A one-dimensional model for the thermal conversion of thermally thick biomass particles is developed for the simulation of the fuel bed of biomass grate furnaces. The model can be applied for cylindrical and spherical particles. The particle is divided into four layers corresponding to the main stages of biomass thermal conversion. The energy and mass conservation equations are solved for each layer. The reactions are assigned to the boundaries. The model can predict the intra-particle temperature gradient, the particle mass loss rate as well as the time-dependent variations of particle size and density, as the most essential features of particle thermal conversion. When simulating the fuel bed of a biomass grate furnace, the particle model has to be numerically efficient. By reducing the number of variables and considering the lowest possible number of grid points inside the particle, a reasonable calculation time of less than 1 min for each particle is achieved. Comparisons between the results predicted by the model and by the measurements have been performed for different particle sizes, shapes and moisture contents during the pyrolysis and combustion in a single-particle reactor. The results of the model are in good agreement with experimental data which implies that the simplifications do not impair the model accuracy.

A one-dimensional single particle model is utilised to investigate the effects of radiation temperature, moisture content, particle size and biomass physical properties on the heating rate in biomass particles during pyrolysis. The model divides the particle into four layers - drying, pyrolysis, char and ash layer - corresponding to the four main stages of biomass thermal conversion. The average of the time derivative of the pyrolysis layer centre temperature weighted by the pyrolysis rate is introduced as an appropriate indicator for the heating rate in the particle during pyrolysis. The influencing parameters on the heating rate are summarised in the Biot number and the thermal time constant, to make the investigation of their effects easier. The heating rate is inversely proportional to the thermal time constant. The effect of a variation of the Biot number on the heating rate is negligible in comparison to the thermal time constant. Therefore, the thermal time constant can be sufficiently used to specify the heating rate regimes during pyrolysis. It is found that for thermal time constants of more than 50 s, pyrolysis takes place in a low heating rate regime, i.e. less than 50 K/min. Additionally, the heating rate during pyrolysis of various biomass types under a wide range of thermal conversion conditions has been examined, in order to classify the heating rate regime of pyrolysis in state-of-the-are combustion/gasification plants. The pyrolysis of wood dust and wood pellets is found to happen always in high heating rate regimes. Therefore, the kinetic parameters obtained by conventional TGA systems (typically with heating rates lower than 50 K/min) are not applicable for them. On the contrary, the pyrolysis of wood logs always happens in low heating rate regimes, which indicates that kinetic parameters obtained by conventional TGA systems can be applied. However, pyrolysis of wood chips can undergo low or high heating rate regimes depending on their particle size. Concerning the moisture content, it can be stated that it does not strongly influence the heating rate regime of certain biomass particles. © 2011 Elsevier Ltd. All rights reserved.

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.

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.

To gain reliable data for the development of an empirical model for the prediction of the local high temperature corrosion potential in biomass fired boilers, online corrosion probe measurements have been carried out. The measurements have been performed in a specially designed fixed bed/drop tube reactor in order to simulate a superheater boiler tube under well-controlled conditions. The investigated boiler steel 13CrMo4-5 is commonly used as steel for superheater tube bundles in biomass fired boilers. Within the test runs the flue gas temperature at the corrosion probe has been varied between 625 °C and 880 °C, while the steel temperature has been varied between 450 °C and 550 °C to simulate typical current and future live steam temperatures of biomass fired steam boilers. To investigate the dependence on the flue gas velocity, variations from 2 m·s⁻¹ to 8 m·s⁻¹ have been considered. The empirical model developed fits the measured data sufficiently well. Therefore, the model has been applied within a Computational Fluid Dynamics (CFD) simulation of flue gas flow and heat transfer to estimate the local corrosion potential of a wood chips fired 38 MW steam boiler. Additionally to the actual state analysis two further simulations have been carried out to investigate the influence of enhanced steam temperatures and a change of the flow direction of the final superheater tube bundle from parallel to counter-flow on the local corrosion potential.

The direct combustion of the biomass is the most advanced and mature technology in the field of energetic biomass utilisation. The legislations on the amount of emitted pollutants and the plant efficiency of biomass combustion systems are continually being restricted. Therefore constant improvement of the plant efficiency and emission reduction is required Numerical modelling is gaining increasing importance for the development of biomass combustion technologies. In this paper an overview about the numerical modelling efforts deal with the most relevant phenomena in biomass grate firing systems is given. The numerical modelling results in a deeper understanding of the underlying processes in biomass combustion plants. Therefore, it leads to a faster and safer procedure of development of a new technology.

State-of-the-art packed bed models supply continuous concentration profiles as boundary conditions for subsequent CFD simulations of gas phase, leading to pre-mixed combustion conditions. However, in reality the “porous” nature of the packed bed leads to streak formation influencing gas mixing and combustion. Therefore, in the present work, in order to account for the influence of the streaks on gas phase combustion, a gas streak model based on a correlation between the local gas residence time and a mixing time has been developed based on numerical simulations. Finally, the streak model was linked with an in-housed developed hybrid gas phase combustion model suitable for laminar to highly turbulent flow conditions and applied for an under-feed pellet stoker furnace (20 kW_th) concerning the simulation of gas phase combustion and NO_x formation. The results in comparison with a simulation without the streak formation model show that the flue gas species prediction can be improved with the proposed streak formation model. Especially, in the region above the fuel bed (in the primary combustion chamber), this is of special importance for NO_x reduction by primary measures.

