Poly(3-hydroxybutyrate) (PHB) is a biobased and biodegradable polymer with properties comparable to polypropylene and therefore has the potential to replace conventional plastics. PHB is intracellularly accumulated by prokaryotic organisms. For the cells PHB functions manly as carbon and energy source, but all possible functions of PHB are still not known. Synechocystis (cyanobacteria) accumulates PHB using light as energy and CO2 as carbon source. The main trigger for PHB accumulation in cyanobacteria is nitrogen and phosphorous depletion with simultaneous surplus of carbon and energy. For the above reasons, obtaining knowledge about external factors influencing PHB accumulation is of highest interest. This study compares the effect of continuous light exposure and day/night (16/8 h) cycles on selected physiology parameters of three Synechocystis strains. We show that continuous illumination at moderate light intensities leads to an increased PHB accumulation in Synechocystis salina CCALA 192 (max. 14.2% CDW – cell dry weight) compared to day/night cycles (3.7% CDW). In addition to PHB content, glycogen and cell size increased, while cell density and cell viability decreased. The results offer new approaches for further studies to gain deeper insights into the role of PHB in cyanobacteria to obtain bioplastics in a more sustainable and environmentally friendly way.

Bioeconomy strategies promote higher shares of biomass products in material and energy sectors. Deploying by-products from sawmills is therefore of major interest. This study aims at analyzing market characteristics and implications of bioeconomy strategies by combining three methods: First, an econometric supply and demand model for sawmill by-products (SBP) was estimated based on data from 2001 to 2020. Second, the model was used to analyze a reference and a bioeconomy scenario. Third, a use case was analyzed dealing with the integration of wood gasification and BioSNG (Synthetic Natural Gas) production into Austrian flows of SBP. The results indicate that SBP supply reacts unit-elastic to sawnwood exports, while both supply and demand respond inelastic to SBP prices. Demand is positively inelastic related to SBP as input in panel and pellet production. In a bioeconomy scenario, long-term supply would exceed demand, resulting in additional SBP to be used for gasification. A 100 MW BioSNG plant converting these SBP could provide 528 MWh BioSNG per year. This is a 11 % share of the Austrian target value of 5 TWh green gas.

This study investigates the detailed ash transformation process during the combustion of rice husks in entrained flow conditions. The experiments were conducted in a lab-scale drop tube furnace at 1200 and 1450 °C in pyrolysis/devolatilization (using N2) and combustion (using air) conditions. The detailed ash transformation process during the different fuel conversion stages in combustion (i.e., devolatilization and char combustion) was investigated by comparing the results obtained in the pyrolysis/devolatilization experiments with the combustion experiments. The resulting residual chars, ashes, and particulate matter (PM) were collected and characterized by scanning electron microscopy and energy-dispersive X-ray spectroscopy (SEM–EDS), X-ray diffraction (XRD), inductively coupled plasma atomic emission spectroscopy (ICP-AES), ion chromatography (IC), and CHN analyses. Furthermore, the obtained results were interpreted via thermodynamic equilibrium calculations (TECs). For all investigated conditions, Si, Ca, and Mg were retained entirely in the coarse ash and char fractions (>1 μm). Meanwhile, K and P were found in coarse ash/char fractions and fine particulate fractions (<1 μm). A moderate, at 1200 °C, to high share, at 1450 °C, of the detected K and P was found in the fine particle fractions after combustion. The majority (>95%) of the detected S and Cl were volatilized during the experiments. The study showed an accumulation of minor ash-forming elements (i.e., K, Ca, Mg, P) on the inner part of rice husk chars, initiating melt formation during the char combustion stage. The identified melt at 1200 °C after combustion was rich in Si with minor amounts of K, Ca, Mg, and P. The share of molten ashes was increased at 1450 °C compared to that at 1200 °C. Overall, the results presented in this work reveal detailed insights into the ash transformation processes taking place in different parts of the fuel during the combustion of rice husks in entrained flow conditions.

The present study investigates how three different silicate-based bed materials behave in bubbling fluidized bed combustion of a model agricultural residue with respect to ash composition, namely barley straw. Quartz, natural K-feldspar, and olivine were all used in combustion at 700 °C, and the resulting layer formation and bed agglomeration characteristics were determined. Based on this, a general reaction model for bed ash from agricultural residues was proposed, taking into account the reactivity of the different silicates investigated towards the main ash-forming elements K, Ca, and Si. The proposed reaction model links bed material interaction with K-rich bed ash to the degree of polymerization of the silicate bed material, where addition reactions occur in systems with high polymerization, predominately in quartz, and substitution reactions dominate for depolymerized silicates such as K-feldspar and olivine.

