Für den ökonomisch und ökologisch effizienteren Betrieb von Dampfkesselanlagen ist die Untersuchung von Korrosionsvorgängen in Wärmetauschern, verursacht durch das Rauchgas aus einer Biomasse-Feuerung, notwendig. Daher wurden bei Bioenergy 2020+ kurzzeitige Korrosionsversuche im Umfang von 300h Betriebszeit an einem Wärmetauscherstahl 13CrMo4-5 mit einer ONLINE-Korrosionssonde der Firma Corrmoran GmbH für die Erstellung eines empirischen Korrosionsmodells durchgeführt. Als Brennstoffe dienten Waldhackgut, Weizenstrohpellets und Altholz. Die Messung benötigt eine Ionen leitende Deckschicht, die sich erst am Beginn des Versuchs aufbaut. Aufgrund der fehlenden Deckschicht wird daher zu Beginn der Messung der Korrosionsleitwert unterschätzt. Daraus ergeben sich systematische Messfehler. Ziel dieser Arbeit war die Eruierung des Zusammenhanges zwischen Messfehler und Versuchszeit. Dabei stellten sich zwei systematische Messfehler als relevant heraus: •Die Abzehrrate ist zum Korrosionsleitwert proportional. Daher wird die Abzehrrate während der Eingangsphase der Messung unterschätzt. •Die Abzehrrate berechnet sich aus dem Korrosionsleitwert, multipliziert mit einem Kalibrierungsfaktor. Dabei ergibt sich der Kalibrierungsfaktor aus dem Verhältnis des gesamten korrosionsbedingten Materialverlustes über die gesamte Versuchsdauer, dividiert durch den über denselben Zeitraum integrierten Korrosionsleitwert. Aufgrund des zu Beginn unterschätzten Korrosionsleitwertes wird der Kalibrierungsfaktor und somit die Abzehrrate, berechnet aus dem reproduzierbaren Signal, überschätzt. Die Literaturrecherche zeigte, dass die Kinetik bei der Hochtemperaturkorrosion bei konstant gehaltenen korrosionsrelevanten Parametern einen linearen, parabolischen oder paralinearen Verlauf einnehmen kann. Die kleinstmögliche Abzehrrate und somit der kleinstmögliche Korrosionsleitwert zu Beginn der Messung ergibt sich bei der Annahme eines linearen Verlaufs, welcher die möglicherweise erhöhten Abzehrraten der Initialkorrosion nicht mitberücksichtigt. Aus dieser Annahme konnte der kleinstmögliche Korrekturfaktor cmin berechnet werden. Dazu mussten die Daten bei konstant gehaltenen Parametern gefiltert und daraus der zeitlich integrierte Korrosionsleitwert PL,Messung gebildet werden. Das Verhältnis von PL,Messung mit einem über die gesamte Versuchszeit konstant angenommenen zeitlich integrierten Korrosionsleitwertes PL,linear ergibt den Korrekturfaktor, der multipliziert mit den ursprünglich bei gleichen Parametern bestimmten Abzehrraten eine neue Abzehrrate k(t)neu ergibt. Der Vergleich mit den Ergebnissen eines Langzeitversuches unter ähnlichen Betriebsbedingungen in einem Biomasse-Heizkraftwerk zeigte dadurch eine Verbesserung der Abweichung der Kurzzeitversuche von 125% auf 55%. Aufgrund der Parametervariationen sowie der Temperaturschwankungen, verursacht durch Ein- und Ausschaltvorgänge der Anlage, haben die bei konstanten Parametern bestimmten Korrekturfaktoren für die durchgeführten Versuche nur bedingt Gültigkeit. Daher wurde in einem weiteren Schritt ein Korrekturfaktor cmin,var bestimmt, welcher alle Daten der Versuchsserie berücksichtigt. Dazu wurde das Signal der Eingangsphase durch ein gleichlanges reproduzierbares Signal, gemessen unter denselben Bedingungen am Ende der Versuchsserien, ersetzt. Es ergibt sich aus dem Verhältnis der zeitlich integrierten Korrosionsleitwerte PL,Messung der Originalkurve zu PL,idealisiert des idealisierten Verlaufs der Korrekturfaktor cmin,var. Dieser hat aufgrund der Berücksichtigung aller gesammelten Daten für alle bei den Versuchen bestimmten Abzehrraten Gültigkeit. Durch cmin,var konnte eine Reduktion der Abweichung auf 110% erreicht werden. Diese wird auf die im Gegensatz zur Langzeitmessung im Biomasse-Heizkraftwerk unterschiedliche Versuchsmethode sowie auf den unbekannten Einfluss der möglicherweise erhöhten Abzehrraten der Initialkorrosion zurückgeführt.  

This study focuses on the determination of alkali release from wood and straw pellets during combustion. The aim is to expand the knowledge on the K and Na release behaviour and to adopt chemiluminescence-based sensors for online monitoring of alkali detection which can be applied for the prevention of fouling formation in low quality biomass combustion plants. Flame emission spectrometry (FES) was used for optical detection of chemiluminescence spectra of K and Na using optical bandpass filters mounted on an ICCD (Intensified Charge Coupled Device) camera. FES data were verified by additional experiments with a single particle reactor (SPR) coupled with an inductively coupled plasma mass spectrometer (ICP-MS). Using both techniques, the release profiles of K and Na during a single pellet combustion at 1000 °C were determined and obtained K* and Na* emission intensities directly correlated with the results from the ICP-MS. It was determined that the emission intensity of alkali radicals depends on alkali concentrations in the samples and K and Na radical emission intensities increase with increasing alkali amounts in the samples. The ICP-MS data revealed that the release of K and Na mainly takes place during the stage of devolatilization. During devolatilization, almost all potassium and sodium are released from wood samples, while only 65–90% of K and 74–90% of Na are released from straw samples. Based on the results, the flame emission spectroscopy technique is capable to fully detect released alkali metals in the gas phase during combustion and proves a possibility to use flame emission sensors for monitoring the release of alkali species from biomass during combustion processes.

This article presents a general representation of the characteristic polynomial of the dynamic matrix for multivariable systems in Luenberger’s canonical forms. The characteristic polynomial is given by means of the determinant of a polynomial matrix of substantially lower order. Therein, the polynomial coefficients of the single elements are the coefficients of the corresponding blocks of the dynamic matrix. The proposed representation of the characteristic polynomial can be helpful for the design of state-feedback controllers and state observers which is demonstrated by a numerical example.

The chemical looping hydrogen (CLH) production process typically uses iron-based oxygen carrier materials and can provide hydrogen with high purity. Chemical looping is particularly attractive when renewable fuels like syngas from biomass gasifiers are used. This work provides a novel assessment of the possible thermodynamic and kinetic limitations for iron-based oxygen carriers in CLH fueled by biomass-based syngas, with a detailed study employing synthetic ilmenite (Fe2O3 + TiO2). Its phase diagram with H2/H2O- or CO/CO2-mixtures was compared to the typical Baur–Glaessner diagram for iron oxides. Thermogravimetric analyses underlined the necessity to consider TiO2 as a chemically active component for this material, in contrast to the common simplification of inert support materials. The validated phase diagram predicted stringent fuel limitations concerning H2O- or CO2-contents. This was confirmed by feeding a real biomass-based syngas, provided by a lab-scale gasifier, to a fixed bed CLH reactor. It was demonstrated for the H2/H2O-system that removing the oxidizing agent from the feed gas helps to overcome these limitations. Kinetic limitations within the thermodynamic boundaries were investigated using a recently published multiscale model for the H2/H2O-system. The influence of the fuel’s reduction potential on reaction rates was explored to formulate simple, kinetic design criteria. A significant retardation of conversion rate in the vicinity of the equilibrium was indicated, effectively narrowing the feasible composition range. Recommendations for the application of biomass-based syngas with iron-based oxygen carrier materials were provided.

Heat is still the largest energy end-use, accounting for about 50% of global final energy consumption in 2022 and contributing to 40% of global carbon dioxide (CO2) emissions. Regarding the heat supply of buildings, district heating plays an important role and is well-established in many countries. However, most of the district heating networks worldwide are still operated with supply temperatures of 70-120°C (medium-high temperature) often produced by caloric power plants. Solar district heating (SDH) systems can be a valuable alternative to decarbonize these systems. How this can be done most efficiently is investigated within the task 68 Efficient Solar District Heating Systems of the International Energy Agency (IEA) from the technology cooperation program – solar heating and cooling (SHC). This contribution presents the latest results of the task regarding comparison of different collector technologies, important digitalization aspects, analysis of available funding schemes and latest efficient SHD installations.

During transportation and storage of wood pellets various gases are formed leading to toxic atmosphere. Various influencing factors and measures reducing off-gassing have already been investigated. The present study aims at applying an antioxidant, acetylsalicylic acid (ASA), to reduce off-gassing from wood pellets by lowering wood extractives oxidation. Therefore, acetylsalicylic acid was applied in industrial and laboratory pelletizing processes. Pine and spruce sawdust (ratio 1:1) were pelletized with adding 0-0.8% (m/m) ASA. Glass flasks measurements confirmed off-gassing reduction by adding ASA for all wood pellets investigated.The biggest effect was achieved by adding 0.8% (m/m) ASA in the industrial pelletizing experiments where the emission of volatile organic compounds (VOC_tot) was reduced by 82% and a reduction of carbon monoxide (CO) and carbon dioxide (CO₂) emissions by 70% and 51%, respectively, could be achieved. Even an addition of 0.05% (m/m) ASA led to off-gassing reduction by >10%. A six week storage experiment to investigate the long-term effectivity of ASA addition revealed, that antioxidant addition was effective in reducing CO-, CO₂- and VOC_tot-release, especially during the first four weeks of the storage experiment, after which time the relative reduction effect was significantly decreased.