Ash related problems such as slagging, fouling, and high temperature corrosion in biomass fired boilers are still insufficiently explored due to the complexity of the underlying processes. High temperature corrosion of low alloy steels like 13CrMo4-5 has already been investigated in plants firing chemically untreated wood chips. In this earlier work it has been suggested that the oxidation of the steel is the dominating mechanism in the material temperature range between 450 and 550 °C. Unfortunately the exponential dependence of the material degradation on the flue gas temperature also found within this work cannot be explained with the proposed corrosion mechanism. To determine the dominating corrosion mechanism, additionally test runs have been carried out in a specially designed drop tube reactor. To investigate the time-dependent corrosion behavior of 13CrMo4-5, a newly developed mass loss probe was applied under several constant parameter setups. In addition to these measurements, the time-dependent oxidation of 13CrMo4-5 under air was investigated in a muffle furnace. To gain relevant information regarding the corrosion mechanism prevailing, the deposits as well as the corrosion products have been examined subsequently to the test runs by means of scanning electron microscopy and energy dispersive X-ray analyses. With the experimental data gained it could be shown that the dominating corrosion mechanism strongly depends on the conditions prevailing (e.g., steel temperature, flue gas temperature, and velocity) and can either be the oxidation of the steel by gaseous O₂ and H₂O or a combination of oxidation and active Cl-induced oxidation.

This paper presents the virtual biomass grate furnace, which comprises of comprehensive CFD models of all relevant processes for the simulation of biomass grate furnaces. The models consist of a 3D packed bed model, a gas phase combustion model for laminar to highly turbulent flows and a model to account for the influence of the flue gas streaks arising from the fuel bed in the freeboard. The simulation results of a 20 kW underfeed stoker furnace show that the overall CFD model is able to provide valuable insight on the processes occurring in the packed bed and freeboard and their interactions.

Detailed reaction schemes and experimental data for the online release of pyrolysis volatiles are required to gain a more fundamental understanding of biomass pyrolysis, which would in turn allow the process to be controlled in a more precise way and the development of more targeted applications. A detailed online characterisation of pyrolysis products has been conducted in single particle experiments with spruce pellets at different temperatures, obtaining a good closure of the elemental mass balances. The yields and online release of CO, CO₂, H₂O, CH₄, other light hydrocarbons and total organic condensable species, as well as char yield and composition, can be predicted with a reasonable accuracy with the application of a single particle model, coupled with a detailed pyrolysis scheme, and a simple one-step scheme for tar cracking. In order to achieve it, improvements have been conducted in the pyrolysis scheme, mainly concerning the release of light hydrocarbons and char yield and composition. Deviations are still present in the different groups in which organic condensable species can be classified.

In this work a novel reaction mechanism for gas phase reactions has been developed to predict the formation of aromatic compounds from the pyrolysis products of woody biomass particles. The aromatic compounds are important for being main soot precursors as well as their toxic properties. The developed gas phase mechanism is validated with experimental data from literature as well as experimental data performed with a single particle reactor for three different pyrolysis temperatures, namely 550, 800 and 1000°C. A good agreement is achieved between model results and experimental data for the total yield of each main family of aromatic hydrocarbons, i.e. phenolics, BTXs and PAHs.

The CO/CO₂ release ratio obtained during char combustion of single biomass particles has been analysed in this work experimentally and by modelling. Experiments have been conducted with spruce, straw and Miscanthus pellets at different temperatures. Furthermore, these experiments have been modelled with a single particle model coupled with a CFD model of the single particle reactor. The results show that the CO/CO₂ ratio strongly depends on the feedstock, being lower for spruce than for straw or Miscanthus. Furthermore, the most commonly employed correlations for this ratio in literature are not adequate, as they either under- or over-predict it.

The energetic utilization of alternative fuels (short rotation coppice, miscanthus), agricultural by-products (straw, corn cobs) or biomass residues (nut shells, coffee grounds) becomes of increasing interest. Due to variations in fuel properties – and the ash content in particular – biomass fuels considerably influence the conditions in the combustion zone and especially in the fuel bed. Usually, state-of-the-art combustion appliances are optimized for a particular fuel quality and typically approved only for utilization of standardized wood pellets or wood chips. Research activities within the GrateAdvance project focus on fuel flexible grate technologies being capable of adapting conditions in the combustion zone by a systematic and targeted adjustment of grate parameters in order to minimize emissions and slagging problems, thus setting the basis for a new generation of biomass technologies. Moreover, a novel control concept will ensure optimal combustion conditions for any biomass fuel, and specifically adjust to relevant fuel properties.

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.

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.

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].

There is a need to reduce NO_x emissions, which can only be achieved through a detailed understanding of the mechanisms for their formation and reduction. In this work the release of the NO_x precursors, NH₃ and HCN, for different fuels is experimentally analysed and modelled in typical fixed-bed combustion conditions. It is shown that NH₃ and HCN are released during the main devolatilization phase and the NH₃/HCN ratio increases for fuels with a higher nitrogen content. A simplified two-steps model for their release is presented. The model can predict with a reasonable accuracy the release for fuels with a low nitrogen content, however deviations are present for fuels with a high nitrogen content, which probably arise due to a reduction of NH₃ and HCN taking place already in the bed.

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.

