Fault-Detection (FD) is essential to ensure the performance of solar thermal systems. However, manually analyzing the system can be time-consuming, error-prone, and requires extensive domain knowledge. On the other hand, existing FD algorithms are often too complicated to set up, limited to specific system layouts, or have only limited fault coverage. Hence, a new FD algorithm called Fault-Detective is presented in this paper, which is purely data-driven and can be applied to a wide range of system layouts with minimal configuration effort. It automatically identifies correlated sensors and models their behavior using Random-Forest-Regression. Faults are then detected by comparing predicted and measured values.

The algorithm is tested using data from three large-scale solar thermal systems to evaluate its applicability and performance. The results are compared to manual fault detection performed by a domain expert. The evaluation shows that Fault-Detective can successfully identify correlated sensors and model their behavior well, resulting in coefficient-of-determination scores between R²=0.91 and R²=1.00. In addition, all faults detected by the domain experts were correctly spotted by Fault-Detective. The algorithm even identified some faults that the experts missed. However, the use of Fault-Detective is limited by the low precision score of 30% when monitoring temperature sensors. The reason for this is a high number of false alarms raised due to anomalies (e.g., consecutive days with bad weather) instead of faults. Nevertheless, the algorithm shows promising results for monitoring the thermal power of the systems, with an average precision score of 91%.

A sustainable energy supply can only be achieved by a flexible, cross-sectoral energy system utilizing the specific advantages of the various renewable technologies. In this workshop possible roles of different technologies will be discussed based on a previous discussion of the users’ needs among the different sectors. In this a special focus should be given on the flexibility provision via the heating sector. By bringing together different users, representing municipal and industrial energy supply, and technological experts from different IEA Technology Collaboration Programmes (TCP) the workshop should support a holistic discussion.

List of presentations: 

• Wien Energie‘s vision of a sustainable energy and ressource supply of Vienna, Teresa Schubert, Wien Energie, Austria
• Digitalization of energy management systems – optimization of internal energy use as an industrial company, Maria Lechner, INNIO Jenbacher, Austria
• Flexible Bioenergy and System Integration, Elina Mäki, VTT Technical Research Centre of Finland, Finland Task Leader – IEA Bioenergy Task 44 Flexible Bioenergy and System Integration
• Use Case: Syngas platform Vienna for utilization of biogenic residues, Matthias Kuba, BEST – Bioenergy and Sustainable Technologies, Austria
• Transformation of District Heating and Cooling Systems towards high share of renewables, Ingo Leusbrock, AEE INTEC, Austria – Lead of Austrian delegation – IEA DHC Annex TS5 Integration of Renewable Energy Sources into existing District Heating and Cooling Systems
• Opportunities offered by long-term heat storages and large-scale solar thermal systems, Viktor Unterberger, BEST – Bioenergy and Sustainable Technologies, Austria Task Manager – IEA SHC Task 68 Efficient Solar District Heating Systems
• Possibilities through digitalization on the example of District Heating and Cooling, Dietrich Schmidt, Fraunhofer Institute for Energy Economics and Energy System Technology IEE, Germany – Operating Agent – IEA DHC Annex TS4 Digitalisation of District Heating and Cooling

List of contributing IEA Tasks:

• IEA Bioenergy Task 44 Flexible Bioenergy and System Integration
• EA DHC Annex TS5 Integration of Renewable Energy Sources into existing District Heating and Cooling Systems
• IEA SHC Task 68 Efficient Solar District Heating Systems
• IEA DHC Annex TS4 Digitalisation of District Heating and Cooling