In this study, we investigated the emissions, including odor, from log wood stoves, burning wood types indigenous to mid-European countries such as Austria, Czech Republic, Hungary, Slovak Republic, Slovenia, Switzerland, as well as Baden-Württemberg and Bavaria (Germany) and South Tyrol (Italy). The investigations were performed with a modern, certified, 8 kW, manually fired log wood stove, and the results were compared to emissions from a modern 9 kW pellet stove. The examined wood types were deciduous species: black locust, black poplar, European hornbeam, European beech, pedunculate oak (also known as “common oak”), sessile oak, turkey oak and conifers: Austrian black pine, European larch, Norway spruce, Scots pine, silver fir, as well as hardwood briquettes. In addition, “garden biomass” such as pine cones, pine needles and dry leaves were burnt in the log wood stove. The pellet stove was fired with softwood pellets.

The composite average emission rates for log wood and briquettes were 2030 mg MJ⁻¹ for CO; 89 mg MJ⁻¹ for NO_x, 311 mg MJ⁻¹ for C_xH_y, 67 mg MJ⁻¹ for particulate matter PM₁₀ and average odor concentration was at 2430 OU m⁻³. CO, C_xH_y and PM₁₀ emissions from pellets combustion were lower by factors of 10, 13 and 3, while considering NO_x – comparable to the log wood emissions. Odor from pellets combustion was not detectable. CxHy and PM10 emissions from garden biomass (needles and leaves) burning were 10 times higher than for log wood, while CO and NO_x rise only slightly. Odor levels ranged from not detectable (pellets) to around 19,000 OU m⁻³ (dry leaves). The odor concentration correlated with CO, C_xH_y and PM₁₀. For log wood combustion average odor ranged from 536 OU m⁻³ for hornbeam to 5217 OU m⁻³ for fir, indicating a considerable influence of the wood type on odor concentration.

The increased biomass utilization leads to the need of an efficient and flexible usage of available sources. Therefore, it is necessary to combust low-cost biogenic residues, which inherently have higher nitrogen contents that lead to increased NOx emissions. In order to tackle this issue a new combustion technology with double air staging and flue gas recirculation is under development. The technology also features an increased fuel bed height and very low oxygen concentrations in the fuel bed to reduce fuel bed temperatures. This work focuses on the CFD simulation of the formation and reduction of NOx emissions of in a small scale boiler (35 kWth). Compared to previously applied models, major modification concerning the heat and mass transfer in the fuel bed as well as the subsequent conversion in the freeboard were made. The fuel bed is modelled via representative fuel particles with a Lagrangian approach and a thermally thick particle model considering intra-particle
gradients. Due to the increased fuel bed height and the relatively low oxygen concentration the formation and cracking of tars has to be considered in the simulation. This heavily influences the formation and reduction of NOx and its precursors. The fuel bound nitrogen is released via the particle model in the form of NO during char burnout and via a lumped tar species during pyrolysis. The cracking of the lumped tar species is modelled via two global gas phase reactions that releases the NOx precursors NH3 and HCN. The cracking reactions are added to a skeletal reaction mechanism with 28 species and 102 reactions that includes the fate of the N species. The simulation results are compared to experimental data from test runs with spruce wood chips and Miscanthus pellets as fuels. The comparison showed good agreement for the test runs with wood chips, where the temperature distribution inside the fuel bed and the released species above the fuel bed were predicted well. The test runs with Miscanthus showed a greater deviation between the measured and simulated values. For both fuels the NOx reduction that was experimentally observed in the secondary combustion zone could not be predicted with reasonable agreement. Therefore, it is necessary to further investigate the cracking of the tars and the subsequent formation of the NOx precursors. The presented work forms the basis for further improvements of the numerical models and subsequently the optimization of the new technology.

The presented grate firing system is a patented small scale screw burner, which is designed for high fuel flexibility. This work focuses on the numerical modelling of the boiler via CFD simulations. The in-house developed CFD models use an Euler – Lagrange approach to predict the thermal degradation of the fuel particles and the subsequent gas-phase reactions. The CFD models are validated with experimental data from a representative measurement campaign where the boiler is operated with softwood pellets and the composition of the flue gas is measured in the primary and secondary combustion zone as well as the boiler outlet. The simulation results agree well with the data acquired in the measurement campaigns.
Keywords: CFD, simulation, combustion, small scale application, wood pellet

With the increasing demand for lower emissions and innovative combustion technologies, it is necessary to have a reaction mechanisms that is accurate as well as computationally affordable for geometry and process optimization using computational fluid dynamics (CFD). The objective of this work is to explore the applicability of several reaction mechanisms in predicting NOx emissions from various combustion systems. This work focuses on the selection of suitable mechanisms from literature (see Table 1) in a full scale 3D model for the prediction of NOX especially for furnaces with low oxygen concentration in the fuel bed and enhanced reduction zones.

The present study examines the applicability of reaction kinetic mechanisms for predicting NOX emissions from biomass furnaces. These mechanisms are essential for numerical optimization of new innovative combustion technologies and therefore must be computationally affordable and provide reasonable accuracy in predicting NOX emissions. The selection of a suitable mechanism from literature is the goal of this work. The numerical investigations carried out utilized chemical reaction kinetic simulations with continuous stirred tank reactor networks. First, the predictions of a detailed benchmark mechanism are compared to experimental data and analyzed with regard to temperature, air-to-fuel equivalence ratio, residence time and producer gas composition. Then, various hybrid and reduced mechanisms are compared with the benchmark mechanism. The investigation showed a good agreement on the trends of NOX emissions from the detailed mechanism and measurements. The detailed mechanism can therefore be employed to find optimal operation windows in terms of temperature, air-to-fuel equivalence ratio and residence time. Benchmarking of the hybrid and reduced mechanisms showed large differences between the mechanisms. In conclusion, only one reduced mechanism is considered suitable for application in a full-scale 3D CFD simulation, which will be investigated in future studies.

A method for deriving kinetic models of gas–solid reactions for reactor and process design is presented. It is based on the nonparametric kinetics (NPK) method and resolves many of its shortcomings by applying tensor rank‐1 approximation methods. With this method, it is possible to derive kinetic models based on the general kinetic equation from any combination of experiments without additional a priori assumptions. The most notable improvements over the original method are that it is computationally much simpler and that it is not limited to two variables. Two algorithms for computing the rank‐1 approximation as well as a tailored initialization method are presented, and their performance is assessed. Formulae for the variance estimation of the solution values are derived to improve the accuracy of the model identification and to provide a tool for diagnosing the quality of the kinetic model. The methods effectiveness and performance are assessed by applying it to a simulated data set. A Matlab implementation is available as Supporting Information.

Pellet boilers and pellet stoves are widely used for heat production. But in most cases, only specific wood pellets with a low ash content are approved due to the increased risk of slagging and limited deashing capacity. The ash fusion test (AFT), according to prCEN/TS 15370-1, is currently the only standard method for the prediction of slagging. This method is not feasible for all biomass fuel types, since sometimes the characteristic temperatures cannot be determined or the characteristic shapes do not occur for temperature determination. Furthermore, the method is costly and requires complex instrumental infrastructure. Hence, a demand for more expressive or more rapid methods to characterize slag formation potential of fuels is often claimed. Based on a literature study, four such laboratory test methods were chosen, partly adapted, and then experimentally investigated. These methods included thermal treatment of the fuel itself or the ashes of the fuel and were the rapid slag test, CIEMAT, the slag analyzer, and the newly developed pellet ash and slag sieving assessment (PASSA) method. Method performance was practically assessed using 14 different biomass fuel pellets, which were mainly from different assortments of wood, but also herbaceous or other nonwoody fuels. The results from the tests with these four alternative methods were evaluated by comparing to both results from standard AFT and results from full-scale combustion tests performed over a maximum of 24 h. Seven different pellet boilers were assessed, of which one boiler was used to apply all 14 test fuels. According to the granulometric ash analysis (i.e., the ratio of >1 mm-fraction toward total ash formed), the sensitivity of the new test methods to depict slagging phenomena at a suitable level of differentiation was assessed. Satisfactory conformity of the boiler ash assessment (reference) was found for both, the slag analyzer and the PASSA method. The latter may, in particular, be seen as a promising and relatively simple low-input procedure, which can provide more real-life oriented test results for fixed-bed combustion. The standardized AFT could, however, not sufficiently predict the degree of slag actually formed in the reference boiler, particularly when only wood fuels are regarded.

Holzpellets werden in zunehmendem Maße aus Hackschnitzel hergestellt. Es ist davon auszugehen, dass diese Veränderung der Rohstoffbasis zu erhöhten Aschegehalten im Brennstoff führt und zu Schwierigkeiten bei der Nutzung führen kann. Die vorliegende Arbeit kommt zum Schluss, dass moderate Anteile (< 5%) sauberer Rinde zu keinen wesentlichen Verschlackungen führen. Bei Verunreinigung oder / und sehr hohen Rindenanteilen ist mit
Verschlackungsproblemen jedenfalls zu rechnen.

The release of potassium during biomass combustion leads to several problems as the emissions of particle matter or formation of deposits. K release is mainly described in literature in a qualitative way and this work aims to develop a simplified model to quantitatively describe it at different stages. The proposed model has 4 reactions and 5 solid species, describing K release in 3 steps; during pyrolysis, KCl evaporation and carbonate dissociation. This release model is coupled into a single particle model and successfully validated with experiments conducted in a single particle reactor with spruce, straw and Miscanthus pellets at different temperatures. The model employs same kinetic parameters for the reactions in all cases, while different product compositions of the reactions are employed for each fuel, which is attributed to differences in composition. The proposed model correctly predicts the online release at different stages during conversion as well as the final release for each case.