We briefly review the general concept and expected market potential of microgrids, then discuss the
optimization challenges associated with planning local cross-sectorial energy systems. A fair technology-
neutral approach to this optimization task leads to a hard problem, which has to be tackled with
advanced methods of mathematical optimization.
The power of this approach is illustrated in a case study, concerning the replacement of heating systems
in an alpine valley. In this case study we see both the potential for cost reduction and for the reduction
of CO2 emissions by an integrated planning approach

The present study examines the possible use of urban and rural traffic areas for producing biomass. Many of those areas (for example, parking lots at cinemas and shopping centers) are only intensively used during certain times. Most of the time those areas remain empty.
At the same time a major problem for large-scale implementation of renewable energy is the massive land use resulting from limited energy density of solar radiation and, in case of biomass production, low efficiency for utilization of solar radiation by plants. Additionally, renewable energies are often criticized for the fact that they require areas, which could also be used for food and feed production.
Therefore, it is an attractive idea to use some of the traffic areas that are lost for the ecosystem anyway for biomass production. This approach is novel that no data have been available yet. The aim of this work was therefore to develop technical solutions, to quantify the technical potential for this type of biomass production and, subsequently, for energy supply, based on data on the area utilization, climatic data and known properties of microalgae.
The work deals with the question of the technical potential for this approach in Austria. This question is
answered by a survey of the area data in Austria, the elaboration of technical systems for a possible implementation, as well as by calculating the biomass potential, based on simulation results. The data have been collected, analyzed and evaluated in a comprehensive literature search. The potential analysis provides an overview of the distribution of traffic areas in Austria and the resulting biomass potential. Thus, a list of possible areas including biomass and energy quantities is available.

To optimize the combustion of biomass grate furnaces a sensitivity analysis is carried out by means of CFD simulation. The methodical procedure consists of a 3D packed bed biomass combustion model, which describes the most essential characteristics of the thermal conversion of biomass particles, such as the detailed consideration of drying, pyrolysis and char oxidation in parallel processes. Within the sensitivity analysis the following parameters have been investigated: distribution of false air, residence time of fuel on the grate and distribution of recirculated flue gas and primary air below the grate. To evaluate the influence of the varied parameters on the combustion process the focus lied on the position of the thermal conversion of the biomass and the CO at the outlet of the simulation domain. The results of the sensitivity analysis show a shift of the thermal conversion towards the grate end for increased false air as well as for reduced momentum of primary air/recirculated flue gas mixture. An increase of the fuel residence time leads to a shift of the thermal conversion towards the fuel inlet. Consequently a large region of the primary combustion zone is not used due to earlier release of CO inside the fuel bed.

This paper proposes a novel design algorithm for nonlinear state observers for linear time-invariant systems. The approach is based on a well-known family of homogeneous differentiators and can be regarded as a generalization of Ackermann's formula. The method includes the classical Luenberger observer as well as continuous or discontinuous nonlinear observers, which enable finite time convergence. For strongly observable systems with bounded unknown perturbation at the input the approach also involves the design of a robust higher order sliding mode observer. An inequality condition for robustness in terms of the observer gains is presented. The properties of the proposed observer are also utilized in the reconstruction of the unknown perturbation and robust state-feedback control

Energy management systems aiming for an efficient operation of hybrid energy systems with a high share of different renewable energy sources strongly benefit from short-term forecasts for the heat-load. The forecasting methods available in literature are typically tailor-made, complex and non-adaptive. This work condenses these methods to a generally applicable, simple and adaptive forecasting method for the short-term heat load. From a comprehensive literature review as well as the analysis of measurement data from seven different consumers, varying in size and type, the ambient temperature, the time of the day and the day of the week are deduced to be the most dominating factors influencing the heat load. According to these findings, the forecasting method bases on a linear regression model correlating the heat load with the ambient temperature for each hour of the day, additionally differentiating between working days and weekend days. These models are used to predict the future heat load by using forecasts for the ambient temperature from weather service providers. The model parameters are continuously updated by using historical data for the ambient temperature and the heat load, i.e. the forecasting method is adaptive. Additionally, the current prediction error is used to correct the prediction for the near future. Due to their simplicity, all necessary steps of the forecasting method, the update of the model parameters, the prediction based on linear regression models and the correction, can be implemented and computed with little effort. The final evaluation with measurement data from all seven consumers investigated leads to a Mean Absolute Range Normalized Error (MARNE) of 2.9% on average, and proves the general applicability of the forecasting method. In summary, the forecasting method developed is generally applicable, simple and adaptive, making it suitable for the use in energy management systems aiming for an efficient operation of hybrid energy systems.

Coupling biomass gasification with high temperature Solid Oxide Fuel Cells (SOFCs) is a promising solution to increase the share of renewables and reduce emissions. The quality of the producer gas used can, however, significantly impact the SOFC durability and reliability. The great challenge is to ensure undisturbed operation of such system and to find a trade-off between optimal SOFC operating temperature and system thermal integration, which may limit the overall efficiency. Thus, this study focuses on experimental investigation of commercial SOFC single cells of industrial size fueled with different representative producer gas compositions of industrial relevance at two relevant operating temperatures. The extensive experimental and numerical analyses performed showed that feeding SOFC with a producer gas from a downdraft gasifier, with hot gas cleaning, at an operating temperature of 750 °C represents the most favorable setting, considering system integration and the highest fuel utilization. Additionally, a 120 h long-term test was carried out, showing that a long-term operation is possible under stated operating conditions. Local degradation took place, which can be detected at an early stage using appropriate online-monitoring tools.

Fixed-bed biomass gasification coupled with internal combustion engines allows an efficient exploitation of biomass for the combined production of heat and power (CHP) at small scale with increased economic viability with respect to combustion-based CHP systems. The main barrier on the way towards a wider market distribution is represented by the fact that a robust practical operation of state-of-the-art fixed-bed biomass gasification systems is limited to very specific fuel properties and steady-state operation. The aim of this work is twofold. On the one hand, it presents the results of a series of test runs performed in a monitored commercial plant under different process conditions, in order to assess its behaviour during load modulation and fuel property variations. On the other hand, an in-house developed thermodynamic equilibrium model was applied to predict the behaviour of the gasification reactor. This gasification model could be used for the development of a model-based control strategy in order to increase the performance of the small-scale gasification system. To assess the general operational behaviour of the whole gasification system an experimental one-week-long test run has been performed by BIOENERGY 2020+ and the Free University of Bozen-Bolzano as round robin test. The plant has been tested under different operating conditions, in particular, varying the load of the engine and the moisture content of the feedstock. The outcomes shown in the present work provide a unique indication about the behaviour of a small-scale fix-bed gasifier working in conditions different from the nominal ones.

