The viability of thermochemical energy storage for a given application is often determined by the reaction kinetics under process conditions. For high exergetic efficiency the process needs to operate in close proximity to the reaction equilibrium. Thus, accurate kinetic models that include the effect of the reaction equilibrium are required.

In the present work, different parametrization methods for the equilibrium term in the General Kinetic Equation are evaluated by modeling the kinetics of two reaction systems relevant for thermochemical energy storage (CaC2O4 and CuO) from experimental data. A non-parametric modeling method based on tensor decompositions is used that allows for a purely data driven assessment of different parametrization methods.

Our analysis shows that including a suitable equilibrium term is crucial. Omitting the equilibrium term when modeling formation reactions can lead to seemingly negative activation energies. Our tests also show that for formation reactions, the reaction rate decreases much faster towards the equilibrium than theory predicts. We present an empirical modeling approach that can predict the reaction rate of gas-solid reactions, regardless of the shortcomings of theory. In this way, non-parametric modeling offers a powerful tool for applied research and may contribute to the advancement of the thermochemical energy storage technology.

The necessity of recycling anthropogenically used phosphorus to prevent aquatic eutrophication and decrease the economic dependency on mined phosphate ores encouraged recent research to identify potential alternative resource pools. One of these resource pools is the ash derived from the thermochemical conversion of sewage sludge. This ash is rich in phosphorus, although most of it is chemically associated in a way where it is not plant available. The aim of this work was to identify the P recovery potential of ashes from sewage sludge co-conversion processes with two types of agricultural residues, namely wheat straw (rich in K and Si) and sunflower husks (rich in K), employing thermodynamic equilibrium calculations. The results indicate that both the melting behavior and the formation of plant available phosphates can be enhanced by using these fuel blends in comparison with pure sewage sludge. This enhanced bioavailability of phosphates was mostly due to the predicted formation of K-bearing phosphates in the mixtures instead of Ca/Fe/Al phosphates in the pure sewage sludge ash. According to the calculations, gasification conditions could increase the degree of slag formation and enhance the volatilization of K in comparison with combustion conditions. Furthermore, the possibility of precipitating phosphates from ash melts could be shown. It is emphasized that the results of this theoretical study represent an idealized system since in practice, non-equilibrium influences such as kinetic limitations and formation of amorphous structures may be significant. However, applicability of thermodynamic calculations in the prediction of molten and solid phases may still guide experimental research to investigate the actual phosphate formation in the future.

Wood log stoves are a common residential heating technology that produce comparably high pollutant emissions. Within this work, a detailed CFD model for transient wood log combustion in stoves was developed, as a basis for its optimization. A single particle conversion model previously developed by the authors for the combustion of thermally thick biomass particles, i.e. wood logs, was linked with CFD models for flow and turbulence, heat transfer and gas combustion. The sub-models were selected based on a sensitivity analysis and combined into an overall stove model, which was then validated by simulations of experiments with a typical wood log stove, including emission measurements. The comparison with experimental results shows a good accuracy regarding flue gas temperature as well as CO2 and O2 flue gas concentrations. Moreover, the characteristic behavior of CO emissions could be described, with higher emissions during the ignition and burnout phases. A reasonable accuracy is obtained for CO emissions except for the ignition phase, which can be attributed to model simplifications and the stochastic nature of stove operation. Concluding, the CFD model allows a transient simulation of a stove batch for the first time and hence, is a valuable tool for process optimization.

In order to evaluate the performance of an electrostatic precipitator (ESP), comprehensive test runs investigating both particulate matter (PM) and gaseous emissions were performed by using softwood pellets as well as alternative biomass feedstocks such as short rotation coppice (poplar) and biomass residues (maize). An ESP was directly integrated in a commercially available small-scale biomass boiler. Based on wet chemical analyses of the fuels, so-called fuel indexes were calculated to deliver primary information on the expected combustion behaviour. The overall aim was to determine appropriate operating conditions, to optimise combustion parameters in order to minimise PM and gaseous emissions as well as to inhibit ash related problems. This was done by an efficient combination of primary (air staging in combination with an innovative control system) and secondary measures (integration of an ESP) and showed an enormous potential for both, a stable plant operation and reduced PM emissions. Thus the findings provide the basis for developing a fuel flexible, low emission and highly efficient biomass boiler in the sector of small-scale combustion systems.

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.

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.

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"

Microalgal biomass as a feedstock for biogas production is linked to the parameters biomass productivity and biogas yield. Besides an easy-to-use strain for anaerobic digestion, the photobioreactor (PBR) design is important. A microalgae strain selection revealed Eustigmatos magnus (SAG 36.89) as the most promising strain yielding an average of 100 mg total suspended solids (TSS) L−1 day−1. The strain was tested in cost-effective sleevebag-PBR-systems of 10 cm, 20 cm and 30 cm diameter facing the light from the front or laterally. Highest mean productivity on a volumetric basis was measured in PBRs with the lowest diameter (104 and 117 mg L−1 day−1. The highest productivity per m−2 was achieved in 10 cm PBRs with front light configuration (9.35 g TSS m−2 day−1). The lateral light configuration of 10 cm PBRs had positive aspects such as the lowest mean water demand to produce 1 kg TSS (481 L−1 kg−1) and the lowest mean energy demand for medium separation of 1 kg TSS (106 Wh). The concentrated microalgal biomass was then subjected to ultrasonication and thermal pre-treatment (90 °C and 120 °C) and tested in BMP tests. Mesophilic anaerobic mono-digestion of untreated microalgae biomass led to a methane (CH4) yield of 343 L−1 kg−1 volatile solids (VS). Thermal pre-treatment at 120 °C resulted in significantly increased CH4 yields of 430 L−1 kg−1 VS. As thermal pre-treatment can be easily installed nearby a biogas plant it could be an interesting option for AD of microalgal biomass with only little investment.

Climate change affects the frequency and intensity of extreme weather, the results of which include production losses and climate-induced crop productivity fluctuations.

Double-cropping systems (DCSs) have been suggested as a way to increase biomass-production while simultaneously delivering environmental benefits. In a three-year field-test, two DCSs based on maize and sorghum as the main crop and rye as the preceding winter crop were compared with each other and compared with 2 single-cropping systems (SCSs) of maize or sorghum; there were comparisons of growth dynamics, optimal harvesting and growing time as well as biomass and methane yield. In addition, the impact of variety and harvest time on the winter rye optimal biomass yield was studied.

The experiments clearly showed the superiority of the DCS over the SCS. Within the DCS, the rye/sorghum combination achieved significantly higher biomass yields compared to those of the rye/maize combination. The highest dry matter biomass yield was achieved during year 1 at 27.5 ± 2.4 t∙ha−1, during which winter rye contributed 8.3 ± 0.7 t∙ha−1 and sorghum contributed 19.2 ± 1.8 t∙ha−1. At the experimental location, which is influenced by a Pannonia climate (hot and dry), the rye/sorghum DCS was able to obtain average methane yields per hectare, 9300 m3, whereas the rye/maize combination reached 7400 m3. In contrast, the rye, maize and sorghum SCSs achieved methane yields of 4800, 6100 and 6500 m3 ha−1, respectively. The study revealed that the winter rye and sorghum DCS is a promising strategy to counteract climate change and thus guarantee crop yield stability.