For many fluidized bed applications, the particle movement inside the reactor is accompanied by reactions at the particle scale. The current study presents for the first time in literature a multi-scale modelling approach coupling a one-dimensional volumetric particle model with the dense discrete phase model (DDPM) of ANSYS Fluent via user defined functions. To validate the developed modelling approach, the current study uses experimental data of pressure drop, temperature and gas composition obtained with a lab-scale bubbling fluidized bed biomass gasifier. Therefore, a particle model developed previously for pyrolysis was modified implementing a heat transfer model valid for fluidized bed conditions as well as kinetics for char gasification taken from literature. The kinetic theory of granular flow is used to describe particle–particle interactions allowing for feasible calculation times at the reactor level whereas an optimized solver is employed to guarantee a fast solution at the particle level. A newly developed initialization routine uses an initial bed of reacting particles at different states of conversion calculated previously with a standalone version of the particle model. This allows to start the simulation at conditions very close to stable operation of the reactor. A coupled multi-scale simulation of over 30 s of process time employing 300.000 inert bed parcels and about 25.000 reacting fuel parcels showed good agreement with experimental data at a feasible calculation time. Furthermore, the developed approach allows for an in-depth analysis of the processes inside the reactor allowing to track individual reacting particles while resolving gradients inside the particle.

Fluidized bed biomass gasification is a complex process whereby gas source terms are released by reactions at the particle level during the movement of fuel particles throughout the reactor. The current study presents for the first time the application of a multi-scale modelling approach for a fluidized bed biomass gasifier of industrial size, coupling a detailed one-dimensional particle model based on the progressive conversion model (PCM) with a commercial CFD software. Results of particle movement and gas source terms are compared with results of an additional simulation employing the simplified uniform conversion model (UCM) which is commonly used in literature. Validation at the particle level showed that the UCM leads to a massive underprediction of the time needed for pyrolysis whereas the PCM is in good agreement with experimental data. This heavily influences the gas sources released during pyrolysis of the biomass particles in the coupled reactor simulations. Volatiles are much more concentrated to the close proximity of the fuel feed when using the UCM whereas the PCM leads to a more homogeneous distribution over the reactor cross-section. The calculation time analysis of the coupled simulations showed that despite the increased complexity, the PCM shows only an increase of 20% in calculation time when compared to the UCM, whereas it is much better suited for these conditions. The coupled multi-scale simulations using the PCM showed the numerical feasibility of the modelling approach for 1,200,000 bed parcels and about 80,000 reacting fuel parcels and furthermore highlighted the importance of a comprehensive description of the particle level.

A transient 3D model for two main zones, namely the fuel bed and the freeboard, of biomass packed bed combustion systems was developed. It integrates the models for the biomass conversion sub-processes and solves the governing equations for the gas and solid phase and their interactions. The intra-particle gradients are included by considering the biomass particles as thermally thick particles. The shrinkage of the packed bed and the variations of the bed porosity due to the uneven consumption of the fuel are taken into account. Detailed kinetic mechanisms are used for the simulation of homogeneous gas phase reactions. To verify the model and to increase the understanding of packed bed combustion, laboratory-scale fixed-bed batch experiments have been performed in a reactor with 9.5 cm diameter and 10 cm length. The model performance was extensively validated with gas phase measurements (CO, CO₂, CH₄, H₂, H₂O and O₂) above the fuel bed, temperatures at different heights in the bed and in the freeboard, and the propagation rate of reaction front. The simulation results are in a good agreement with the measured values. © 2014 Elsevier Ltd. All rights reserved.

The use of renewable-energy-based heat producers within district heating grids is getting more and more popular. In order to benefit from the advantages and compensate for the different disadvantages of the various types of heat producers powered by renewable energy sources like biomass, solar energy or waste heat, a combination of these systems could be favoured over using, for example, only one main biomass-based boiler. Furthermore , in many cases, the additional use of buffer storages is necessary to fully benefit from the use of these kinds of heat producers. A major challenge with such multi-producer heating grids is the cost optimal management of all heat producers and buffer storages. Therefore , a high-level control strategy is necessary, which is able to plan ahead the use of slowly reacting and/or weather dependent heat producers while minimizing operational costs and pollutant emissions. This article shows the development of a linear model predictive controller (MPC) for a district heating grid with several (renewable) decentralized heat producers and heat storages. In order to provide the MPC with the required forecast of the future heat demand, an adaptive load forecasting method has been designed. Additionally, in order to be able to incorporate solar panels, the MPC needs to have a forecast of their possible future heat output. Therefore, a physically motivated solar yield forecasting method has been designed. The required prediction models for the MPC were represented by so-called mixed logical dynamical (MLD) system models. MLD system models combine the modelling power of discrete state system models (finite state machines) and discrete time system models by the extension of the regular linear state-space system model approach with integer and continuous auxiliary variables and linear inequality constraints. The occurrence of both integer and continuous variables within the resulting optimization problem of the MPC leads to a mixed-integer linear program (MILP), which can be solved efficiently using modern MILP solvers. The resulting control strategy is tested in a thermo-hydraulic simulation environment of an actual small-scale multi-producer district heating grid consisting of a medium-scale wood chip boiler with buffer storage, a solar collector with buffer storage and a high temperature heat pump, an oil boiler and 25 heat consumers. Additionally, a state observer was designed and connected with the MPC in order to detect control errors and to incorporate feedback from the heat producers and the buffer storages. The simulations have indicated that the designed MPC and the state observer work properly. Therefore, these elements have been implemented on-site on the actual heating grid, with the first test run scheduled for October 2017.
Modellprädiktive Regelung eines solar-und biomassebasierten Fernwärmenetzes | Request PDF. Available from: https://www.researchgate.net/publication/321314304_Modellpradiktive_Regelung_eines_solar-und_biomassebasierten_Fernwarmenetzes [accessed Feb 21 2018].

A new mathematical model for the grate combustion of biomass has been derived from physical considerations. Various models for grate combustion can already be found in the literature. Usually their intention is to simulate the real situation in a furnace as precisely as possible. Hence they are very detailed, typically consisting of many partial differential equations. However, because of their complexity they are useless for control purposes. The new model is very simple, consisting of only two ordinary differential equations, which makes it particularly suitable as a basis for model based control strategies. To verify the model, experiments were performed at a pilot scale furnace with horizontally moving grate. The pilot plant is a downscaled version (180 kW_th) of a typical medium scale furnace in terms of geometry and instrumentation. Comparison of the measured and calculated values shows good agreement. © 2009 Elsevier Ltd. All rights reserved.

 Im Bereich der thermischen Biomassenutzung (speziell Rostfeuerungen) werden CFD-Simulationen eingesetzt, um Hilfestellung bei der Diagnose und Lösung von Betriebsproblemen zu leisten sowie bei der Entwicklung von neuen Feuerungen und Kesseln zu unterstützen. Zurzeit sind keine Modelle verfügbar, mit denen sowohl die Vorgänge im Brennstoffbett als auch in der Gasphase einer Biomasse-Rostfeuerung mit Hilfe von detaillierten numerischen Modellen bei akzeptabler Berechungszeit simuliert werden können. Um die direkte Kopplung des Bett-Modells mit der Gasphase zu bewerkstelligen, ist es nötig, ein geeignetes Partikel-Modell zu entwickeln, welches die thermische Konversion (Trocknung, Pyrolyse und Holzkohle-Ausbrand) von thermisch dicken Biomassepartikeln beschreibt und mit bereits vorhandenen CFD-Modellen für die Gasphasensimulation gekoppelt werden kann. In diesem Schalenmodell werden die einzelnen Biomassepartikel als thermisch dick behandelt, d.h. die Temperaturgradienten in den einzelnen Partikeln sowie der gleichzeitige Ablauf mehrerer Umwandlungsprozesse berücksichtigt. Das Schalenmodell wurde mit Hilfe von gemessenen Partikeloberflächen- und -zentrumstemperaturen sowie mit Messwerten des Gesamtmasseverlustes während der Verbrennung in einem Einzel-Partikelreaktor validiert. Ein weiteres Problem, das bei der Simulation von Biomasse-Rostfeuerungen auftritt, ist die Modellierung der Gas-Festkörper-Mehrphasenströmung. Das Modell muss dabei in der Lage sein, den Einfluss der Partikel-Partikel-Wechselwirkung währenden der Partikelbewegung am Rost korrekt zu beschreiben. Aus diesem Grund wurde durch Kopplung von Euler- und Lagrange Mehrphasenströmungs- Ansätzen ein neues, dreidimensionales Schüttungsmodell entwickelt. Dabei wird die Partikelbewegung am Rost mit Hilfe eines Euler-Ansatzes (Euler-Granular-Modell) beschrieben, während die thermische Umwandlung der Biomassepartikel mit Hilfe eines Lagrange-Ansatzes und dem entwickelten Einzelpartikelmodell beschrieben wird. Das 3D-Festbettmodell für Biomasserostfeuerungen wurde eingesetzt, um eine 20 kW Biomasse-Unterschubfeuerung zu simulieren. Da es keine experimentelle Daten hinsichtlich der Bedingungen im Brennstoffbett gab, wurden qualitative Informationen hinsichtlich der Positionen der Trocknungs-, Pyrolyse- und Holzkohle-Ausbrandzonen, sowie mit Thermoelementen gemessenen Rauchgastemperaturen an verschiedenen Positionen in der Brennkammer zum Vergleich mit den Simulationsergebnissen herangezogen. Des Weiteren erfolgte im Zuge dieser Arbeit eine Weiterentwicklung des Festbett-Modells, indem der Strahlungsaustausch zwischen den Partikeln sowie detaillierte kinetische Modelle für die Gasphasenverbrennung im Modell implementiert wurden. Das weiterentwickelte Modell wurde mit Hilfe von experimentellen Daten aus Testläufen in einem Festbett-Laborreaktor validiert. Diese Messdaten beinhalten gemessene Konzentrationen von CO, CO2, CH4, H2, H2O und O2 im Rauchgas über dem Brennstoffbett sowie Temperaturen in unterschiedlichen Positionen im Bett und über dem Bett. Die vorhergesagten Werte zeigten eine gute Übereinstimmung mit den gemessenen Werten.