Workshop of the research project ÖKO-OPT-QUART (Ökonomisch optimiertes Regelungs- und Betriebsverhalten komplexer Energieverbünde zukünftiger Stadtquartiere)

The continuous increase of (volatile) renewable energy production and the development of energy-efficient buildings have led to a transformation of city districts’ energy systems. Their complexity has increased significantly due to the coupling of the different energy sectors like heating, cooling and electricity. Such complex multi-energy systems can be operated more efficiently and reliably if knowledge of their specific components (in terms of mathematical models) as well as knowledge of weather forecasts is incorporated in a high-level controller, which is typically referred to as an Energy Management System (EMS). However, still little comprehensive information on the costs and the practical advantages of such systems is available. For this reason, a simulation environment to estimate the real costs and advantages of the use of such an EMS is required. Consequently, this work focuses on the development of an EMS for future city districts’ energy systems and the development of a co-simulation environment in order to demonstrate the benefits of the use of the developed EMS in comparison to a conventional control strategy. The co-simulation is implemented with the aid of the co-simulation platform Building Controls Virtual Test Bed (BCVTB) and consists of the following parts: a non-linear, thermoelectric model and a control block containing either the conventional control strategy or the EMS. The thermoelectric model is built up using the well-established simulation tools TRNSYS and IDA-ICE, simulating the energy hub of the city district and the districts’ buildings, respectively. The control block is simulated using MATLAB, where IBM ILOG CPLEX is used for solving the resulting mixed-integer linear program (MILP) of the EMS. Finally, an economic model for financial (and ecological) assessment of the operation is simulated with the aid of the software package Dymola. To put the developed EMS and the co-simulation into practise a case study based on a new city district in Graz, Austria, which is currently in the planning stage, is carried out. The integration of the responsible planners and investors in the modelling process guarantees the models’ practical applicability. In the case study the performance of the originally planned conventional control strategy is compared with the performance of the developed EMS using annual simulations with a simulation time step of 1 minute, and a 24 hour prediction horizon and a 15 minute time step for the EMS. For a more robust and realistic comparison both control strategies are simulated for different scenarios considering current and future (2060) climate conditions, medium and high energy demands (load), ideal and real load prediction methods and varying import prices for electricity from the electricity grid. The results show that the use of the developed EMS strategy results in reduced annual total costs (considering operational and investment costs of additionally suggested distributed energy resources) in comparison to the conventional control strategy. Furthermore, the annual CO2-emissions could be reduced by increasing the self-consumption of the installed (renewable) energy resources and thus decreasing the necessary energy imports from the electricity and the heating grid.

Slides of the talk "Co-Simulation of an Energy Management System for Future City District Energy Systems"

With energy systems, the problem of economic planning is decisive in the design of a low carbon and resilient future grid. Although several tools to solve the problem already exist in literature and industry, most tools only consider a single “typical year” while providing investment decisions that last around a quarter of a century. In this paper, we introduce why such an approach is limited and derive two approaches to correct this. The first approach, the Forward-Looking model, assumes perfect knowledge and makes investment decisions based on the full planning horizon. The second novel approach, the Adaptive method, solves the optimization problem in single year iterations, making incremental investment decisions that are dependant on previous years, with only knowledge of the current year. Comparing the two approaches on a realistic microgrid, we find little difference in investment decisions (maximum 21% difference in total cost over 20 years), but large differences in optimization time (up to 12000% time difference). We close the paper by discussing implications of forecasting errors on the microgrid planning process, concluding that the Adaptive approach is a suitable choice.

With energy systems, the problem of economic planning is decisive in the design of a low carbon and resilient future grid. Although several tools to solve the problem already exist in literature and industry, most tools only consider a single “typical year” while providing investment decisions that last around a quarter of a century. In this paper, we introduce why such an approach is limited and derive two approaches to correct this. The first approach, the Forward-Looking model, assumes perfect knowledge and makes investment decisions based on the full planning horizon. The second novel approach, the Adaptive method, solves the optimization problem in single year iterations, making incremental investment decisions that are dependant on previous years, with only knowledge of the current year. Comparing the two approaches on a realistic microgrid, we find little difference in investment decisions (maximum 21% difference in total cost over 20 years), but large differences in optimization time (up to 12000% time difference). We close the paper by discussing implications of forecasting errors on the microgrid planning process, concluding that the Adaptive approach is a suitable choice.

Assessing the operational behaviour of biomass gasification systems is a crucial basis for further improvements in terms of operational behaviour and robustness in order to increase the technologies’ operational and economic viability. However, in most fixed-bed biomass gasification systems not all parameters required for the assessment can be measured directly. Typically, unknown parameters are determined by using as many balance equations as parameters have to be determined neglecting the additional information provided by other available but not chosen balance equations. Thus, these approaches do not incorporate all measurement data available resulting in a lack of reliability in their results. A detailed analysis of these approaches emphasises that even small deviations in the measurement data can lead to significant deviations in the calculated parameters, demonstrating that individual choices of equations can be highly sensitive regarding measurement uncertainties.