Chemical Looping Combustion (CLC) is a highly efficient CO2 separation technology with no direct contact between combustion air and fuel. A metal oxide is used as oxygen carrier (OC) in a dual fluidized bed to generate clean CO2. The use of solid fuels, especially biomass, is the focus of current research, because of the possibility of “negative” CO2-emissions. The OC is a key component, because it must meet special requirements for solid fuels, which are different to gaseous fuels. Most frequently naturals ores or synthetic materials are used as OC. Synthetic OC are characterised by higher reactivity at the expense of higher costs. For this reason, so far not so many experiments have been conducted on a larger scale with synthetic OC on solid CLC. This work deals with the synthetic perovskite C28 and investigating the suitability as oxygen carrier in an 80 kWth pilot plant for chemical looping combustion with biogenic fuels. The experiments show a significantly increased combustion efficiency of 99.6 % compared to natural ores and a major influence of the solid circulation rate on general performance, whereby carbon capture rates up to 98.3 % were reached. Furthermore, the role of the fuel reactor's counter-current flow column and its impact on better gas conversion was investigated. C28 suffered no deactivation or degradation over the experimental time, but first traces of ash layer formation, phase shifting and attrition of fines could be detected. The focus of further research should lie on long-term stability and reactivity for their high impact on the economic scale up of C28.

Both the planning and operation of complex, multi-energy systems increasingly rely on optimization. This optimization requires the use of mathematical models of the system components. The model most often used to describe thermal storage, and especially in the common mixed-integer linear program (MILP) formulation, is a simple integrator model with a linear loss term. This simple model has multiple inherent drawbacks since it cannot be applied to represent the temperature distribution inside of the storage unit. In this article, we present a novel approach based on multiple layers of variable size but fixed temperature. The model is still linear, but can be used to describe the most relevant physical phenomena: heat losses, axial heat transport, and, at least qualitatively, axial heat conduction. As an additional benefit, this model makes it possible to clearly distinguish between heat available at different temperatures and thus suitable for different applications, e.g., space heating or domestic hot water. This comes at the cost of additional binary decision variables used to model the resulting hybrid linear dynamics, requiring the use of state-of-the-art MILP solvers to solve the resulting optimization problems. The advantages of the more detailed model are demonstrated by validating it against a standard model based on partial differential equations and by showing more realistic results for a simple energy optimization problem.

The recovery of phosphorus (P) from sewage sludge ashes has been the focus of recent research due to the initiatives for the use of biogenic resources and resource recovery. This study investigates the ash transformation chemistry of P in sewage sludge ash during the co-gasification with the K-Si- and K-rich agricultural residues wheat straw and sunflower husks, respectively, at temperatures relevant for fluidized bed technology, namely 800 °C and 950 °C. The residual ash was analyzed by ICP­AES, SEM/EDS, and XRD, and the results were compared to results of thermochemical equilibrium calculations. More than 90% of P and K in the fuels were retained in the residual ash fraction, and significant interaction phenomena occurred between the P-rich sewage sludge and the K-rich ash fractions. Around 45–65% of P was incorporated in crystalline K-bearing phosphates, i.e., K-whitlockite and CaKPO4, in the residual ashes with 85–90 wt% agricultural residue in the fuel mixture. In residual ashes of sewage sludge and mixtures with 60–70 wt% agricultural residue, P was mainly found in Ca(Mg,Fe)-whitlockites and AlPO4. Up to about 40% of P was in amorphous or unidentified phases. The results show that gasification provides a potential for the formation of K-bearing phosphates similar to combustion processes.

Measuring the producer gas from biomass gasification is very challenging and the use of several methods is required to achieve a complete characterization. Various techniques are available for these measurements, offering very different affordability or time demand requirements and the reliability of these techniques is often unknown. In this work an assessment of commonly employed measuring methods is conducted with a round robin. The main permanent gases, light hydrocarbons, tars, sulfur and nitrogen compounds were measured by several partners employing a producer gas obtained from fluidized bed gasification of wood and miscanthus with steam. Online and offline methods were used for this purpose and their accuracy, repeatability and reproducibility are here discussed. The results demonstrate the reliability of gas chromatography for measuring the main permanent gases, light hydrocarbons, benzene and H2S, validating the obtained results with other methods. An online method could also measure NH3 with a reasonable accuracy, but deviations were present for compounds at even lower concentrations. Regarding tar sampling and analysis, the main source of variability in the results was the analysis of the liquid samples, especially for heavier compounds. The presented work pointed out the need for a complementary use of several techniques to achieve a complete characterization of the producer gas from biomass gasification, and the suitability of certain online techniques as well as their limitations.