Primary devolatilization and the exothermic heterogeneous secondary charring of the primary volatiles need to be described in a consistent manner in order to correctly predict the heat of reaction of biomass pyrolysis. Detailed reaction schemes can currently predict mass loss and product composition of biomass pyrolysis with good accuracy, but have a weakness in the description of the heat of reaction. In this work it is shown for the first time that including secondary charring reactions a detailed reaction scheme can predict the evolution of the heat of pyrolysis for different conditions. The enthalpy of reaction is calculated for each reaction as the difference between the net calorific value of reactants and products. The presented model is able to describe the heat evolution in micro-TGA-DSC experiments conducted without a lid, where pyrolysis is endothermic, and with a lid, where secondary reactions are enhanced and the global heat of reaction shifts to exothermic. Furthermore, when it is coupled to a particle model, it correctly describes single particle pyrolysis experiments conducted with beech spheres where there is a remarkably exothermic peak in the centre temperature.

Fixed-bed biomass conversion with a low primary air ratio and a counter-current configuration has a high feedstock flexibility, as it resembles updraft gasification, and the potential to reduce emissions when integrated in biomass combustion systems. A 1D bed model was validated with experimental results from a biomass combustion boiler with such a bed conversion system, predicting with a good accuracy the temperatures in the reactor and producer gas composition. The model was applied for different cases to investigate the fuel flexibility of this combustion system, including the influence of moisture content and the maximum temperatures achieved in the bed. It was shown that with variations in fuel moisture content from 8 to 30% mass w.b. the producer gas composition, char reduction to CO or maximum temperatures at the grate were not affected due to the separation of the char conversion and pyrolysis/drying zones. Flue gas recirculation was the only possible measure with the tested configuration to reduce the maximum temperatures close to the grate, which is beneficial e.g. to avoid slagging with complicated fuels. A higher tar content was obtained than in conventional updraft gasifiers, which is attributed to the absence of tar condensation in the bed due to the limited height of the reactor and the integration in the combustion chamber. The presented model can support the development of such combustion technologies and is a relevant basis for detailed CFD simulations of the bed or gas phase conversion.

Heat makes up the largest share of energy end-use, accounting for 50% of global final energy consumption in 2018 and contributing to about 40% of global carbon dioxide (CO2) emissions. Of the total heat produced, about 46% was consumed in buildings for space and water heating. Large-scale solar thermal systems provide a highly valuable possibility to increase the share of renewables in heating systems and to reduce carbon dioxide emissions. In this context, the worldwide number of large-scale solar heating systems has increased rapidly in the last couple of years, especially in China and European countries, e.g. in Denmark. This has led to the installation of about 400 large-scale solar thermal systems ( ≥ 350kWth, 500m²) by the end of 2019.
Unlike other heating systems, their main source of power (solar radiation) cannot be manipulated and is subject to changes on a seasonal as well as on a daily basis. That is why control systems play a very important role for the efficient operation of these systems. This thesis therefore focuses on the application of model-based control strategies, and the necessary preliminary work regarding modelling, in order to achieve an efficient control of large-scale solar thermal systems. Consequently, the thesis addresses three important aspects:
In the first main section, models of components of large-scale solar thermal systems are developed and validated. For the most important components (heat exchanger, solar collector and sensible heat storage), two models of different complexity, one simulation-oriented, one control-oriented, are developed. While the simulation-oriented models aim to model the physical behaviour very accurately in order to be used in simulation studies, control-oriented models aim to model the physical behaviour only as accurately as necessary in order to serve as a basis for model-based control strategies. All models are validated with measurement data from a typical solar system, and it is shown that they are sufficiently accurate for their intended purpose. The sum of the models provides a holistic view on all modelling aspects that have to be considered in large-scale solar thermal plants, and serves as a reasonable basis for model-based control strategies and accurate simulation studies of solar systems.
In the second main section, adaptive forecasting methods for the future solar heat production as well as the heat demand are developed and validated with measurement data and using real weather forecasts. These methods are important to most efficiently integrate and operate solar systems by better scheduling heat production, storage and distribution for the near future. In order to be used in real-world applications, the methods are developed with the goal to meet three important practical requirements: simple implementation, automatic adaption to seasonal changes, and wide applicability. The final long-term evaluation for half a year proves that the developed methods can forecast the solar heat production as well as the heat demand very accurately and outperform common forecasting methods, yielding results that are nearly twice as accurate.
In the third main section, model-based control strategies for the high-level as well as for the low-level control of solar thermal systems are developed and validated. For the high-level control an approach is presented which considers future information by using the developed forecasting methods. It achieves higher profits (plus 3 %) and leads to a more stable operation, compared to the existing commercial solution. For the low-level control, model-based control strategies based on the developed models for the heat generation and distribution are presented. The model-based control strategy for the heat generation considers the dynamic behaviour of the collector and especially considers the variable time-delay. This, compared to conventional control strategies, leads to a significantly better control performance in case of fluctuating solar radiation and changing inlet temperatures. The model-based control strategy for the heat distribution follows a modular approach which can be applied for several hydraulic settings, leading to an accurate and independent control of mass flow and temperature, and outperforms state-of-the-art control strategies. For both control levels, care was taken that the applied strategies can be used in real-world applications regarding their mathematical complexity and computational resources required.
In summary, this thesis presents a holistic approach regarding modelling (simulation-oriented models, control-oriented models and adaptive forecasting methods) and control aspects (high-level as well as low-level control) which can help to improve the efficiency of large-scale solar thermal plants on various levels, making them more competitive, and is furthermore essential for a successful integration of these plants in larger energy systems.

Die Verbrennung fester Biomasse gewinnt als nachhaltige Form der Energieerzeugung stetig an Bedeutung. Eine mögliche Technologie stellen dabei Biomasse-Thermoölkesselanlagen dar, deren Regelungen bis jetzt noch nicht auf einem mathematischen Modell basieren und dementsprechend deren verkoppeltes und zum Teil nichtlineares Verhalten nur ungenügend berücksichtigen. Ziel dieser Arbeit ist es, ein für Biomassefeuerungsanlagen mit Wasserkesseln existierendes Modell sowie die darauf aufbauende Regelungsstrategie an die speziellen Gegebenheiten von Thermoölkesselanlagen anzupassen. Dazu wird zunächst ein einfaches Modell für Thermoölwärmeübertrager auf Basis einer Energiebilanz hergeleitet und anhand von verfügbaren Betriebsdaten qualitativ verifiziert. Anschließend wird die bei der Regelung von Wasserkesselanlagen eingesetzte Eingangs-Ausgangslinearisierung verallgemeinert. Darauf aufbauend wird eine Regelungsstrategie zur Regelung des Thermoölwärmeübertragers hergeleitet. Die Leistungsfähigkeit des Regelungskonzeptes wird schließlich in Simulationsstudien gezeigt. 

Die vorliegende Arbeit widmet sich der Herleitung mathematischer Simulationsmodelle eines Pufferspeichers, eines Solarkollektors sowie eines Plattenwärmeübertragers. Dabei wird das Simulationsmodell des Pufferspeichers anhand eines am Markt verfügbaren Pufferspeichers entwickelt. Die mathematischen Beschreibungen der Simulationsmodelle basieren auf einer partiellen Differentialgleichung zur Beschreibung der Wärmeübertragung in einem durchströmten zylindrischen Rohr. Nach dem Erhalt der mathematischen Modelle werden diese mit einem impliziten Lösungsverfahren numerisch gelöst. Anschließend werden die experimentell zu ermittelnden Parameter des Pufferspeichermodells anhand gezielt durchgeführter Versuche bestimmt. Nach dem Ermitteln der Parameter wird das Simulationsmodell des Pufferspeichers mit einem weiteren Versuch experimentell verifiziert. Schlussendlich bildet das mathematische Modell des Pufferspeichers den untersuchten Pufferspeicher sehr zufriedenstellend ab, womit ein Simulationsmodell vorliegt, das gezielte Untersuchungen ohne aufwändige Versuche ermöglicht. Abschließend wird eine Regelung für die Wärmeübertragung aus dem Solarkollektor in den Pufferspeicher entwickelt. Dabei werden zwei in der Praxis übliche Verfahren untersucht. Bei der ersten Variante erfolgt die Übertragung der Wärme in den Pufferspeicher über ein im Pufferspeicher integriertes Solarregister. Bei der zweiten Variante erfolgt die Übertragung der Wärme über einen Plattenwärmeübertrager vom Wasser-Frostschutzgemisch auf Wasser, welches dann direkt in den Pufferspeicher eingespeist wird. Als Reglerstruktur wird in beiden Fällen ein Standard-Regelkreis mit einer statischen Vorsteuerung verwendet. Anhand von Simulationsstudien werden zunächst die Parameter des PI-Reglers festgelegt und in weiterer Folge die mit der jeweiligen Variante resultierenden Temperaturverläufe des Wassers im Pufferspeicher untersucht und gegenübergestellt. Dabei stellt sich heraus, dass die Temperatur des Wassers im Pufferspeicher, bei gleich bleibender Strahlungsstromdichte der Solarstrahlung Igauf den Solarkollektor, die gewünschte Solltemperatur bei Wärmeübertragung mittels Plattenwärmeübertrager schneller erreicht, als bei Wärmeübertragung durch das Solarregister. Darüber hinaus ermöglicht die Verwendung des Plattenwärmeübertragers eine Schichtung der Temperatur des Wassers im Pufferspeicher und somit eine Speicherung der Wärme auf einen höheren Temperaturniveau.