Therefore, an adjusted weighted least squares approach is developed utilizing an overdetermined system of equations incorporating all balance equations simultaneously. Thus, all measurement data available is taken into account, minimizing the influences of measurement uncertainties on the determined parameters. A comprehensive analysis shows that this approach is less sensitive to measurement uncertainties, allowing for a more reliable and accurate assessment of fixed-bed biomass gasifiers.

Keywords: fixed-bed, gasification, mass balance, performance assessment

Kernthema dieses Beitrags ist die ganzheitliche Konzeption von Mikronetze, die sich auf die Reduzierung von Kosten und CO2-Emissionen konzentriert. Mikronetze, oder auch Microgrids, ermöglichen die koordinierte Energieerzeugung von dezentralen Energieressourcen, die Speicherungen der produzierten Energie und ein Lastmanagement zum Ausgleich von Wärme-, Kälte- und Elektrizitätsdienstleistungen. Mikronetze können vom breiteren Versorgungsnetz getrennt werden, können diverse Dienstleistungen erbringen und/oder selbst Energie erzeugen sowie in Überschusszeiten speichern und bei Bedarf wieder Kosten- oder Stabilitäts-orientiert freigeben.
Die mathematische Optimierung dient als unvoreingenommene Alternative für eine gesamtheitliche Planung von dezentralen Energietechnologien. Dieses Kriterium wird bei einer Kosten- oder CO2-Reduktion vor allem dann essentiell, wenn vielfältigen Kombinationen von Technologien und Kapazitäten möglich sind. Modernste Ansätze betrachten jedoch einen quasistatischen Aufbau unter Verwendung linearisierte Modelle und Mixed Integer Linear Optimization (MILP), wobei dynamische Effekte vernachlässigt werden. Unter Berücksichtigung von Lasten, geografischen, ökonomisch-ökologischen und tariflichen Daten sind mathematische Optimierungsalgorithmen in der Lage, verschiedene Anwendungsfälle zu beurteilen, wobei Effekte wie Vorwärmung, Sollwertänderungen oder kurzfristige Sonnenschwankungen unberücksichtigt bleiben. Dies bedeutet, dass die in quasistatischen Ansätzen verwendete Wärme- und Strombilanzen ungenau sein können (eventuell können physikalische Randbedingungen sogar verletzt werden, was zu suboptimalen Ergebnissen bei der Planung führen würde).
Die Notwendigkeit besteht quasistatische Optimierung mit einer weiteren Modellierungsart zu vergleichen und die Auswirkungen auf traditionelle quasistatische Ansätze, wie sie in DER-CAM oder ReOpt eingesetzt werden, aufzudecken. Um Abweichungen - bestehend aus dynamischen oder sogar Rebound Effekten - zu erkennen, werden mit TRNSYS Gebäude- und Anlagensimulationen für eine geplante Siedlungsanlage erstellt und ein Energiekonzept mit dem mathematischen Optimierungsprogramm OptEnGrid berechnet. Der Ansatz wird für vier Doppelhäuser und ein Mehrfamilienhaus getestet. Die Gebäude werden in TRNSYS simuliert und bieten thermische Lastdaten für den Referenzfall. Auch die Stromerzeugung mit PV-Modellen und der elektrische Verbrauch mit synthetischen Lastprofilen sind sowohl in der Optimierung als auch in der Simulation beteiligt. In der elektrischen Stromerzeugung zeigt die mathematische Optimierung bereits eine Abweichung von mehr als 5% auf Jahresbasis zur TRNSYS-Simulation. Ergebnisse im thermischen Energiebereich folgen nach weiterer Auswertung.

Sustainable technologies can hardly compete with fossil-based technologies in terms of economic efficiency. One sustainable technology with special relevance due to its wide range of application and industrial readiness is biomass gasification using a dual fluidized bed (DFB). The economic challenges of a DFB gasification plant are addressed without constructional measures by adapting a current control strategy. This paper proposes a model-based control strategy aiming for increased economic efficiency of a DFB gasification plant considering exemplarily the “HGA Senden” in Ulm, Germany. A process analysis reveals high potential for improvement at the current control strategy for the synchronization of product gas production and utilization. A significant surplus of product gas is burned in an auxiliary boiler just for synchronization, and regular manual adjustments by the plant operators at the fuel feed are necessary. The model-based control strategy synchronizes by actuating the auxiliary boiler and the fuel feed simultaneously. The model-based control strategy is experimentally validated for over one month at the “HGA Senden” proofing a significant increase in economic efficiency. So, the economic efficiency of this technology for the sustainable production of energy and products is increased by model-based control.

Computational time in optimization models scales with the number of time steps. To save time, solver time resolution can be reduced and input data can be down-sampled into representative periods such as one or a few representative days per month. However, such data reduction can come at the expense of solution accuracy. In this work, the impact of reduction of input data is systematically isolated considering an optimization which solves an energy system using representative days. A new data reduction method aggregates annual hourly demand data into representative days which preserve demand peaks in the original profiles. The proposed data reduction approach is tested on a real energy system and real annual hourly demand data where the system is optimized to minimize total annual costs. Compared to the full-resolution optimization of the energy system, the total annual energy cost error is found to be equal or less than 0.22% when peaks in customer demand are preserved. Errors are significantly larger for reduction methods that do not preserve peak demand. Solar photovoltaic data reduction effects are also analyzed. This paper demonstrates a need for data reduction methods which consider demand peaks explicitly.

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.