Green Carbon Liquids - staged condensation from lab-scale pyrolysis; Green Gas - Green Heat for Industrie from Biogenic Waste; Biohydrogen - Implementation of Dark Fermentation for Industrial Wastewater Treatment; Effects of the climate crisis and pesticide use on fatty acida in the food web; Syngas production from biogenic residues and waste via advanced dual fluidized bed gasification; New developments in gas cleaning for the production of C-based products and fuels via gasification; Advancements in Fischer-Tropsch synthesis using a slurry bubble column reactor; Biofuels - a crucial part of decarbinisation; Speed-Up Algorithms for advanced simulations; Multiscale modeling of metal oxide and biomass conversion for chemical looping processes; Multiscale modeling of metal oxide and biomass conversion for chemical looping processes; Model-Based Control of the Generated Steam Mass Flow in a Fluidized-Bed Waste Incineration Plant; Modular, predictive, optimization-based supervisory control of multi-energy systems; Monitoring of a Renewable Flow Battery; Use cases of optimally planned multi-energy systems with OptEnGrid: hotel resort and renewable energy communities; Optimal Design of Multi-Energy Systems using OptEnGrid; Sustainability assessment: mere obligation or a key to success; 

In this work, the fate of the ash-forming elements during bubbling fluidized bed combustion and gasification of P-rich sewage sludge (SS) and mixtures with either Si-K-rich wheat straw (WS) or K-Ca-rich sunflower husks (SH) were investigated. The focus of the study was assessing the feasibility of using fuel blends in fluidized bed systems and potential P recovery from the resulting ashes. The used fuels were pure SS and mixtures including 90 wt.% WS (WSS) and 85 wt.% SH (SHS). The analyzed operating conditions were combustion (930–960 °C, λ: 1.2–1.5) and gasification (780–810 °C, λ: 0.4–0.7) in a 5 kW bench-scale reactor. Residual ash and char fractions were collected from different parts of the 5 kW bubbling fluidized bed (bed, cyclone, filter) and analyzed by CHN, SEM/EDS, XRD, and ICP-AES.

The conversion of the fuel mixtures achieved a steady state under the used process conditions except for the combustion of WSS, which led to the formation of large bed agglomerates with the bed material. The morphology of ash samples after combustion showed that SS fuel pellets mostly maintained their integrity during the experiment. In contrast, the ash and char particles from fuel mixtures were fragmented, and larger quantities were found in the cyclone, the filter, or on interior reactor surfaces. The fate of P was dominated by crystalline Ca-dominated whitlockites in all ash fractions, partially including K for the fuel mixtures SHS and WSS. 76–81 % of ingoing P was found in the bed residue after combustion and gasification of the SS-fuel. After conversion of the fuel mixtures SHS and WSS, the share was lower at 22–48 %, with larger shares of P in the entrained fractions (25–34 %). The quantity of identified crystalline compounds was lower after gasification than combustion, likely due to the limited interaction of ash-forming elements in the residual CHN matrix. Altogether, the results show that fuel mixtures of sewage sludge with agricultural residues could expand the fuel feedstock and enable P recovery. This may be used in the fuel and process design of upscaled fluidized bed processes or systems employing both combustion and gasification.

Polyhydroxyalkanoates (PHA) are a promising bio-based alternative to traditional plastics derived from petroleum. Cyanobacteria are photosynthetic organisms that produce PHA from CO2 and sunlight, which can potentially reduce production costs and environmental footprint in comparison to heterotrophic bacteria cultures because (1) they utilize inorganic carbon sources for growth and (2) they do not require intensive aeration for oxygenation. Moreover, supplementing precursors such as propionate, acetate, valerate, etc., can be used to obtain various copolymers with plastic customizable properties in comparison to the classical homopolymers, such as polyhydroxybutyrate, PHB. This critical review covers the latest advances in PHA production, including recent discoveries in the metabolism interplay between PHA and glycogen production, and new insights into cultivation strategies that enhance PHA accumulation, and purification processes. This review also addresses the challenges and suggests potential solutions for a viable industrial PHAs production process.

Reliable experimental data and models are required to better understand and design chemical looping processes with oxygen carrier materials like ilmenite. A dubious variability of suggested kinetics for similar oxygen carrier materials has been presented in the literature. Part I of this work focuses on thermogravimetric analysis (TGA) of gas–solid kinetics and addresses several of its challenges, which are possible reasons behind such deviations. The reduction of synthetic ilmenite (60 mass% Fe2O3 ＋40 mass% TiO2) powder with H2 in a TGA system was investigated for this purpose.
Multiple steps were necessary to overcome mass transfer limitations during the measurements: (i) small sample masses down to 1.6 mg, (ii) high gas flow rates, (iii) a suitable sample carrier and (iv) proper sample dispersion on the sample carrier. Three types of sample carriers (crucible, basket and plate) were tested; the plate showed the best performance overall. It was alarming that an exemplary increase in sample mass from 1.6 to 3 mg, which was still significantly lower than all other studies reviewed, already introduced a noticeable influence of diffusion. Isothermal (650–950 °C, 17–50 vol% H2) and nonisothermal parameter studies were conducted and yielded vastly different isoconversional activation energies. A computational fluid dynamics (CFD) study of the TGA system suggested considerable axial dispersion of H2 influencing the initial conversion period.
These findings help to assess the reliability of kinetic studies and guide towards diffusion-free, kinetic measurements. The results will be used for model development in part II.

Chemical looping combustion has the potential to be an efficient and low-cost technology capable of contributing to the reduction of the atmospheric concentration of CO2 in order to reach the 1.5/2 °C goal and mitigate climate change. In this process, a metal oxide is used as oxygen carrier in a dual fluidized bed to generate clean CO2 via combustion of biomass. Most commonly, natural ores or synthetic materials are used as oxygen carrier whereas both must meet special requirements for the conversion of solid fuels. Synthetic oxygen carriers are characterized by higher reactivity at the expense of higher costs versus the lower-cost natural ores. To determine the viability of both possibilities, a techno-economic comparison of a synthetic material based on manganese, iron, and copper to the natural ore ilmenite was conducted. The synthetic oxygen carrier was characterized and tested in a pilot plant, where high combustion efficiencies up to 98.4% and carbon capture rates up to 98.5% were reached. The techno-economic assessment resulted in CO2 capture costs of 75 and 40 €/tCO2 for the synthetic and natural ore route respectively, whereas a sensitivity analysis showed the high impact of production costs and attrition rates of the synthetic material. The synthetic oxygen carrier could break even with the natural ore in case of lower production costs and attrition rates, which could be reached by adapting the production process and recycling material. By comparison to state-of-the-art technologies, it is demonstrated that both routes are viable and the capture cost of CO2 could be reduced by implementing the chemical looping combustion technology.