For an appropriate operation of a heat exchanger it is very helpful to know its dynamic behaviour. To this a simple sufficient accurate nonlinear model for the description of the dynamic behaviour is derived on the basis of a gas tube heat exchanger. Due to the general approach used for the derivation the model could be adaptet easily for other types of heat exchangers. The presented model can be used to estimate not measured physical values, to monitor the deposit formation in the heat exchanger and as a basis for the design of a model based control strategy. © Oldenbourg Wissenschaftsverlag.

Scheitholzkessel sind die in Europa immer noch am stärksten verbreitete Form von Holz-basierten Zentralheizungssystemen. Der Bestand ist überaltert und weist die größten Anteile an den verursachten Schadstoffemissionen aus Festbrennstoffzentralheizungssystemen auf. Das Ziel des Projektes, die komplette Neuentwicklung einer modellbasierten Regelung für Scheitholzkessel mit Pufferspeichern und einer Solaranlage, stellte einen Technologie-sprung in Richtung einer drastischen Reduktion der Schadstoffemissionen (CO, org. C, Fein-staub) bei gleichzeitiger Erhöhung des Nutzungsgrades und Benutzerkomforts dar. Dabei erfolgte sowohl die übergeordnete Regelung des Zusammenspiels der Komponenten (Systemregelung) als auch die Regelung der einzelnen Komponenten (Feuerungsregelung, Hydraulikregelung) modellbasiert. Die neue Regelung basiert auf einer gezielten Interaktion mit dem Benutzer, in welcher der Benutzer zielgerichtet zum Nachlegen einer bestimmten Brennstoffmenge in einem bestimmten Zeitraum aufgefordert wird. Zusätzlich dazu werden alle Teilprozesse (Verbrennung des Scheitholzes, Übertragung der Wärme in den Pufferspeicher, usw.) modellbasiert und damit deutlich effizienter und genauer geregelt. Im Fall der Feuerungsregelung wurde zusätzlich zur modellbasierten Regelung von Vorlauf-temperatur und Sauerstoffgehalt auch eine innovative CO-l-Regelung eingesetzt, die basierend auf einer kontinuierlichen Schätzung der CO- l-Charakteristik unter Verwendung eines kombinierten Sensors zur Sauerstoffmessung und Detektion unverbrannter Kompo-nenten stets einen für den aktuellen Betriebszustand optimalen Sollwert für den Sauer-stoffgehalt vorgibt. Die laufende Anpassung des Sauerstoffgehaltes führt zu einer deutlichen Reduktion der Schadstoffemissionen (CO, org. C, Feinstaub). Zum Erreichen dieser Ziele wurden im Wesentlichen folgende Schritte durchgeführt:

• Experimentelle Untersuchung und Modellierung des Abbrandverhaltens von Scheitholz (inklusive der CO-l-Charakteristik)
• Entwicklung einer übergeordneten modellbasierten Systemregelung
• Entwicklung einer modellbasierten Feuerungsregelung (inkl. CO-l-Regelung) für einen effizienten und schadstoffarmen Betrieb des Scheitholkessels
• Experimentelle Bewertung des Potentials der modellbasierten Regelung
• Analyse der Anforderungen zur Anpassung der Regelung an andere Konfigurationen

Das beantragte Projekt leistete somit einen entscheidenden Beitrag zum Ausschreibungs-schwerpunkt „Effiziente und emissionsarme Klein- und Kleinstfeuerungen durch Integration einer intelligenten Verbrennungs- und Leistungsregelung“ und ging zusätzlich explizit auf die im Ausschreibungsleitfaden adressierte Verwendung von kombinierten Sensorsystemen wie CO- l-Sensorsysteme zur Verbrennungsregelung ein. Dabei ist insbesondere hervorzuheben, dass der durchdachte Ansatz das Sensorsignal zu Schätzung der CO- l-Charakteristik zu verwenden den wesentlichen Vorteil mit sich bringt, dass die exakte Messung der CO-Emissionen durch den Sensor nicht erforderlich ist, sondern es ausreicht, wenn dieser die Tendenzen richtig wiedergibt.

Die saubere und effiziente Verbrennung von Müll stellt, insbesondere aufgrund der typischerweise stark inhomogenen Brennstoffzusammensetzung, eine große Herausforderung dar. Eine effektive Maßnahme dieser Problematik zu begegnen, ist der Einsatz geeigneter Methoden zur Prozessregelung. In diesem Artikel wird daher eine neue Methode zur modellbasierten Regelung des produzierten Dampfmassenstromes in einer Wirbelschichtmüllverbrennungsanlage vorgestellt. Diese beinhaltet als Herzstück einen Softsensor, welcher den Rauchgasmassenstrom aus vorhandenen Messgrößen online schätzt. Durch die zusätzliche Kenntnis dieser wichtigen Prozessgröße kann die Regelgüte deutlich verbessert werden. Zusätzlich zeigt sich eine stabilisierende Wirkung auf die Reaktorkopftemperatur, wodurch die thermische Belastung des Schamotts verringert werden kann.

Three estimators for the estimation of the flue gas mass flow in biomass boilers are presented and compared, namely a sliding-mode observer, a Kalman filter, and a so-called steady-state estimator. The flue gas mass flow is an important process variable in biomass boilers as it contains information about the supplied mass flows of air and decomposed fuel. It is also related to the generated heat flow. Furthermore, its knowledge may be exploited in model-based control strategies which allow one to keep pollutant emissions low, on the one hand, and to achieve high efficiency, on the other hand. However, due to fouling of the equipment over time, measurements and existing estimation methods are not suitable for long-term applications. The estimators proposed in this article are based on a dynamic model for gas tube heat exchangers. They are capable of handling the fouling of the heat exchanger and, additionally, they offer the possibility of monitoring the degree of fouling. By incorporating an additional differential pressure measurement and extending the aforementioned estimators, an improvement regarding the dynamic response and the estimation accuracy is achieved. The application of the estimators to real measurement data from both, a medium-scale and a small-scale biomass boiler, demonstrates their wide applicability.

The integration of solar thermal plants into district heating grids requires advanced control strategies in order to utilize the full potential in terms of efficiency and least operating effort. State-of-the-art control strategies cannot completely fulfil this since they are not able to consider the physical characteristics of the different components, nor do they take information on future conditions and requirements into account properly. A promising attempt for improvement is the application of model-based control strategies together with practicable forecasting methods for both the solar yield as well as the heat demand. This contribution will present the results of several projects performed on the development of suitable mathematical models, forecasting methods and control strategies relevant for the integration of solar thermal plants into district heating grids.

With the share of renewable energy sources increasing in heating and hot water applications, the role of hydraulic heat distribution systems is becoming more and more important. This is due to the fact that in order to compensate for the often fluctuating behaviour of the renewables a flexible heat transfer must be ensured by these distribution systems while also taking the optimal operating conditions (mass flow, temperature) of the individual components into consideration. This demanding task can be accomplished by independently controlling the two physical quantities mass flow and temperature. However, since there exists an intrinsic nonlinear coupling between these quantities this challenge cannot be handled sufficiently by decoupled linear PI controllers which are currently state-of-the-art in the heating sector. For this reason this paper presents a model-based control strategy which allows a decoupled control of mass flow and temperature. The strategy is based on a systematic design approach from models described in this contribution, which are validated by commercially available components from which most of them can be parametrized by the data sheet. The control strategy is designed for a typical hydraulic configuration used in heating systems, which will allow the accurate tracking of the desired trajectories for mass flows, temperatures and consequently heat flows. The controllers are validated experimentally and compared to well-tuned state-of-the-art (PI) controllers in order to illustrate their superiority and prove their decoupling of the control of mass flow and temperature in real world applications.

Absorption heat pumping systems (AHPSs, comprising absorption heat pumps and chillers) are devices that mainly use thermal energy instead of electricity to generate heating and cooling. This thermal energy can be provided by, e.g., waste heat or renewable energy sources such as solar energy, which allow AHPSs to contribute to ressource-efficient heating and cooling systems. Despite this benefit, AHPSs are still not a widespread technology. One reason for this is unsatisfactory controllability under varying operating conditions, which results in poor modulation and partial load capability. Emloying model-based control is a promising approach to address this issue, which will be the focus of this  contribution.
First, a viable control-oriented model for AHPSs is developed. It is based on physical correlations to facilitate systematic adaptions to different scales and operating conditions and considers only the most relevant mass and energy stores to keep the model order at a minimum. The resulting model is mathematically simple but still has the structure of a nonlinear differential-algebraic system of equations. This is typical for models of thermo-chemical
processes, but is unfortunately not suitable for many control design methods. Therefore, linearization at an operating point is discussed to derive a model in linear state space representation. Experimental validation results show that the linearized model does have slightly worse steady-state accuracy than the nonlinear model, but that the dynamic accuracy seems to be almost unaffected by the linearization and is considered sufficiently good to be used in control design.
As a next step, the linearized model is used to design model-based control strategies for AHPSs. A special focus is put on redundantly-actuated configurations, i.e. configurations with more manipulated variables than controlled variables, which allows using additional degrees of freedom to extend the operating range of AHPS and hence improve their partial load capability. Two model-based control approaches are discussed: First, a linear model predictive control (MPC) approach is presented - a well-established and generally easy-to-parameterize approach, which, however, often results in high computational effort prohibitive to its implementation on a conventional PLC. Therefore, a second control approach based on state feedback is presented which is mathematically simple enough for implementation on a conventional PLC. It consists of an observer for state variables and unknown disturbances, a state feedback controller and, in case of redundantly-actuated configurations, a dynamic control allocation algorithm. Both approaches are experimentally validated and compared to a state-of-the art control approach based on SISO PI control, showing that the model-based MIMO control approaches allow for a wider operating range and hence better modulation and partial load capability compared to the SISO PI approach. This, in turn, reduces ON/OFF operation of AHPSs and also facilitates their integration into complex energy systems to generate heating and cooling in a ressource-efficient manner.