Achieving the autonomous deployment of aerial robots in unknown outdoor environments using only onboard computation is a challenging task. In this study, we have developed a solution to demonstrate the feasibility of autonomously deploying drones in unknown outdoor environments, with the main capability of providing an obstacle map of the area of interest in a short period of time. We focus on use cases where no obstacle maps are available beforehand, for instance, in search and rescue scenarios, and on increasing the autonomy of drones in such situations. Our vision‐based mapping approach consists of two separate steps. First, the drone performs an overview flight at a safe altitude acquiring overlapping nadir images, while creating a high‐quality sparse map of the environment by using a state‐of‐the‐art photogrammetry method. Second, this map is georeferenced, densified by fitting a mesh model and converted into an Octomap obstacle map, which can be continuously updated while performing a task of interest near the ground or in the vicinity of objects. The generation of the overview obstacle map is performed in almost real time on the onboard computer of the drone, a map of size is created in , therefore, with enough time remaining for the drone to execute other tasks inside the area of interest during the same flight. We evaluate quantitatively the accuracy of the acquired map and the characteristics of the planned trajectories. We further demonstrate experimentally the safe navigation of the drone in an area mapped with our proposed approach.

Currently, many Microgrid projects remain financially uncertain and not bankable for institutional investors due to major challenges in existing planning and design methods that require multiple, complex steps and software tools.

Existing techniques treat every Microgrid project as a unique system, resulting in expensive, non-standardized approaches and implementations which cannot be compared. That is, it is not possible to correlate the results from different planning methods performed by different project developers and/or engineering companies.

This very expensive individual process cannot guarantee financial revenue streams, cannot be reliably audited, impedes pooling of multiple Microgrid projects into a financial asset class, nor does it allow for wide-spread and attractive Microgrid and Distributed Energy Resource projects deployment.

Thus, a reliable, integrated, and streamlined process is needed that guides the Microgrid developer and engineer through conceptual design, engineering, detailed electrical design, implementation, and operation in a standardized and data driven approach, creating reliable results and financial indicators that can be audited and repeated by investors and financers.

This article describes the steps and methods involved in creating bankable Microgrids by relying on an integrated Microgrid planning software approach that unifies proven technologies and tested planning methods, researched and developed by the United States National Laboratory System as well as the US Department of Energy, to reduce design times.

ie Biomasseverbrennung spielt eine zentrale Rolle bei der Bereitstellung von Wärme aus erneuerbaren Energieträgern. Konventionelle Biomasse-Brennstoffe werden jedoch aufgrund einer steigenden Anzahl stofflicher Verwertungsmöglichkeiten, wie z.B. der Umwandlung in Chemikalien, teurer und schwieriger zugänglich. Agrarbrennstoffe, die bisher nur selten oder gar nicht in Biomasse-Kleinfeuerungen eingesetzt wurden, stellen eine vielversprechende Alternative zu konventionellen Brennstoffen dar. Diese Agrarbrennstoffe, wie zum Beispiel Kurzumtrieb, Maisspindeln oder Stroh sind kostengünstig und in ausreichender Menge vorhanden. Der Einsatz von Agrarbrennstoffen in konventionellen Biomasse-Kleinfeuerungen ist jedoch aufgrund stark variierender Brennstoffeigenschaften mit erhöhten Anforderungen an das Verbrennungssystem verbunden. Erhöhte N, S, Cl, Alkalimetall- und Aschegehalte sowie niedrigere Aschenschmelzpunkte können zu aschebedingten Problemen (Ascheschmelze, Ascheablagerung und Korrosion) sowie erhöhten Konzentrationen von gasförmigen (CO, NOx, HCl und SOx) und partikelförmigen Emissionen bei der Verbrennung führen.

Ziel der in diesem Beitrag präsentierten Arbeiten war die Erhöhung die Brennstoffflexibilität einer handelsüblichen Biomasse-Kleinfeuerung um damit eine Verbrennung von Agrarbrennstoffen mit niedrigen Schadstoffemissionen und einem hohen Wirkungsgrad zu ermöglichen. Hierzu wurde eine modellbasierte Regelung entwickelt, welche insbesondere eine gezielte Einstellung des Luftverhältnisses in der Primärverbrennungszone ermöglicht und damit das Risiko der Ascheschmelze reduziert und Schadstoffmissionen verringert. Soft-Sensoren bestimmen relevante Brennstoffeigenschaften während des Betriebs, welche von der modellbasierten Regelung zur automatischen Anpassung an geänderte Brennstoffeigenschaften genutzt werden. Die modellbasierte Regelung wurde um eine CO-lambda-Optimierung ergänzt, welche auf Basis von Messwerten des Restsauerstoffgehalts und der CO-Emissionen den Wirkungsgrad der Verbrennung maximiert und gleichzeitig die Schadstoffemissionen verringert. Zur weiteren Verringerung von partikelförmigen Schadstoffemissionen wurde ein am Markt verfügbarer Elektrofilter adaptiert und nach dem Wärmeübertrager der Biomasse-Kleinfeuerung angebracht.

Dieses Verbrennungssystem wurde durch umfassende Testläufe mit begleitenden Emissionsmessungen sowie Brennstoff-, Staub- und Ascheanalysen bewertet. Der Einsatz der modellbasierten Regelung führte zu einem stabileren Betrieb bei allen Leistungen und für alle Brennstoffe. Der Elektrofilter zeigte sehr zufriedenstellende Abscheidegrade für alle untersuchten Brennstoffe und Anlagenleistungen. Dadurch konnte die Brennstoffflexibilität der handelsüblichen Biomasse-Kleinfeuerung erhöht und die Verbrennung von Agrarbrennstoffen ermöglicht werden.