Various single particle models to describe the conversion of porous solids with gaseous reactants are available in the literature. It is, therefore, not obvious which models should be selected for specific problems and applications. This work focuses on two popular types of particle models: the volumetric model (VM) and the layer model (LM). Different variations of the layer model were considered: the standard layer model, which is similar to common shrinking core models, and an extended layer model, which solves inherent problems of the shrinking core approach by replacing surface reactions with volumetric reactions. For the first time, all these models were benchmarked together regarding prediction quality and computational cost for relevant applications: gasification and oxidation of biochar, reduction of nickel oxide and oxidation of magnetite. These cases covered a wide range of Thiele moduli and Biot numbers. The volumetric model reliably predicted the conversion for all cases considered. Its computational effort was, however, significantly higher than for the layer models. Suitable reactions kinetics in combination with heat of reaction and pore diameters were integral to prediction accuracy. Char oxidation, having a high Thiele modulus, could be described suitably by the standard layer model and the extended layer model, when it accounted for the residual ash layer. Char gasification and nickel oxide reduction had moderate Thiele moduli, rendering the standard layer model unsuitable in the general case. The extended layer model overcomes these limitations due to its volumetric reaction approach. All layer models showed inferior temperature predictions for biochar gasification and magnetite oxidation owing to their lower spatial resolution compared to the volumetric model. Additional, possible problems for layer models were addressed.

Biofuels are crucial for reducing emissions in the transport sector, contributing significantly to the objectives of the Fit for 55 package and climate neutrality goals. This role is anticipated to grow in the future as advanced biofuels become increasingly accessible. This expansion will be driven by the full commercial-scale development of technologies, processes, and value chains, supported by ambitious policies and sector-specific targets that will encourage their deployment.

Bioenergy retrofitting may be a short-term strategy to promote the transition from first-generation to advanced bioethanol, as it could improve the cost-competitiveness of the latter. In addition, this strategy could also extend the operational lifetime of first-generation ethanol plants, whose production is restricted by the current European renewable energy regulations. Therefore, this work evaluates two retrofitting scenarios of an existing corn-based first-generation ethanol facility located in Spain from an economic and environmental perspective. In the first case (scenario 1), advanced bioethanol was produced using industrial waste streams included in the Renewable Energy Directive II. The second approach (scenario 2) involves the integration of second-generation technology into the existing first-generation facility. The economic analysis shows that scenario 1 presents a low capital expenditure (CAPEX, €100,000), as it only requires the installation of an industrial waste storage tank. Although, in terms of net present value (NPV), the CAPEX of scenario 2 is higher. It obtains better profitability reaching an NPV of approximately €25,610,000. The environmental assessment identified natural gas consumption as the main contributor to the overall score of the global warming impact category. Consequently, the increased energy demand of the retrofit scenarios, mainly linked to second-generation technology, has a negative impact in terms of greenhouse gas emissions. Therefore, a key aspect to improve the environmental performance of these scenarios would be the replacement of natural gas with a more sustainable alternative, such as bio-based gases.

Bioenergy retrofitting may be a short-term strategy to promote the transition from first-generation to advanced bioethanol, as it could improve the cost-competitiveness of the latter. In addition, this strategy could also extend the operational lifetime of first-generation ethanol plants, whose production is restricted by the current European renewable energy regulations. Therefore, this work evaluates two retrofitting scenarios of an existing corn-based first-generation ethanol facility located in Spain from an economic and environmental perspective. In the first case (scenario 1), advanced bioethanol was produced using industrial waste streams included in the Renewable Energy Directive II. The second approach (scenario 2) involves the integration of second-generation technology into the existing first-generation facility. The economic analysis shows that scenario 1 presents a low capital expenditure (CAPEX, €100,000), as it only requires the installation of an industrial waste storage tank. Although, in terms of net present value (NPV), the CAPEX of scenario 2 is higher. It obtains better profitability reaching an NPV of approximately €25,610,000. The environmental assessment identified natural gas consumption as the main contributor to the overall score of the global warming impact category. Consequently, the increased energy demand of the retrofit scenarios, mainly linked to second-generation technology, has a negative impact in terms of greenhouse gas emissions. Therefore, a key aspect to improve the environmental performance of these scenarios would be the replacement of natural gas with a more sustainable alternative, such as bio-based gases.