Absorption heat pumping devices (AHPDs, comprising heat pumps and chillers) can provide heating and cooling in a resource-efficient manner. However, their perceived complexity has limited their widespread application. This contribution shows how mathematical models, systematically capturing this complexity, can be used for model-based control of AHPDs (on the device-level for model-predictive or state feedback control and on the system-level for optimisation-based energy management systems) to facilitate their integration into energy systems, and discusses an exemplary application to solar cooling systems.

Absorptionswärmepumpenanlagen (AWPA, beinhaltet Absorptionswärmepumpen und –kältemaschinen), sind Anlagen, die hauptsächlich thermische statt elektrischer Energie nutzen, um Wärme und Kälte zu generieren. Dadurch wird die Nutzung von Abwärme und erneuerbaren Energiequellen wie Solarenergie in Heiz- und Kühlsystemen erleichtert. Trotz dieses Vorteils ist der Einsatz von AWPA nach wie vor stark eingeschränkt. Ein Grund dafür ist das Fehlen von Regelungsstrategien, die eine zufriedenstellende Regelgüte über einen weiten Betriebsbereich, insbesondere unter Teillast, bieten. Deshalb befasst sich diese Arbeit mit der Entwicklung eines neuen, modellbasierten Regelungsansatzes für AWPA, die den Betriebsbereich durch den Einsatz von Mehrgrößen-Regelungsmethoden (multi-input-multi-output (MIMO) Regelungsmethoden) erweitern kann.



Zunächst wird ein geeignetes dynamisches Modell abgeleitet, das im modellbasierten Regelungsansatz verwendet werden soll. Es handelt sich um ein physikalisch basiertes Modell mit modularer Struktur, was eine systematische Anpassung an verschiedene AWPA erleichtert. Um die Anzahl der Zustandsvariablen niedrig zu halten, werden nur diejenigen Masse- und Energiespeicher berücksichtigt, die zu Zeitkonstanten und Totzeiten führen, die für die spätere Regelungsaufgabe relevant sind. Das entwickelte Modell ist mathematisch einfach, hat jedoch die Struktur eines nichtlinearen differential-algebraischen Gleichungssystems. Als solches ist es sehr gut als Simulationsmodell geeignet um verschiedene Regelungsstrategien in der Simulation zu testen, aber es ist zu komplex für viele modellbasierte Regelungsmethoden. Um eine noch einfachere Modellstruktur zu erhalten, wird das Modell an einem Betriebspunkt linearisiert, was auf ein Modell in linearer Zustandsraumdarstellung führt. Die entwickelten nichtlinearen und linearen Modelle werden experimentell validiert und mit zwei alternativen Modellierungsansätzen als Benchmark verglichen. Ein Vergleich zwischen dem abgeleiteten nichtlinearen Modell und den Benchmark-Modellen zeigt eine höhere Genauigkeit für das neue Modell, sowohl stationär als auch dynamisch. Ein Vergleich zwischen dem abgeleiteten nichtlinearen und dem linearisierten Modell zeigt, dass das linearisierte Modell zwar eine etwas schlechtere stationäre Genauigkeit aufweist, die dynamische Genauigkeit jedoch durch die Linearisierung nahezu unbeeinflusst zu sein scheint. Das vorgestellte neue linearisierte AWPA -Modell gilt daher als geeignet, als Grundlage für den Entwurf des modellbasierten Regelansatzes verwendet zu werden.



Als nächstes wird dieses Modell verwendet, um einen neuen modellbasierten Regelungsansatz für AWPA zu entwerfen. Der neue Regelungsansatz kann für verschiedene AWPA-Anwendungen und damit für verschiedene Regelungskonfigurationen verwendet werden, d.h., verschiedene Kombinationen von Stell- und Regelgrößen. Er kann auch für redundante aktuierte Konfigurationen mit mehr Stell- als Regelgrößen verwendet werden, was die Erweiterung des Betriebsbereichs einer AWPA ermöglicht. Der Ansatz besteht aus einem Beobachter für die Zustandsvariablen und unbekannte Störgrößen, einem Zustandsregler und, im Falle von redundant aktuierten Konfigurationen, einem Algorithmus zur dynamischen Stellgrößenverteilung. Der vorgeschlagene Regelungsansatz wird experimentell für zwei verschiedene Regelungskonfigurationen validiert und mit zwei Benchmark-Ansätzen verglichen – einem Eingrößen-PI-Regler (Single-input-single-output (SISO) PI-Regler), der den Stand der Technik repräsentiert, und einem modellprädiktiven Regelungsansatz (model predictive control, MPC) als alternative fortschrittliche Regelungsmethode. Die experimentelle Validierung zeigt, dass die beiden MIMO-Regelungsansätze (der vorgeschlagene Zustandsregler und der MPC-Ansatz) einen erweiterten Betriebsbereich und somit eine bessere Teillastfähigkeit im Vergleich zum SISO-PI-Regler ermöglichen. Während MPC durch die Notwendigkeit zur kontinuierlichen Lösung eines Optimierungsproblems im Allgemeinen eine vergleichsweise hohe Rechenleistung benötigt, ist der vorgeschlagene Zustandsregler-Ansatz mathematisch einfach genug, um auf herkömmlichen speicherprogrammierbaren Steuerungen für AWPA implementiert werden zu können. Er wird daher als vielversprechender neuer Regelungsansatz für AWPA betrachtet, der die Möglichkeit bietet, ihren Betriebsbereich zu erweitern und ihre Teillastfähigkeit zu verbessern, was wiederum eine einfachere Einbindung in moderne Energiesysteme ermöglicht und somit die Nutzung nachhaltiger Wärmequellen für Heizen und Kühlen erleichtert.

Optimization-based energy management systems (EMS) are a high-level control approach for energy systems like district heating networks. A descriptive model and objective function are required to solve an optimization problem and apply the resulting schedule in a receding horizon fashion. EMS for buildings require a simplified model of each thermal zone, and the objective function includes costs for heating and cooling, virtual costs, and a comfort model. Feedback from users is necessary since thermal comfort varies among individuals.

To influence the combustion process of modern biomass furnaces specifically the combustion-controller determines the necessary mass flows. The gaseous mass flows can be adjusted by fans and flaps. To ensure the desired overall performance of the furnace the mass flows need to be set by inner control loops respectively. Within the work described in this paper a model based approach for the control design of the inner control loop is presented exemplarily for the secondary air supply. Thereby a flatness-based feedforward control will be designed by means of an appropriate model. © 2014 Oldenbourg Wissenschaftsverlag GmbH.

Because of increased efforts to reduce CO₂ emissions a significant step in the development of small-scale (residential) biomass boilers for space heating has been achieved in recent years. Currently, the full potential for low-emission operation at high efficiencies, which is in principle possible due to optimized furnace geometries as well as combustion air staging strategies, cannot be exploited since there is still the need to enhance the controllers applied. For this reason, a model based control strategy for small-scale biomass boilers was developed and successfully implemented in a commercially available system. Thereby, appropriate mathematical models were developed for all relevant parts of the furnace and connected to an overall model subsequently used for the control unit design. The resulting controller is based on the input–output linearization and the state variables are estimated by an extended Kalman filter. Finally, the new control was implemented at a commercially available small-scale biomass boiler and the experimental verification showed a significant improvement of the operating behaviour in comparison to the conventional control.

Local and renewable energy communities show a high potential for the efficient use of distributed energy technologies at regional levels according to the Clean Energy Package of the European Union. However, until now there are only limited possibilities to bring such energy communities into reality because of several limitation factors. Challenges are already encountered during the planning phase since a large number of decision variables have to be considered depending on the number and type of community participants and distributed technologies. This paper overcomes these challenges by establishing a mixed-integer linear programming based optimal planning approach for renewable energy communities. A real case study is analyzed by creating an energy community testbed with a leading energy service provider in Austria. The case study considers nine energy community members of a municipality in Austria, distributed photovoltaic systems, energy storage systems, different electricity tariff scenarios and market signals including feed-in tariffs. The key results indicate that renewable energy communities can significantly reduce the total energy costs by 15% and total carbon dioxide emissions by 34% through an optimal selection and operation of the energy technologies. In all the optimization scenarios considered, each community participant can benefit both economically and ecologically.

A novel biomass combustion technology was investigated that operates at a low oxygen content under fixed-bed and double air staging conditions. This technology was used to achieve extremely low NO_X and particle matter emissions in a 30 kW lab-scale reactor, displaying high fuel flexibility and no slagging. In this experimental work, the aim was to minimize inorganic particulate matter emissions, this aim was achieved by enabling the very low release of inorganics such as K from the fixed bed, which operates like a compact updraft gasifier. The elemental composition of the employed fuels, emitted dust particles, and fuel particle samples taken at three different heights within the fixed bed, and the bed temperatures were measured. The main objective in this study was to determine and understand the different processes of inorganic matter release that take place within the compact fixed bed. The results show that 98% and 99.7% of the K could be retained in the fixed bed for wood chips and miscanthus pellets, respectively, thus minimizing the particulate matter emissions. Different processes in the context of K release within the fixed bed could be identified for silica rich/agricultural and calcium rich / woody fuels, respectively and inconsistencies in the literature on these mechanisms could be resolved. In the case of miscanthus pellets, K is retained in silicates, and no accumulation of K, Cl and S occurs in the fixed bed above. In the case of wood chips, on the other hand, there is an unexpected K accumulation in the fixed bed, which is due to the release of K in the hot oxidation zone and the subsequent formation of large amounts of K chlorides and sulfates by condensation in the cooler upper region. Furthermore, for woody fuels, bounding or intercalation of K into the char matrix plays a more important role than the formation of carbonates in avoiding K release from the bed.