Modern buildings with floor heating or thermally activated building structures (TABS) offer a significant potential for shifting the thermal load and thus reduce peak demand for heating or cooling. This potential can be realized with the help of model predictive control (MPC) methods, provided that sufficiently descriptive mathematical models describing the thermal characteristics of the individual thermal zones exist. Creating these by hand or from more detailed simulation models is infeasible for large numbers of zones; instead, they must be identified automatically based on measurement data. We present an approach using only open source tools based on the programming language Julia that allows to robustly identify simple thermal models for heating and cooling usable in MPC optimization. The resulting models are used in a distributed optimization scheme that co-ordinates the individual zones and buildings of a city quarter in order to best support an energy hub.

Modern buildings with floor heating or thermally activated building structures (TABS) offer a significant
potential for shifting the thermal load and thus reduce peak demand for heating or cooling. This potential can be realized with the help of model predictive control (MPC) methods, provided that sufficiently descriptive mathematical models describing the thermal characteristics of the individual thermal zones exist. Creating these by hand or from more detailed simulation models is infeasible for large numbers of zones; instead, they must be identified automatically based on measurement data. We present an approach using only open source tools based on the programming language Julia that allows to robustly identify simple thermal models for heating and cooling usable in MPC optimization. The resulting models are used in a distributed optimization scheme that co-ordinates the individual zones and buildings of a city quarter in order to best support an energy hub.

A better understanding of the underlying motives of consumers considering a new RESS (heating,
cooling and electricity) can contribute to create favorable conditions for an energy transition.
Therefore, the main objectives of this research project are to:
▪ Identify motives of consumers interested in ordeciding for a certain RESS
▪ Assess the impact of gender and intersectingaspects, such as age, income and education on these motives.

Der Leitfaden „Energiegemeinschaften im Tourismus“ zeigt, welche Möglichkeiten Energiegemeinschaften für Tourismusbetriebe, ihre Beschäftigten und Menschen, die in Tourismusregionen leben, bieten können und wie eine Energiegemeinschaft ins Leben gerufen werden
kann.

Sector coupling is expected to play a key role in the decarbonization of the energy system by enabling the integration of decentralized renewable energy sources and unlocking hitherto unused synergies between generation, storage and consumption. Within this context, a transition towards hybrid energy networks (HENs), which couple power, heating/cooling and gas grids, is a necessary requirement to implement sector coupling on a large scale. However, this transition poses practical challenges, because the traditional domain-specific approaches struggle to cover all aspects of HENs. Methods and tools for conceptualization, system planning and design as well as system operation support exist for all involved domains, but their adaption or extension beyond the domain they were originally intended for is still a matter of research and development. Therefore, this work presents innovative tools for modeling and simulating HENs. A categorization of these tools is performed based on a clustering of their most relevant features. It is shown that this categorization has a strong correlation with the results of an independently carried out expert review of potential application areas. This good agreement is a strong indicator that the proposed classification categories can successfully capture and characterize the most important features of tools for HENs. Furthermore, it allows to provide a guideline for early adopters to understand which tools and methods best fit the requirements of their specific applications.

The cyanobacterial genus Synechocystis is of particular interest to science and industry because of its efficient phototrophic metabolism, its accumulation of the polymer poly(3-hydroxybutyrate) (PHB) and its ability to withstand or adapt to adverse growing conditions. One such condition is the increased salinity that can be caused by recycled or brackish water used in cultivation. While overall reduced growth is expected in response to salt stress, other metabolic responses relevant to the efficiency of phototrophic production of biomass or PHB (or both) have been experimentally observed in three Synechocystis strains at stepwise increasing salt concentrations. In response to recent reports on metabolic strategies to increase stress tolerance of heterotrophic and phototrophic bacteria, we focused particularly on the stress-induced response of Synechocystis strains in terms of PHB, glycogen and photoactive pigment dynamics. Of the three strains studied, the strain Synechocystis cf. salina CCALA192 proved to be the most tolerant to salt stress. In addition, this strain showed the highest PHB accumulation. All the three strains accumulated more PHB with increasing salinity, to the point where their photosystems were strongly inhibited and they could no longer produce enough energy to synthesize more PHB.