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

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

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

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

Pore size distribution is a key parameter in the performance of biobased pyrolytic char in novel applications. In industrial-scale production, the size of feedstock particles typically exceeds a few millimeters. For such particle sizes, it is a challenge to tailor the final properties of the char based only on the process conditions (experimental and modeling-wise). Pyrolysis studies of single particles larger than a few millimeters provide data sets useful for modeling and optimization of the process. Part 1 of this research focused on the pyrolysis of single particles of beech wood, secondary cracking, and its effect on the char porous texture. It contains a quantitative assessment of the effects of five conversion temperatures (from 300 to 840 °C) and two particle dimensions (Ø8 × 10 mm and Ø8 × 16 mm) on the composition of the pyrolysis vapors and pore morphology of the char. Results from real-time temperature and mass changes are presented along with release profiles of 15 vapor constituents measured by infrared spectroscopy. Furthermore, characterization of the collected bio-oil (using GC-MS/FID) and the textural hierarchical structured char (through N2 and CO2 adsorption, Hg porosimetry, and scanning electron microscopy (SEM)) was performed. Cracking of vapors above 500 °C was compound-specific. The polyaromatic hydrocarbons (PAHs) yield, between 680 and 840 °C, increased 5 times for 10 mm particles and 9 times for 16 mm ones. Besides temperature, PAH yield was suspected to correlate with particle length and PAHs/soot deposition in the micropores. Results showed that the macropores accounted for over 80% of the total pore volume, regardless of the temperature and particle length. Increasing the particle length by 60% caused a reduction in the specific surface area (ca. 15% at 840 °C) of the resulting char, mainly due to a reduction in microporosity. Based on the findings, the production conditions for a specific char application are suggested. The obtained data will be used in Part 2 of this research, devoted to subsequent CFD modeling of the process.

The prediction of the structural properties of biobased carbonaceous materials of pyrolytic origin (chars) with only base feedstock properties and process conditions still poses a challenge that hinders char tailoring for novel applications. CFD modeling of single biomass particle conversion can help solve this issue since it allows for the quantification of relations between parameters that are difficult to measure. A model for char tailoring must include a validated representation of the structural changes coupled to all other relevant phenomena occurring during conversion. Part 2 of this study focuses on finding the description of the mentioned aspects to achieve the highest precision of prediction of the structural changes in char by a CFD model. The investigation in Part 2 is composed of three cases focused on accurate description and prediction of (1) bulk density and porosity, (2) secondary vapor reactions on yields and soot formation, and (3) permeability, as well as the outflux and conversion of evolved vapors. The experimental results from Part 1 and the literature data were used to find appropriate descriptions of phenomena and assess the accuracy of the model. The model results indicate that for both particle lengths (10 and 16 mm), a high accuracy of prediction of base structural parameters was achieved. The average prediction error for temperatures between 400 and 840 °C of bulk density was 31 ± 15 kg/m3, and the porosity was 1.8 ± 1.1 vol %. The results also show a low error in the prediction of bulk product yields (dry basis) over the mentioned temperature range, which were: for char 2.8 ± 1.1 wt %, for the condensable fraction 6.5 ± 3.3 wt %, and for the pyrolysis gas 4.1 ± 1.9 wt %. The distribution of secondary char formation was found to be nonuniform below 500 °C. The changes in permeability had a minor influence on the vapor outflux but a non-negligible effect on the soot formation, especially at 840 °C. The results indicate a need for further improvement of the primary degradation model to increase the accuracy of the effect of soot formation on the char structure.

Pyrolyse ist ein althergebrachtes Verfahren, das bereits vor Jahrtausenden zur Herstellung von Kohle praktiziert wurde. Bestrebungen nach Unabhängigkeit von fossilen Ressourcen und klimaneutralen sowie kreislaufwirtschaftlichen Wertschöpfungsketten, führen aktuell zu deutlich steigendem Interesse an dieser Technologie. Durch vielseitige verfahrenstechnische Ausgestaltungsmöglichkeiten stellt die Pyrolyse eine potenzielle Schlüsseltechnologie für verschiedene zum Teil hoch spezifische Anwendungen für stoffliche und energetische Prozessketten dar. Diese Vielfalt an Möglichkeiten resultiert jedoch gleichzeitig in einer hohen Komplexität, die es erschwert einen Überblick über angebotene Anlagen zu bekommen.

Ziel dieser Studie ist es, Informationen vielfältiger Systeme in eine vergleichbare Form zu bringen und dadurch eine Übersicht für Interessierte zu ermöglichen. Der Aufwand der Informationsbeschaffung als initialer Schritt für Umsetzungen soll dadurch reduziert werden. Hierdurch soll zur Realisierung regionaler Pyrolyseprojekte als Bestandteil kreislaufwirtschaftlicher Stoffnutzungskonzepte beigetragen werden.

A dried dairy processing sludge (sludge from wastewater treatment of an effluent from a milk processing plant) was pyrolysed in a single-particle reactor at different temperatures from 400 °C to 900 °C. NH₃ and HCN were measured online and offline by means of FTIR as well as by cumulative sampling in impinger bottles (in 0.05 M H₂SO₄ and 1 M NaOH, respectively) and analysed by photometric method. NO and NO₂ were measured online using a nitric oxide analyser while N₂O was measured by FTIR. Nitrogen (N) in the sludge and in the remaining char, char-N, was determined. Moreover, tar content in pyrolysis gas was measured and tar-N was determined. The results with respect to N mass balance closure are discussed. The different measurements techniques are compared. For pyrolysis at 520 ℃ and 700 ℃ nitrogen in the gas phase was mainly contained as N₂ (36 % and 40 % respectively), followed by NH₃ (15 % and 18 %), tar-N (10 % and 9 %), HCN (1 % and 3 %), NO (1 %) and NO₂ (0.2 %). The dairy processing sludge has very specific properties with organic-N present predominantly as proteins and a high content of inherent Ca. These characteristics affected the distribution of N. The amount of char-N was higher while the amount of tar-N lower than for sewage sludge from literature, at comparable pyrolysis temperature.

