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.

Solar-assisted heating systems use the energy of the sun to supply consumers with renewable heat and can be found all over the world where heating of buildings is necessary. For these systems, both heat production and heat demand are directly related to the weather conditions. In order to optimally plan production, storage, and consumption, forecasts for both the future heat production of the thermal solar collectors as well as the future heat demand of the connected consumers are essential. For this reason, this contribution presents adaptive forecast methods for the solar heat production and the heat demand of consumers using weather forecasts. The developed methods are easy to implement and therefore practically applicable. The final verification of the methods shows good agreement between the predicted values and measurement data from a representative solar-assisted heating system.

n the course of this study the direct utilization of ammonia in different types of solid oxide fuel cells (SOFCs), such as anode- and electrolyte-supported SOFC, is investigated. Experiments in low fuel utilization, exhibited excellent performance of ammonia in SOFCs, although the power outputs of equivalent hydrogen/nitrogen fuels were not attained due to the incomplete endothermic ammonia decomposition. Next, the single cells were operated under high fuel utilization conditions and methane was added to the humidified ammonia stream, where they showed excellent ammonia- and methane conversions. The stability of the cells used was proven over a period of at least 48 hours with a variety of fuel mixtures. Post mortem scanning electron microscopy analysis of the anode micro-structures indicated nitriding effects of nickel, as microscopic pores and enlargements of the metallic parts occurred. Finally, a long-term test over 1,000 hours was carried out using a ten-layer stack consisting of electrolyte-supported cells.

The food and beverage industry offers a wide range of organic feedstocks for use in biogas production by means of anaerobic digestion (AD). Microorganisms convert organic compounds—solid, pasty, or liquid ones—within four steps to biogas mainly consisting of CH₄ and CO₂. Therefore, various conversion technologies are available with several examples worldwide to show for the successful implementation of biogas technologies on site. The food and beverage industry offer a huge potential for biogas technologies due to the sheer amount of process residues and their concurrent requirement for heat and power. The following study analyzes specific industries with respect to their implementation potential based on arising waste and heat and power demand. Due to their chemical composition, several feedstocks are resistant against microbiological degradation to a great extent. A combination of physical-, chemical-, and microbiological pretreatment are used to increase the biological availability of the feedstock. The following examples will discuss how to best implement AD technology in industrial processes. The brewery industry, dairy production, slaughterhouses, and sugar industry will serve as examples.

Several studies pointed out that emission release is related to the concentration of particular elements in the fuel. Fuel indexes were developed to predict emissions of biomass combustion based on the elemental composition of the fuel. This study focuses on emissions of different biomass combustion technologies for domestic heating. Based on combustion tests with a wide range of fuel qualities we validated fuel indexes from the literature. We calculated the values for predicting total suspended particulate (TSP) matter and nitrogen oxide (NO_x) emission of 39 biomass-derived fuels. Combustion tests conducted in 10 different small-scale appliances provided experimental data. The combustion technologies had a nominal load between 6 and 140 kW_th. We measured TSP and NO_x emissions during the stable phases of the experiments. The evaluation considered 529 combustion test intervals. All tested indexes for predicting the TSP corresponded well to the measured values. The correlation analysis confirmed that these indexes are associated with each other and are basically dominated by the concentration of potassium. The results regarding NO_x emissions confirm previous findings from the literature by showing the typical nonlinear relation between nitrogen content of the fuel and NO_x in the flue gas. Overall the comparison of the fuel indexes with the practical data indicated also an influence of the combustion technologies.

Several methods are available to predict the combustion behavior of fuels. Fuel indexes have been developed either for specific fuel types (e.g., coal, biomass) or their utilization in combustion technology (fluidized bed, grate systems). This study deals with the validation of fuel indexes for biomass fuels utilized in small-scale appliances for residential heating. Laboratory analysis data of 33 biomass-derived fuels were used for determining indexes for predicting slag formation tendencies. Indexes were selected that have been reported and previously applied in the literature. They vary in terms of their derivation: ratio or concentration of specific components that are relevant for ash chemistry, temperature-based indexes, and empirical correlations. Combustion tests with 9 different small-scale appliances were conducted to gain experimental data. The appliances had a nominal load between 6 kW_th and 140 kW_th. After each experiment, the fraction of fuel ash that formed slag was quantified. Because of several boiler–fuel combinations in total, data from 90 combustion experiments were available for evaluation. The comparison of the quantified slag with the calculated slagging indexes showed that the applicability was strongly dependent on the (chemical) background of the respective index. Also, the fuel composition (e.g., fuels rich in calcium, silicon or phosphorus) plays an important role. Thus, available indexes are not applicable without restrictions and require a closer look on fuel properties and possible ash transformation mechanisms. Overall, the comparison of the fuel indexes with practical data (slag formation) also indicated an influence of the combustion technologies and operation conditions. The comparison of indexes that predict particulate matter and nitrogen oxide emissions with data measured during combustion experiments was evaluated as well. These results will be described in the second part of the present work.

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)

Fluidized bed gasification of sewage sludge is a promising method for its valorisation due to the fuel flexibility of the process. The main drawbacks are the impurities present in the producer gas, with a high tar content, and its low calorific value. In this study, sewage sludge and wood mixtures are gasified in a fluidized bed. A tar cracking reactor is used to reduce the amount of tars and to increase the calorific value of the producer gas. Sewage sludge char is employed for tar cracking with a real producer gas, showing the feasibility of the process with a tar conversion of about 80% at the beginning. The test was conducted for several hours and tar deactivation was observed, which lead to a decrease of tar conversion to about 35% after 5 hours. Reactivating the char with steam increases again the tar conversion up to 84%, however, the subsequent deactivation was found to be faster compared to the one for fresh char. First tests using char from the gasification process in the tar cracking unit also show promising results.