Mikro-Netze (Microgrids), ein Unterbereich der Intelligenten Strom/Energie-Netze (Smartgrids),
die sich durch eine enge räumliche Bindung von Energieerzeugungseinheiten und Verbraucher
auszeichnen wird international ein sehr starkes Wachstum zugeschrieben. Microgrids sind kleine,
lokale Energienetze für Strom, Wärme und Kälte, die Haushalte, Betriebe und Gemeinden mit
Energie versorgen. Diese lokalen und regionalen Konzepte der Energieversorgung können in
Zukunft einen wesentlichen Beitrag in Richtung Energieunabhängigkeit und effizientere
Integration von Erneuerbaren in das Energiesystem leisten. Sie können ihren Energiebedarf
selbstständig aus erneuerbaren Energien oder anderen Energieformen decken, etwa Biomasse,
Wärmepumpen, PV, Windräder oder Kraftwärmekopplungen. Diese können nach den
individuellen Zielen der Gemeinden, Haushalte oder der Betriebe gesteuert werden, um
Kostenreduktionen, CO2 Einsparungen oder eine Erhöhung des Unabhängigkeitsgrades zu
realisieren. Sie berechnen den aktuellen und zukünftigen Verbrauch und können Energie im
Bedarfsfall dorthin verlagern, wo sie gerade benötigt wird, oder sie reduzieren den
Energieverbrauch direkt.

Most industrial fixed-bed biomass gasification systems usually operate at steady-state to produce the maximum amount of energy possible although they can principally modulate their loads to compensate for the fluctuations of other volatile renewable energy systems. To unleash their full load modulation capability, their typically traditional control strategies should be improved, their gas residence times affected by typically basic char removal strategies adjusted and any required manual interaction of an operator avoided. In this respect, a new controller for the char handling (accumulation and removal) of the reduction zone in a fixed-bed biomass gasifier of a representative industrial small-scale gasification system is developed and experimentally verified. This new controller consists of a recursive least-squares estimator for the flow resistance of the gasifier representing the amount of char inside and a switching controller for rotating a grate located at its bottom. The experimental verification reveals that only the traditional (pressure-based) controller requires manual adjustment of the thresholds. Moreover, the new controller (flow resistance based) significantly reduces the fluctuation range during partial load and stabilizes the temperature and pressure downstream the gasifier. This provides the basis for enhancing its fuel flexibility too and is an important feature for flexible operation in future.

Bed materials and their catalytic activity are two main parameters that affect the performance of the dual fluidized bed (DFB) gasification system in terms of product gas composition and tar levels. Two sources of bed materials were used for the operation of a commercial DFB gasification system in Thailand, using woodchips as a biomass feedstock. One source of the bed materials was the calcined olivine which had been used in the Gussing Plant, Austria, and the other activated bed material was a mixture of fresh Chinese olivine and used Austrian olivine with additives of biomass ash, calcium hydroxide and dolomite. These bed materials were collected and analysed for morphological and chemical composition using a scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS) and X-ray fluorescence spectroscopy (XRF). The product gas was cleaned in a scrubber to remove tars, from which the samples were collected for gravimetric tar analysis. Its composition data was automatically recorded at the operation site before it entered the gas engine. From the SEM, EDS and XRF analyses, calcium-rich layers around the bed materials were observed on the activated bed material. The inner layers of bed materials collected were homogeneous. Biomass ash, which was generally added to the bed materials, had significant calcium and potassium content. These calcium-rich layers of the bed materials, from the calcium hydroxide, biomass ash and dolomite, influenced system performance, which was determined by observing lower tar concentration and higher hydrogen concentration in the product gas.

„Welche Heizung passt zu mir/uns? Vielleicht auch Kühlen oder selber Strom erzeugen?“ – Diese
Fragen stellen sich oft, wenn der Traum von den eigenen vier Wänden näher rückt. Egal ob bei Neubau
oder Sanierung, die Wahl eines passenden Energiebereitstellungssystems (EBS) sollte wohl überlegt
sein. Neben den technologischen Fragen sind es auch persönliche Motive, welche die Entscheidung
der Nutzer*innen beeinflussen.

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