First experiments with biogenic residues and a plastic-rich rejects and woody biomass blend were conducted in an advanced 1 MW dual fluidized bed steam gasification demonstration plant at the Syngas Platform Vienna. Wood chips, bark, forest residues, and the plastic-rich rejects and woody biomass blend were tested and the tar composition was analyzed upstream and downstream of the upper gasification reactor, which is designed as a high-temperature column with countercurrent flow of catalytic material. Each feedstock was gasified with olivine as bed material in demonstration scale and is compared to the gasification of softwood pellets with olivine and limestone in pilot scale. A reduction in tar content was observed after countercurrent column for all feedstocks. However, a shift in tar species occurred. While styrene, phenol, and 1H-indene were predominant upstream, naphthalene and polycyclic aromatic hydrocarbons (PAHs) were the prevailing tar species downstream the countercurrent column. Hence, an increase of i.e. anthracene, fluoranthene, and pyrene from the upstream concentration was observed. For pyrene, up to twice the initial concentration was measured. This recombination to PAHs was observed for all feedstocks in demonstration- and pilot-scale. The only exception occurred with limestone as bed material, characterized by a higher catalytic activity in comparison to the typically used olivine. In the perspective of the integrated product gas cleaning, tar with higher temperature of condensation are separated more efficiently in the installed scrubbing unit. Hence, the recombination facilitates an overall decline of tar content after the gas cleaning.

A drastic reduction in the consumption of fossil resources and efficient use are key factors in limiting the further progression of climate change. Cascading use and recycling of residues in the sense of bioeconomy and circular economy are essential. Thermochemical or microbiological conversion can produce various intermediates and endproducts (e.g. biochar, basic chemicals, bioenergy) from biogenic residues. Implemented decentrally, such concepts can reduce transportation efforts, increase the degree of self-sufficiency with raw materials, increase regional added value creation and close (preferably regional) material and energy cycles.

In modern waste management, the energetic utilization of waste is an important key technology. On the one hand, it allows the waste to be disposed of in an environmentally friendly manner and, on the other hand, makes it possible to reduce the use of other controversial energy sources, such as nuclear fission or fossil fuels. However, the efficient and clean incineration of waste is a challenging task due to the strong inhomogeneity of the waste.

The Alpine Region is characterized by a high density of biomass processing and conversion plants. Alps4GreenC sets the scene for transnational utilization of biomass residues in biochar-based value chains. The project aims at:

• Researching opportunities for conversion of biomass residues with focus on biochar production.
• Increasing awareness of citizens, plant owners, policy makers and all involved stakeholders.
• Establishing connection and coordination among Austria, Italy and Slovenia.

Anaerobic acidification of pressed sugar beet pulp (PSBP) is a promising strategy for the transition towards a circular economy. In this work, volatile fatty acids were produced by anaerobic acidification of PSBP and subsequently converted to mcl-polyhydroxyalkanoates. The results point to mesophilic acidification as superior to thermophilic one. At the same time, the pH regulated at the value of 6.0 showed a decisive advantage over both the pH of 7.0 and the lack of pH regulation. Furthermore, the conditions with a hydraulic retention time (HRT) of 10 days significantly outperformed those with an HRT of 6 days. The best-performing process (mesophilic, pH controlled at 6, HRT of 10 days) was successfully scaled up to a 250 L reactor, reaching a volatile fatty acid (VFA) concentration of up to 27.8 g L-1. Finally, the produced VFA were investigated as feedstock for mcl-PHA producers, Pseudomonas citronellolis and Pseudomonas putida. Both strains grew and produced PHA successfully, with P. citronellolis reaching a biomass of 15.6 g L-1 with 38% of mcl-PHA, while P. putida grew to 15.2 g L-1 with a polymer content of 31%. This study proves that acidified PSBP is a valuable feedstock for mcl-PHA production and an important approach to developing biorefineries.

Buildings with floor heating or thermally activated building structures offer significant potential for shifting the thermal load and thus reduce peak demand for heating or cooling. This potential can be realised with the help of model predictive control (MPC) methods, provided that sufficiently descriptive mathematical models of the thermal characteristics of the individual thermal zones exist. Creating these by hand is infeasible for larger numbers of zones; instead, they must be identified automatically based on measurement data. In this paper an approach is presented that allows automatically identifying thermal models usable in MPC. The results show that the identified zone models are sufficiently accurate for the use in an MPC, with a mean average error below 1.5K for the prediction of the zone temperatures. The identified zone models are then used in a distributed optimisation scheme that coordinates the individual zones and buildings of a city quarter to best support an energy hub by flattening the overall load profile. In a preliminary simulation study carried out for buildings with floor heating, the operating costs for heating in a winter month were reduced by approximately 9%. Therefore, it can be concluded that the proposed approach has a clear economic benefit.

The Area Automation and Control at BEST - Bioenergy and Sustainable Technologies GmbH focuses on the optimal operation of sustainable biorefinery and renewable energy systems, the optimal interaction of different technologies and systems and the highly automated operation management
by new digital services.

Char originating from biomass can be used as a sustainable carbon additive in the production of polymer compounds with enhanced characteristics.

Over the last decades the general interest in recycling and upcycling technologies heavily grew and in the agricultural sector, it is not different. Lal estimated already in 2005 that 3,8 billion tons of crop residues alone are produced annually
worldwide.