Absorption heat pumping devices (AHPDs, comprising absorption heat pumps and chillers) use mainly thermal energy instead of electricity as the driving energy to provide resource-efficient heating and cooling when using waste heat or renewable heat sources. Despite this benefit, AHPDs are still not a very common technology due to their complexity. However, better modulation and part-load capability, which can be achieved through advanced control strategies, can simplify the use of AHPDs and help to better integrate them into complex energy systems. Therefore, this paper presents a new, dynamic model-based control approach for single-stage AHPDs that can extend an AHPD’s operating range by employing multi-input-multi-output (MIMO) control methods. The control approach can be used for different AHPD applications and thus control configurations, i.e., different combinations of manipulated and controlled variables, and can also be used for redundantly-actuated configurations with more manipulated than controlled variables. It consists of an observer for the state variables and unknown disturbances, a state feedback controller and, in case of redundantly-actuated configurations, a dynamic control allocation algorithm. The proposed control approach is experimentally validated with a representative AHPD for two different control configurations and compared to two benchmark control approaches – single-input-single-output (SISO) PI control representing the state-of-the-art, and model-predictive control (MPC) as an alternative advanced control concept. The experimental validation shows that the two MIMO control approaches (the proposed state feedback and the MPC approach) allow for a wider operating range and hence better part load capability compared to the SISO PI control approach. While MPC generally results in a comparably high computational effort due to the necessity of continuously solving an optimization problem, the proposed state feedback control approach is mathematically simple enough to be implemented on a conventional programmable logic controller. It is therefore considered a promising new control approach for AHPDs with the ability to extend their operating range and improve their part load capability, which in turn facilitates their implementation and thus the use of sustainable heat sources in heating and cooling systems.

Microgrids, a research topic within the smart grids area, build on close relationships between demand and supply and will create a 170 Mrd. € market potential in 2020[1]. These individual markets are characterized by different technologies in use. For example, biogas will play a key role in microgrids in Asia compared to Photovoltaics, Combined heat and Power (CHP), as well as storage technologies in North America. All these different technologies need to be coordinated and controlled. BIOENERGY2020+ GmbH is the industry leader when it comes to biomass control systems in Austria. Thus, BIOENERGY2020+ GmbH is already combining this knowledge within the OptEnGrid and “Grundlagenforschung Smart- und Microgrid“ (K3-F-755/001-2017) research projects, which are based on the leading microgrid optimization tool DER-CAM from Lawrence Berkeley National Laboratory at the University of California in Berkeley. These two BIOENERGY2020+ GmbH basic research projects constitute the basis for new innovative microgrid controller concepts and these new microgrid controller will be implemented and tested in the suggested Microgrid Research Lab in Wieselburg. The Microgrid Research Lab will include the Technology- und Reseach Centre (tfz) Wieselburg-Land and the new firefighting department next to the tfz.

Microgrids are local energy grids that (partly) cover their own energy demand. Decentralized renewable energy sources reduce energy costs and CO2 emissions in a microgrid. Various storage systems and strategies like load shift are employed to balance the volatile energy flows. Intelligent controllers improve the energy management of the micro and smart grids. BEST GmbH is the industry leader when it comes to biomass control systems in Austria. Thus, BEST GmbH is already combining this knowledge within the “OptEnGrid” (FFG 858815) and “Grundlagenforschung Smart- und Microgrid“ (K3-F-755/001-2017) research projects, which are based on the leading microgrid optimization tool DER-CAM from Lawrence Berkeley National Laboratory at the University of California. These two BEST GmbH basic research projects form the basis for new innovative microgrid controller concepts which will be implemented and tested in the presented Microgrid Research Lab in Wieselburg (project Microgrid Lab 100%). The Microgrid Research Lab will include the Technology- und Reseach Centre (tfz) Wieselburg-Land and the new firefighting department next to the tfz.

Die Energiewende in Richtung dezentraler Energieversorgung und der stetige Ausbau
erneuerbarer Energieressourcen erfordert ein angepasstes Energienetz (Strom, Wärme und
Kälte) mit einem flexiblen, ausbau- und integrationsfähigen Regelungssystem, welches
bestehende Energieversorgungsunternehmen (EVU) Systeme komplementiert, Netze
entlastet und die Notwendigkeit des teuren Netzausbaus verringert. Intelligente Mikro-Netze
(Microgrids), ein Bereich der Strom- und Energie-Netze (Smartgrids), erfüllen diese
Anforderungen. Durch Microgrids entstehen lokale Energiemärkte, welche lokale
Ungleichgewichte von den Verbundnetzen fernhalten und somit das Angebot und den
Verbrauch bereits auf lokaler Ebene ausbalancieren (wie z.B. Energiegemeinschaften).
Zusätzlich können die regionale Erzeugung und der Verbrauch von Strom um die Wärme-,
Kälte- und Gas-Seite ergänzt werden. Dies ergibt somit ein ganzheitliches regionales
Energiesystem, welches die gesamte Energieeffizienz erhöht und auch positive Netzeffekte
für den Energieversorger mit sich bringt. Microgrids liefern die Möglichkeit eine 100%ige
dezentrale Energieversorgung zu erreichen.
Gegenstand des Projekts „Microgrid Lab 100%“ war es bestehende und neue
wissenschaftliche Arbeiten und F&E-Ergebnisse zu Microgrids (mathematische &
physikalische Modellierung, modellbasierte Steuerungsmethoden, Regelung mit künstlicher
Intelligenz, Kommunikationsmethoden, Datenerfassung und der Austausch zwischen
Energieversorger, privaten Kunden und Gebäudemanagementsystemen) in einem realen
Umfeld zu evaluieren und auf wissenschaftlicher Ebene weiter zu entwickeln.
Projektinhalte und Projektziele waren die wissenschaftliche Planung und Inbetriebnahme des
Microgrid Forschungslabors, eine Nutzerbefragung, die Entwicklung von Testzyklen und ein
Monitoring, um mit den Ergebnissen die Optimierungsalgorithmen weiterzuentwickeln. Das
über das Projekt hinausgehende Ziel ist die Etablierung des Microgrid Forschungslabors für
verschiedene Wirtschaftszweige, um Planungs-, Steuerungs-, Integrations- und
Kommunikationskonzepte in Echtzeit zu entwickeln und für den Markt zu testen. Die
Involvierung von Industriepartner (u.a. COMET-Partner: EVN AG, Netz NÖ GmbH, Wien
Energie, meo Energie, Wüsterstrom) bereits während der Projektlaufzeit und der Aufbau eines
Kompetenznetzwerkes zu Microgrids, mit Unterstützung des Bau.Energie.Umwelt Cluster und
des Technopolmanagement Wieselburg, trugen zu dieser Zielerreichung wesentlich bei.
Konkret umfasst das geplante Microgrid Forschungslabor das Umfeld des Technologie- und
Forschungszentrum (TFZ) Wieselburg-Land sowie das neue Feuerwehrhaus der
Stadtgemeinde Wieselburg und Gemeinde Wieselburg-Land.

Die Energiewende in Richtung dezentrale Energieversorgung und der stetige Ausbau
erneuerbarer Energieressourcen erfordert ein angepasstes Energienetz (Strom, Wärme und
Kälte) mit einem flexiblen, ausbau- und integrationsfähigen Regelungssystem, welches
bestehende EVU Systeme komplementiert, Netze entlastet und die Notwendigkeit des teuren
Netzausbaus verringert. Intelligente Mikro-Netze (Microgrids), ein Bereich der Strom- und
Energie-Netze (Smartgrids), erfüllen diese Anforderungen. Durch Microgrids werden lokale
Energiemärkte entstehen, welche lokale Ungleichgewichte von den Verbundnetzen
fernhalten und somit das Angebot und den Verbrauch bereits auf lokaler Ebene
ausbalancieren. Zusätzlich können die regionale Erzeugung und der Verbrauch von Strom
um die Wärme-, Kälte- und Gas-Seite ergänzt werden. Dies ergibt somit ein ganzheitliches
regionales Energiesystem, welches die gesamte Energieeffizienz erhöht und auch positive
Netzeffekte für den Energieversorger mit sich bringt. Microgrids liefern die Möglichkeit eine
100%ige dezentrale Energieversorgung zu erreichen.
Gegenwärtiger Forschungsbedarf und Gegenstand des Projektantrages
„Microgrid Lab 100%“ sind bestehende und neue wissenschaftliche Arbeiten und F&EErgebnisse
zu Microgrids (mathematische & physikalische Modellierung, modellbasierte
Steuerungsmethoden, Regelung mit künstlicher Intelligenz, Kommunikationsmethoden,
Datenerfassung und der Austausch zwischen Energieversorger, privaten Kunden und
Gebäudemanagementsystemen) in einem realen Umfeld zu evaluieren und auf
wissenschaftlicher Ebene weiter zu entwickeln. Da es derzeit keine vergleichbaren
Methoden, Verfahren oder Richtlinien gibt, ist ein hoher Innovationsgrad des beantragten
Projekts sichergestellt.
Projektinhalte und Projektziele sind die wissenschaftliche Planung und Inbetriebnahme des
Microgrid Forschungslabors, eine Nutzerbefragung, die Entwicklung von Testzyklen und ein
Monitoring, um mit den Ergebnissen die Optimierungsalgorithmen weiterzuentwickeln. Das
über das Projekt hinausgehende Ziel ist die Etablierung des Microgrid Forschungslabors für
verschiedene Wirtschaftszweige, um Planungs-, Steuerungs-, Integrations- und
Kommunikationskonzepte in Echtzeit zu entwickeln und für den Markt zu testen. Die
Involvierung von Industriepartner (u.a. COMET-Partner: EVN AG, Netz NÖ GmbH, Wien
Energie) bereits während der Projektlaufzeit und der Aufbau eines Kompetenznetzwerkes zu
Microgrids, mit Unterstützung des Bau.Energie.Umwelt Cluster und des
Technopolmanagement Wieselburg, tragen zu dieser Zielerreichung wesentlich bei.
Konkret umfasst das geplante Microgrid Forschungslabor das Umfeld des Technologie- und
Forschungszentrum (TFZ) Wieselburg-Land sowie das neue Feuerwehrhaus der
Stadtgemeinde Wieselburg und Gemeinde Wieselburg-Land. Zusätzlich wird die
Fachhochschule Wieselburg Daten (aus der Nutzerbefragung und einem eigenen
Monitoring) für die Weiterentwicklung der Optimierungsalgorithmen liefern.