Natural draft wood log stoves for residential bioheat production are very popular due to the low fuel costs, the ecological aspect of a renewable energy source and the visual appeal of the flame. However, they have rather high pollutant emissions, specially of unburnt products. The description of large wood logs conversion in stoves needs to be improved to allow a process optimization which can reduce these emissions. The transient conversion of a single wood log in a stove is experimentally investigated with test runs quenching the log after defined time intervals and measuring the flue gas composition and temperatures in the log and stove. The experiments have been described with a volumetric single particle model, which predicts with good accuracy the log conversion until a time of around 30 min, when pyrolysis is almost ending. At that point, log fragmentation takes place and smaller fragments are detached from the log falling onto the bed of embers. Despite the increase in external surface area, char oxidation takes place at a moderate rate. This last stage of wood log conversion in a stove is the most challenging to model. Finally, preliminary recommendations are provided for reducing CO emissions in wood log stoves.

The continuous increase of (volatile) renewable energy production and the coupling of different energy sectors such as heating, cooling and electricity have significantly increased the complexity of urban energy systems. Such multi-energy systems (MES) can be operated more efficiently with the aid of optimization-based energy management systems (EMS). However, most existing EMS are tailor-made for one specific system or class of systems, i.e. are not generally applicable. Furthermore, only limited information on the actual savings potential of the usage of an EMS under realistic conditions is available. Therefore, this paper presents a novel modular modeling approach for an EMS for urban MES, which also enables the modeling of complex system configurations. To assess the actual savings potential of the proposed EMS, a comprehensive case study was carried out. In the course of this the influence of different user behavior, changing climatic conditions and forecast errors on the savings potential was analyzed by comparing it with a conventional control strategy. The results showed that using the proposed EMS in conjunction with supplementary system components (thermal energy storage and battery) an annual cost savings potential of between 3 and 6% could be achieved.

In order to limit global warming to 1.5 °C compared to the pre-industrial temperature level, zero net CO2 emissions are needed on a global scale until 2050. A Chemical Looping (CL) process represents a technological system which is CO2-negative when using biomass as fuel and thus can substantially contribute to this target. In principle, the process uses a metal oxide as oxygen carrier material (OC) which is cyclically oxidized by air or steam and reduced by the fuel. Without air as the direct oxygen source for fuel conversion, high calorific product gases or pure carbon dioxide in case of combustion are obtained after the condensation of water vapor, which can then be stored or further utilized.
Within the funded project ”BIO-LOOP”, different Chemical Looping processes (for example combustion, gasification, hydrogen production) and reactors (fixed bed, fluidized bed) are investigated numerically and experimentally. An advanced process analysis tool based on mass and energy balances of the system considered will be presented. It provides data about the specific internal and external streams, process conditions and efficiencies. Within the analysis tool, various independent modular units describe individual process steps, e.g. mixing, chemical reaction or splitting. These components can be adjusted, combined and interconnected according to the flow chart of the system. The process model represents the first step towards a flexible Chemical Looping reactor simulation toolbox to analyze various process scenarios. Emphasis is put on the flexibility regarding the fuels and oxygen carriers, their conversion and possible process variations. The tool developed will support upcoming CFD modeling and further economic considerations.

The large variations found in literature for the activation energy values of main biomass compounds (cellulose, hemicellulose and lignin) in pyrolysis TGA raise concerns regarding the reliability of both the experimental and the modelling side of the performed works. In this work, an international round robin has been conducted by 7 partners who performed TGA pyrolysis experiments of pure cellulose and beech wood at several heating rates. Deviations of around 20 – 30 kJ/mol were obtained in the activation energies of cellulose, hemicellulose and conversions up to 0.9 with beech wood when considering all experiments. The following method was employed to derive reliable kinetics: to first ensure that pure cellulose pyrolysis experiments from literature can be accurately reproduced, and then to conduct experiments at different heating rates and evaluate them with isoconversional methods to detect experiments that are outliers and to validate the reliability of the derived kinetics and employed reaction models with a fitting routine. The deviations in the activation energy values for the cases that followed this method, after disregarding other cases, were of 10 kJ/mol or lower, except for lignin and very high conversions. This method is therefore proposed in order to improve the consistency of data acquisition and kinetic analysis of TGA for biomass pyrolysis in literature, reducing the reported variability.

A new model-based control strategy for biomass grate boilers is presented in this paper. Internal model control is used to control four outputs of the plant and to achieve a control structure with fewer control parameters needing to be experimentally tuned. A nonlinear state–space model describing the essential behaviour of the biomass grate boiler is used for controller design. The inverse system dynamics representing the main part of internal model control are designed with the help of this model. In doing so the properties of differentially flat systems are used. Due to a time delayed input, the inverse system is determined only for three input output channels. The stabilization of the inverse system dynamics, however, is a challenging task. A stabilization method with the help of the time delayed input is suggested and a stability analysis is given. The new control strategy has only three parameters to be tuned, representing a major reduction of complexity in comparison to existing model-based approaches. Finally, experimental results of the implemented control strategy on representative biomass grate boiler with a nominal capacity of 180 kW are presented and compared to an existing model-based control strategy based on input output linearization. The experimental evaluation proves that it is possible to operate the biomass boiler in all load ranges with high efficiency and low pollutant emissions.

The authors want to acknowledge, that during the production of the final version of the publication the image for Figure 9 has been replaced with the image for Figure 12, however without changing the content of the paper. This issue is resolved in the current version of the publication.