With respect to the climate objectives Chemical Looping (CL) processes constitute a promising alternative to traditional thermochemical conversion routes. Through the application of solid materials, so-called oxygen carriers (OC), instead of air as oxygen supply, CO2 can be easily separated from the flue gas. By this, biomass can be used for hydrogen production (Chemical Looping Hydrogen, CLH) or it can be burnt without CO2 emissions (Chemical Looping Combustion, CLC).

Absorption heat pumping devices (AHPDs, comprising absorption heat pumps and chillers) are devices that use thermal energy instead of electricity to generate heating and cooling, thereby facilitating the use of waste heat and renewable energy sources such as solar or geothermal energy. Despite this benefit, widespread use of AHPDs is still limited. One reason for this is partly unsatisfactory control performance under varying operating conditions, which can result in poor modulation and part load capability. A promising approach to tackle this issue is using dynamic, model-based control strategies, whose effectiveness, however, strongly depend on the model being used. This paper therefore focuses on the derivation of a viable dynamic model to be used for such model-based control strategies for AHPDs such as state feedback or model-predictive control. The derived model is experimentally validated, showing good modeling accuracy. Its modeling accuracy is also compared to alternative model versions, that contain other heat transfer correlations, as a benchmark. Although the derived model is mathematically simple, it does have the structure of a nonlinear differential–algebraic system of equations. To obtain an even simpler model structure, linearization at an operating point is discussed to derive a model in linear state space representation. The experimental validation shows that the linear model does have slightly worse steady-state accuracy, but that the dynamic accuracy seems to be almost unaffected by the linearization. The presented new modeling approach is considered suitable to be used as a basis for the design of advanced, model-based control strategies, ultimately aiming to improve the modulation and part load capability of AHPDs.

Aqueous phase reforming (APR) describes the conversion of oxygenated hydrocarbons dissolved in
an aqueous phase to hydrogen and carbon dioxide.

Efficient control of energy systems is an important factor in achieving the CO2-emission goals. District heating (DH) networks are an especially relevant example of such energy systems. State-of-the-art control of small and medium-sized DH networks, however, still mainly relies on simple rule-based control concepts. Handling future challenges such as varying prices and intermittent renewable production is difficult to achieve with such control concepts. Optimization-based energy management systems (EMS) are a promising high-level control approach for the efficient operation of DH networks and complex energy systems in general. An especially interesting challenge arises when DH networks grow, as often the opportunity arises to interconnect them. However, if they operated by different owners, the control task becomes challenging, especially for optimization-based EMS. This is because, in the overall objective function, the cost and revenue for any exchange of energy would cancel out. This thesis presents a solution to this challenge. The main focus of this thesis is on the application of distributed optimization methods for EMS in the context of coupled energy systems, operated by multiple owners, especially interconnected DH networks. The presented methods and ideas are evaluated on a practical application of three DH networks in Austria.  

Annex TS3: Hybrid Energy Networks

The aim of the IEA DHC Annex TS3 „hybrid energy networks" is to promote opportunities and to overcome challenges for district heating and cooling (DHC) networks in an integrated energy system context, focusing on the coupling to the electricity and the gas grid.

K-feldspar was utilized as bed material for fluidized bed combustion of bark, chicken manure, and their mixture. Bed samples were extracted after 4 and 8 h and the samples were analyzed with scanning electron microscopy to study the impact of P-rich chicken manure on the bed material. The results were compared to fixed bed exposures with different orthophosphates to investigate their influence in detail.

The fresh bed material used for this study exhibited an uneven surface with many cavities which facilitated the deposition and retention of the fuel ash. Utilizing pure chicken manure as fuel led to the formation of Ca- and P-rich particles which accumulated in these cavities. At the same time, larger ash particles were formed which consisted of the elements found in chicken manure ash. The co-combustion of bark and chicken manure led to the interaction of the two ash fractions and the formation of a thicker ash layer, which consisted of elements from both fuel ashes, namely Ca, P, Si, K and S. The layer appeared to be partially molten which could be favorable for the deposition of ash particles and thereby the formation of a mixed Ca/K-phosphate. Fixed bed exposures of the K-feldspar particles with Na3PO4 or K3PO4 caused particle agglomeration which means presence of alkali-phosphates should be limited.

The co-combustion of bark with chicken manure showed promising results both regarding a shift from Ca-phosphates to more bioavailable Ca/K-phosphates and an acceleration in ash layer formation. The formation of an ash layer after only 4 h of exposure with the mixture of bark and chicken manure could be advantageous for catalytic activation of the bed material.

Oxygen carrier aided combustion (OCAC) is a novel technology that aims to enhance combustion of heterogenous fuels by replacing the inert bed material with an active oxygen carrier. One of the promising oxygen carriers is natural ilmenite which shows decent oxygen transport capacity and mechanical stability under OCAC operating conditions. However, interactions between ilmenite and woody biomass ash lead to the formation of a calcium-rich ash layer, which affects the ability of the oxygen carrier (OC) to transfer oxygen throughout the boiler and subsequently decreases the combustion efficiency. This paper focuses on the time-dependent morphological and compositional changes in ilmenite bed particles and the consequence effects on the oxygen transport capacity and reactivity of ilmenite. Ilmenite utilized in this study was investigated in a 5 kW bubbling fluidized bed combustion unit, utilizing ash-rich bark pellets as fuel. A negative effect of iron migration on the oxygen transport capacity was observed in ilmenite bed particles after 6 h of operation in the bubbling fluidized bed reactor. The decrease in the oxygen transport capacity of ilmenite was found to correlate with the increased exposure time in the fluidized bed reactor and was caused by the migration and subsequent erosion of Fe from the ilmenite particles. On the other hand, the older bed particles show an increase in reaction rate, presumably due to the catalytic activity of the calcium-enriched outer layer on the bed particle surface.

