (pork), Blood (bovine); - Intestine and contents (pork), Washing waterm. And also these were combined with diverse proportions, generating different mixtures. The parameters determined in each substrate and mixture were: - Total nitrogen (N-ges), NH4 N, Dried matter (TS), - Organic fraction (VSS), Fats Volatile Fatty Acids (HACeq). It was compared for each feedstock mixture at the same HRT and Organic Loading Rate and the results showed that OTS and COD removed were around 70%- 80% respectively. Also a high fat concentration in digester inhibits the methanization process. Besides, in the feeding mixture the above-mentioned parameters plus DQO, sulphides, sulphates, Cl, K, P and pH have been determined. The frequency of the parameters determination is specific for each type of parameter and equipment where it is made the test.

The obtained biogas was analysed. The biogas compounds sought were CH4, CO2, H2S, O2 and N2. Average biogas composition obtained is around 65% and 70% Methane, 25% Carbon dioxide. As substrate fat concentration became higher, the percentage of methane in the biogas increased as well. Taking care that a high fat concentration in digester inhibits the methanization process. Also we have investigated the different averages biogas compositions for several HRT.

Utilisation of biogas in Fuel Cells (FC's) in stead of usual gas engines to CHP generation cause a dramatically increase in required purity of the biogas fuel. It is specifically, but much FC type determined, related to Sulphur, Siloxanes a.o. The major FC harming impurities are all close related to substrates subject to anaerobic digestion (AD) and the digestion process itself. Thus, a sensoric layout enabling optimisation of substrates and AD process governing might be of decisive importance to an expected future with competitiveness in CHP generation through FC's. The results of sensoric layout as achieved by GasCon are integrated in the whole Amonco concept embracing the developed Decision Support Tool (DST) and the refined biogas purification methods developed under Work Package 8 of the project.

Organosiloxanes are semi-volatile organo-silicon compounds that can be converted to solid inorganic siliceous deposits (Silicon Dioxide SiO2). In gas engines they form a coating that can be very dangerous, with chemical and physical properties similar to those of glass, leading to the abrasion of gas motor surface. Additionally, the glassy residues are responsible for the inactivity of the surface of the catalytic system for the control of waste gas. The manufacturers of gas engines recently introduced a limit value for silicon of 1 mg/l measured in the oil of the gas engine in order to prevent premature engine failure due to silicon-induced damages (Prabucki et al., 2001). At the present there is not a standard method for the elimination of siloxanes from biogas from anaerobic digestion or from landfill gas. The main methods, which are used now are: freezing to -70°C (~ 99,3% efficiency), activated carbons (~ 99,1% efficiency) and solvent washing (~ 60,0% efficiency). The main advantages of these methods are the high costs. In the literature you can find that also microorganism can degrade organosiloxanes. Our intention is therefore to use the microorganism in a biofilter in order to develop a cost-effective cleaning system capable of eliminating the obstacles to widespread use of biogas in fuel cell.

It has been largely recognised that biomass will play a substantial role in the global energy balance. The use of biomass for power generation has a potential of solving, at least partially, the problem of non-renewable fossil fuel depletion. Although a fuel cell produces electricity, a fuel cell power system requires the integration of many components beyond the fuel cell stack itself, for the fuel cell will produce only DC power and utilise only processed fuel. Fuel conversion and alteration catalysts are normally susceptible to poisoning; thus the raw fuel cleaning process takes place upstream or within the fuel conversion process. The main goal of our work is to determine and quantify the influence of these poisoning compounds in the Fuel Cells, in order to establish specific testing methods. To evaluate the tolerance of contaminants a novel automatic, dynamic and steady state methods was development. The potential of fuel cell was measured at a constant current density applying a series of pulses with different concentrations of contaminants and different intervals of pulses. After poisoning the components of the fuel cell will be analysed using analytical techniques to try to assessed the real impact of it.

The Decision Support System is a software-tool that supports the operator of an anaerobic digester in running the reactor at maximum methane-production rates and minimum production rates of gases toxic to fuel cells at the same time. The core of the software is a neural network application realized completely in LabViewÓ. The neural network is trained with data gained from the experiments during AMONCO. The self-learning tool of neural networks enables a fast adaptation on different plant specifics.

The obtained knowledge and research results have been transferred into the education and training of the specialists and professionals for the biogas plants operation and biogas utilization in agriculture. Due to the fact that university students have access to the Biogas plant Kolinany; any by occasions of their visits at the biogas plant they are acquainted with the topics of renewable energy sources, biogas technologies, optimisation of anaerobic digestion processes as well as the fuel cell technologies and their use in combination with biogas. The students' interest in these issues was an impulse to prepare a new study course for bachelor degree students (3 year study course) in the study branch of renewable energy sources. The knowledge and research results obtained within the project has been implemented into the study programme of this new study course to transfer the good experiences into the education and training of the further specialists and professionals for the biogas plants operation and biogas utilization in agriculture. Moreover, all the above-mentioned issues are used as research topics solved by PhD post-graduate students as well as the topics for the final diploma thesis of the pre-graduate students.

Advanced prediction, monitoring and controlling of anaerobic digestion processes behaviour towards biogas usage in fuel cells - target action h (AMONCO)

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