This publication focuses on the experimental investigation of a novel small-scale fuel flexible biomass combustion technology with a fixed-bed employing a low oxygen concentration. It was obtained through a low primary air ratio and the additional supply of recirculated flue gas. The plant was operated with spruce wood chips, which contained three different mass fractions of water, and miscanthus pellets. All relevant components of the released gas above the fixed-bed were measured, as well as the 3D bed temperature distribution. The balances confirmed a high experimental data consistency. Therefore, it was possible to determine the location of the four different conversion zones inside the fixed-bed: drying, pyrolysis, char gasification and char oxidation. The reduction of CO2 to CO in the char reduction zone worked efficiently across the entire grate area. Furthermore, the results showed that the water mass fraction of the fuel did not influence the dry product gas composition, but significantly affected the location for the release of pyrolysis products such as tars. It was found that the low oxygen concentration in the fixed-bed combined with flue gas recirculation was an effective method to reduce bed temperatures and therefore its inorganic emissions while significantly increasing feedstock flexibility. The investigations provided fundamental findings on the conversion and release behavior of the new technology under real operating conditions and are very useful for further experimental work and CFD simulations targeting the reduction of PM and NOX emissions.

Absorptionskälteanlagen können einen wesentlichen Beitrag zur Verringerung von CO2-Emissionen leisten, wenn Wärme aus regenerativen Energieträgern oder Abwärme aus industriellen Prozessen zum Antrieb verwendet wird. Absorptionskälteanlagen weisen bereits jetzt eine hohe Effizienz auf, bei veränderlichen Betriebsbedingungen kann diese je nach vorhandenen Stellgliedern weiter gesteigert werden. Dazu werden im Rahmen des Forschungsprojektes „Heat Pumping Systems Control (HPC)“ zwei Absorptionskälteanlagen – eine mit der Stoffpaarung Ammoniak/Wasser (NH3/H2O) und eine mit der Stoffpaarung Wasser/Lithiumbromid (H2O/LiBr) – untersucht, um für unterschiedliche Anwendungen optimale Betriebsstrategien zu entwickeln. Zur Berücksichtigung der Zustandsänderungen in der Absorptionskälteanlage, werden dynamische Simulationsmodelle in der Modellierungssprache Modelica entwickelt und mit Messdaten validiert.

Im Rahmen dieses Konferenzbeitrags werden Komponentenmodelle für die NH3/H2O-Absorptionskälteanlage und Simulationsrechnungen bei veränderlichen Randbedingungen präsentiert, sowie ein Vergleich mit Messdaten diskutiert.

Four different models for heat transfer to the particles immersed in a fluidized bed were evaluated and implemented into an existing single particle model. Pyrolysis experiments have been conducted using a fluidized bed installed on a balance at different temperatures and fluidization velocities using softwood pellets. Using a heat transfer model applicable for fluidized beds, the single particle model was able to predict the experimental results of mass loss obtained in this study as well as experimental data from literature with a reasonable accuracy. A good agreement between experimental and modeling results was found for different reactor temperatures and configurations as well as different biomass types, particle sizes – in the typical range of pellets - and fluidization velocities when they were higher than . However, significant deviations were found for fluidization velocities close to minimum fluidization. Heat transfer models which consider the influence of fluidization velocity show a better agreement in this case although differences are still present.

The majority of renewable energy technologies are volatile in nature. External factors such as weather conditions lead to fluctuations in their produced electricity and heat. This results in a demand either not being covered or dissatisfied since too much electricity and heat is produced in the energy system. Although energy storages can counteract these fluctuations, renewable energy technologies that are capable of producing energy on demand are needed as well. As such, technologies based on the thermochemical conversion of biomass are especially relevant as they are considered to be CO2-neutral. Although most existing implementations are based on combustion of biomass, fixed-bed biomass gasification is of growing relevance due to higher overall efficiencies and low pollutant emissions. Currently, fixed-bed biomass gasifiers are usually operated at steady-state operation to produce the maximum amount of energy possible. This contribution investigates, whether they can be used as a technology for demand-oriented electricity and heat production

The operation characteristics of thermally driven absorption refrigeration systems (ARS) are strongly dependent on their hydraulic integration. Therefore, varying operating conditions of the hydraulic supply have a great influence on the behaviour of ARS and lead to dynamic operation, which can affect the efficiency and is largely unexplored so far. To enable a simple investigation of ARS integration considering their dynamic behaviour and to develop modern, efficiency-enhancing control strategies, dynamic simulation models of ARS are developed in Modelica Code.

In this paper, a dynamic simulation model of an ARS with the working pair ammonia/water (NH3/H2O) is presented. The parameterization and the physical correlations of selected components of the simulation model are described. Afterwards, the simulation model is verified by comparing simulation results with measurement data of the NH3/H2O-ARS. Finally, the capabilities of the simulation model are demonstrated by performing a simulation-based analysis of the temperature glide of the refrigerant in the evaporator.

Industrial plants using DFB biomass gasification are on the verge of profitability. These plants should be operated more economically in order to support the industrial applications for renewable technologies of this kind. Since some parts of such plants are typically difficult to control, a state-of-the-art control strategy is analyzed here in the context of its potential for increased economic efficiency. The DFB gasification plant “HGA Senden” in Ulm, Germany is considered on an exemplary basis here. A process analysis reveals a high potential in the synchronization of product gas generation and utilization. At the present time a relevant surplus of product gas is burned in an auxiliary boiler for synchronization purposes and regular manual adjustments at the fuel feed are necessary by the plant operators. For this synchronization a novel control strategy is developed that actuates the auxiliary boiler and the fuel feed simultaneously. The novel control strategy was experimentally validated for a period of over one month. Due to this long-term evaluation the fuel consumption was reduced by 5% and the manual adjustments of the fuel feed that were necessary on average every 30min were eliminated. As a result DFB gasification plants can be operated more economically by applying the novel control strategy for synchronization of product gas generation and utilization.