Introduction and motivation
A key objective for the operation of biomass boilers is to achieve the highest possible efficiency while emitting the lowest possible pollutant emissions. In order to automate this task, CO-lambda optimization methods have been proposed in literature that ensure that the biomass boiler is operated at the lowest excess air ratio at which no relevant pollutant emissions occur, maximizing efficiency as a result. Since this optimal excess air ratio depends on various external factors, such as fuel properties, CO-lambda optimization methods continuously incorporate new measurements of the excess air ratio and the carbon monoxide content of the flue gas and estimate a new optimal excess air ratio during operation.
While achieving promising results in lab-scale tests, none of the CO-lambda optimization methods presented in literature has yet been able to gain practical acceptance. Either they are not robust enough and provide inaccurate estimates of the optimal excess air ratio or they are too slow and do not allow the optimal excess air ratio to be tracked sufficiently quickly. With the goal of providing a method that is fit for practical application, this publication presents a new modular approach for CO-lambda optimization that determines the optimal excess air ratio robustly and quickly, i.e. in real time.

Method
The new approach for CO-lambda optimization approximates the correlation between the excess air ratio and the carbon monoxide content of the flue gas, the CO-lambda characteristic, with a continuous, algebraic, non-linear model function. For this purpose, it uses a recursive-least-squares algorithm to continuously identify the model function’s parameters that lead to the optimal fit with the measured data, which are the excess air ratio and carbon monoxide content of the flue gas. From these model parameters, the optimal excess air ratio is calculated and defined as a desired value for the biomass boiler’s existing controller. This existing controller then ensures, that the biomass boiler is operated with this desired optimal excess air ratio, thus, maximizing efficiency and decreasing pollutant emissions. As a result, this new approach for CO-lambda optimization is entirely modular and can be applied to any biomass boiler with an existing control strategy capable of accurately adjusting the excess air ratio. For the measurement of the carbon monoxide content of the flue gas, a separate sensor has to be used. For this study the commercially available and proven in-situ exhaust gas sensor “KS1D” provided by the company LAMTEC has been used.

Long-term verification
The new approach for CO-lambda optimization was tested and validated at a biomass boiler with a nominal capacity of 2.5 MW that supplies a local heating network and combusts wood chips with a water content ranging from 30 w.t.% to 50 w.t.%. The long-term validation took place over an entire heating period, i.e. 5 months from November to March, during which the biomass boiler was operated alternately with the new approach for CO-lambda optimization and the standard control strategy, which means a constant desired residual oxygen content. In total the new approach for CO-lambda optimization was active for 1155 operating hours while the standard control strategy was active for 1310 operating hours. Compared to the standard control strategy, the new approach for CO-lambda optimization increased the biomass boiler’s efficiency by 3.8%, decreased total dust emissions by 19.5% and reduced carbon monoxide emissions on average (median) by 200 mg/m³. This demonstrates that the new approach for CO-lambda optimization is not only robust enough to run over a long period of time, it also leads to significant improvements in the biomass boiler’s operation. In addition, following these results, this new approach for CO-lambda optimization has also successfully been implemented and demonstrated at another biomass boiler with a nominal capacity of 1 MW where it has already been active for several months. This contribution presents the new approach to CO-lambda optimization in detail and discusses its technological and economic impact.

Many processes in environmental biotechnology are working due to the presence of a mix of microbes, with each group playing a specific role, like being responsible for one step of a multistage conversion process. Even in industrial fermentations which have the purpose of producing biomass of one specific microorganism, an accompanying flora of other microbes is almost always present.

The so-called “layer model” or “interface-based model” is a simplified single particle model, originally developed for shorter computation time during computational fluid dynamics (CFD) simulations. A reactive biomass particle is assumed to consist of successive layers, in which drying, pyrolysis and char conversion occur sequentially. The interfaces between these layers are the reaction fronts. The model has already been validated for drying, pyrolysis and char oxidation. Layer models in the literature have commonly employed surface reactions at the reaction front to describe char conversion. In this work, the suitability of this surface reaction concept is assessed when gasifying biochar. It is shown that a particular layer model, already available, which originally employed surface reactions, was unable to adequately describe the mass loss during gasification of a biochar. In order to overcome this incapability, the model was extended to consider volumetric reactions in the char layer. The influence of intraparticle diffusion was considered through an effectiveness factor. The model is easily adaptable for different gas-solid kinetic rate laws, while still allowing for comparably fast solutions of the model equations. The extended model was validated using theoretical calculations and experimental measurements from literature. It was demonstrated that intraparticle diffusion can significantly slow down the biochar gasification process. A general guideline for when to employ volumetric reactions, rather than surface reactions, and when to consider intraparticle diffusion is provided based on the Thiele modulus as the criterion.

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%.

This work presents the first results of a newly commissioned biomass-to-liquid Fischer-Tropsch (FT) pilot plant. A 1 MWth dualfluidized bed (DFB) steam gasifier, a 55 Nm3/h 4-step gas cleaning plant and a 250 kW slurry bubble column FT synthesis reactor (SBCR) form the full process chain.