Dieser Ergebnisbericht zeigt die Ergebnisse zu den gesammelten Lastkurven und Datensätzen
im Microgrid Forschungslabor in Wieselburg (Microgrid Lab). Die Ergebnisse beziehen sich
auf die Technologien, Messgeräte, Strom-, Heiz- und Kühllasten und Marktdaten wie z.B.
Stromtarife und verschiedene Energie- und Brennstoffpreise.

Die Erkenntnisse der Arbeitspakete I, II und III bildeten die Grundlage, um Konzepte für
innovative Produktentwicklungen von Systemkomponenten für Microgrids zu entwickeln und
diese fertigzustellen. Dazu erfolgte in Arbeitspaket I die Analyse und Planung der verwendeten
Wärme-, Strom- und Kältetechnologien, welche in AP II installiert und ins lokale System
integriert wurde. Die Datenerfassung, Monitoring und Bewertung des Nutzerverhaltens erfolgte
im Anschluss in AP III. Dadurch wurden die Rahmenbedingungen geschaffen um neue
Produkte und Dienstleistungen zu entwickeln und zu testen.

Das im Projektantrag formulierte Ziel zum Arbeitspaket III enthält die systematische
Sammlung, Aufbereitung und Interpretation des Denkens sowie Verhaltens von Personen, die
im Microgrid handeln. Mittels qualitativer Befragungsmethoden werden Aspekte, wie der
erwartete Nutzen, die Akzeptanz, die erwartete Benutzerfreundlichkeit und die
Zahlungsbereitschaft – insbesondere in Bezug auf E-Mobilität und dazugehörigen
Lademöglichkeiten - erhoben.
Die Erkenntnisse aus diesem Arbeitspaket können verwendet werden für die Entwicklung der
theoretischen Planungsalgorithmen. Diese sollen die Effizienz der Einbindung von Gebäuden
in das Microgrid sicherstellen.

Wood pellet combustion units are a comfortable, full automatic and low emission solution for the provision of space heating in small scale applications. The requirement of an auxiliary energy source for the heat supply and distribution however results in a dependence on the electrical grid. The goal of this work is thereby to eliminate this dependence and to meet the auxiliary energy demand through the independent production of electrical energy. The thermoelectric power production method was chosen from a number of technology variations so as to guarantee the silent and maintenance free production of direct current that can be implemented in cellars and space heaters. The first development step was the implementation of a Prototype with a fuel heat input of 10 kW and a nominal electrical power of 200 W. The central point of the implementation was the integration of a thermo-generator in a pellet combustion unit and the subsequent evaluation of the system concept. The integrated system implemented in the prototype confirms the feasibility of the combination of these technologies. The electrical efficiency of the thermo-generator was found to be in accordance with the target value of 4%, corresponding to a produced nominal electric power of 200 W.

La combustione di biomassa legnosa con piccoli apparecchi e caldaie è oggi vista con rinnovato interesse per il raggiungimento degli obiettivi comunitari di produzione di energia rinnovabile al 2020. L’aumento dell’utilizzo della biomassa combustibile è di stretto interesse del settore agroforestale, per via del notevole indotto economico che peraltro interessa tutto il territorio nazionale. Tuttavia, la combustione della biomassa è legata ad una serie di problematiche ambientali quali le emissioni in atmosfera di polveri sottili che influenzano direttamente la qualità dell’aria. Si ritiene, quindi, che l’auspicato aumento dell’utilizzo delle biomasse, soprattutto ai fini della produzione di calore (riscaldamento ambienti), sia legata al contenimento delle emissioni al camino. In questo contesto, è quindi importante la corretta misura delle polveri emesse dagli apparecchi di riscaldamento domestico alimentati a biomassa solida, tenendo conto anche della frazione condensabile, come richiesto dalla normativa. Il lavoro mette a confronto due tecniche di misura delle polveri, la tecnica di prelievo a caldo con raffreddamento dei fumi in impinger e la tecnica di diluizione con tunnel. Sono stati selezionati per il confronto due apparecchi di ridotta potenza (< 15 kWt) ed elevata efficienza: una caldaia a pellet ed una stufa a pellet. In condizioni di combustione completa le due tecniche restituiscono fattori di emissione simili. Nella stufa a pellet la misura a freddo è maggiore del 20 – 30 % rispetto alla misura a caldo. La ridotta presenza della frazione condensabile è stata confermata dall’analisi NPOC degli impinger. Sono state misurate le emissioni totali prodotte da un utilizzo reale del dispositivo, comprendendo anche le fasi transitorie di combustione (accensione, riscaldamento a regime e spegnimento), solitamente non considerate nelle misure standard di laboratorio. La fase di accensione produce fino a tre volte le polveri emesse in condizioni stazionarie. L’emissione totale si riduce all’aumentare del tempo di utilizzo del dispositivo, rientrando nell’intervallo delle emissioni delle condizioni stazionarie dopo circa 6 h. Gli IPA, emessi in quantità elevate, sono costituiti maggiormente da congeneri a peso molecolare medio – basso, associati a minore tossicità. Il TEQ è funzione della potenza e delle condizioni di
combustione del dispositivo.

Utilization of biomass as feedstock in dual fluidized bed steam gasification is a promising technology for the substitution of fossil energy carriers. Experience from industrial scale power plants showed an alteration of the olivine bed material due to interaction with biomass ash components. This change results mainly in the formation of Ca-rich layers on the bed particles. In this paper, a mechanism for layer formation is proposed and compared to the better understood mechanism for layer formation on quartz bed particles. Olivine bed material was sampled at an industrial scale power plant before the start of operation and at pre-defined times after the operation had commenced. Therefore, time dependent layer formation in industrial-scale conditions could be investigated. The proposed mechanism suggests that the interaction between wood biomass ash and olivine bed particles is based on a solid-solid substitution reaction, where Ca2+ is incorporated into the crystal structure. As a consequence Fe2+/3+ and Mg2+ ions are expelled as oxides. This substitution results in the formation of cracks in the particle layer due to a volume expansion in the crystal structure once Ca2+ is incorporated. The results of this work are compared to relevant published results including those related to quartz bed particles.
 

This study explores AnMBR technology as a promising method for treating wastewater from the meat-processing industry by analysing its characteristics and impact under continuous feeding. The solids were retained, utilising an ultrafiltration membrane with a pore size of 0.2 µm, and the efficacy of reducing the organic load was evaluated. Although the COD removal rate decreased from 100% at an OLR of 0.71 g/(L*d) to 73% at an OLR of 2.2 g/(L*d), maximum methane yields were achieved at the highest OLR, 292.9 Nm3/t (COD) and 397.8 Nm3/t (VS) per loaded organics and 353.1 Nm3/t (COD) and 518.7 Nm3/t (VS) per removed organics. An analysis of the microbial community was performed at the end of the experiment to assess the effects of the process and the substrate on its composition. The AnMBR system effectively converts meat-processing wastewater into biogas, maintaining high yields and reducing the loss of dissolved methane in the permeate, thanks to a temperature of 37 °C and high salt levels. AnMBR enables rapid start-up, efficient COD removal, and high biogas yields, making it suitable for treating industrial wastewater with high organic loads, enhancing biogas production, and reducing methane loss. Challenges such as high salt and phosphate levels present opportunities for a wider use in nutrient recovery and water reclamation.

Product gas produced by biomass gasification contains small amounts of sulfur compounds (hydrogen sulfide) which can reduce catalyst activity during steam reforming process. Sulfur removal has a negative effect on process efficiency and steam reforming has to be run without cleaning the gas prior to the reactor. It is therefore of interest to investigate the effect of sulfur on the performance of steam reforming reactions. In this work a packed bed reactor filled with nickel based catalysts is mathematically modeled to simulate the steady state pseudo-heterogeneous equations representing heat and mass transfer in the reactor tube. Catalytic bed is subjected to hydrogen sulfide and an isotherm model for the sulfur coverage on the Ni surface is considered to exactly investigate sulfur poisoning effects on methane conversion, hydrogen yield, carbon dioxide and carbon monoxide concentration. It is shown that even when present in the hydrocarbon feedstock in small quantities, (ppm) levels, sulfur can have a significant effect in methane conversion and temperature distribution within the reactor. © 2013 Elsevier B.V.