Gas-fermentation is the conversion of gaseous feedstocks (e.g. CO2-rich off gases, CO, H2) into
valuable products such as organic acids and alcohols by microorganisms such as clostridia.
By supplying electrical energy (an alternative source of reducing/oxidizing energy), the fermentation
environment can be further optimized, resulting in products with higher purity, a broader product
spectrum and higher cell densities.

Iron production via blast furnace utilizes coal and coke to reduce iron oxides resulting in high greenhouse gas emissions. This important issue for the iron and steel industry may be mitigated by application of biomass-based reducing agents (bioreducer).

Simple biorefinery concepts for the production of sustainable carbon products are investigated in the GreenCarbon Lab at the Wieselburg site of BEST. The heart of the GreenCarbon Lab consists of two pyrolysis units: A lab-scale reactor for testing new input materials as well as conducting detailed parameter studies to reveal the correlation of input material, process conditions and products formed, and a pilot-scale to implement and validate knowledge gained in the laboratory environment to
produce specific GreenCarbon products. Also, product batches in larger quantities (approx. 0,1 – 5 tons) can be manufactured for subsequent application tests – e.g. as part of industrial trials at company partners. In addition, equipment for process and product analysis enables a detailed study of the conversion reactions and the characterization of the products obtained.

Bioenergy is the largest source of renewable energy today. It is versatile and can provide heat, power and transport services, and biomass can also serve as a raw material for the production of chemicals and materials. If done responsibly, and wherever it substitutes for fossil fuels, bioenergy provides substantial GHG emission savings, diversifies energy sources, improves energy supply security and provides income through regional biomass supply chains.

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

Future hybrid energy systems require flexible technologies for compensating the volatile nature of most renewable energies. As such, fixed-bed biomass gasifiers are especially relevant as they allow a flexible production of heat, electricity and in a broader sense bio-based products (e.g. biochar). Thus, flexible fixed-bed biomass gasifiers will continuously become more relevant for a sustainable and highly flexible energy and resource system (bioeconomy).

However, due to their current economic dependency on specific feed in tariffs for the produced electricity, they are almost always operated at nominal load, to maximize the electricity production. Thus, their potential for flexibility has not been revealed up to now. Consequently, the currently applied control strategies are typically designed with the focus on steady-state operation. Any operation differing from nominal load typically requires manual interventions of the plant operators to avoid lower efficiencies or operational difficulties. Thus, currently applied control strategies do not allow a fully-automatic and flexible operation of the gasifiers.

To unleash the full potential of the gasifiers’ flexibility, new and more advanced control strategies able to handle varying operating conditions automatically are required. For this reason, this contribution aims for the development of a model-based control strategy, since it allows to explicitly consider all the correlations between the different process variables, and an efficient adaptation of the control strategy to different plants. The development was carried out on the basis of a representative industrial small-scale fixed-bed biomass gasifier operated as combined heat and power plant (CHP) with a nominal capacity of 300 kW_th and 150 kW_el. In this contribution we present the developed method as well as the practical verification of the model-based controller for the industrial small-scale fixed-bed biomass gasification plant.

The practical verification revealed a significant potential for flexibility increase by the new model-based control strategy in comparison to state-of-the-art control strategies. For example, the new controller performs a step-wise load change from 150 kW_el to 100 kW_el (-33%) within less than 2 min without affecting the gasification performance. The new control leads to a much more homogeneous gasification, in particular during partial load operation, and reduces the fluctuation margin of relevant process parameters to less than 1%. This controlled stabilization and homogenization of the gasification at different operating conditions is also a prerequisite for further future flexibilization measures, e.g. the extension of the feedstock variety (fuel flexibility) or increasing product flexibility.

Due to the modular and model-based design, the new control strategy can also be implemented on other fixed-bed gasifiers of the same type without requiring any structural modifications, by solely adjusting the model parameters appropriately. Furthermore, the new control strategy makes only use of sensors and actuators typically already available in state-of-the-art fixed-bed gasification systems. In conclusion, the model-based control strategy to be presented states a very important contribution towards flexible fixed-bed biomass gasification systems.

Buildings account for 30% of the globally consumed final energy and 19% of the indirect emissions, i.e., from the production of electricity and heat. Air-conditioned office buildings have an especially high energy footprint. Retrofitting buildings with predictive control strategies can reduce their energy demand and increase thermal comfort by considering future weather conditions. One challenge lies in the required infrastructure, i.e., sensors and actuators. Another challenge is about satisfying the comfort requirements of the users, getting their feedback and reacting to it. We propose a predictive control strategy, where an optimization-based energy management system (EMS) controls the thermal zones of such office buildings. The approach uses a mathematical model of the building within an optimization problem to predict and shift thermal demand. The individual thermal zones are modelled using a grey-box approach, where the simultaneous state and parameter estimation is handled by an unscented Kalman filter (UKF). This minimizes the needed effort for deployment of the system, as the parameters are learned automatically from historical measurement data. The objective function ensures the users’ comfort based on a comfort model, penalizes unwanted behaviour such as frequent valve position changes, and minimizes the costs for heating and cooling supply. Since the offices are typically shared by multiple users, the internal comfort model is calibrated based on their feedback. Each feedback is viewed as a measurement from the internal comfort model, and an UKF updates the parameters of the model, thus lowering or increasing the temperature setpoint of the zone controller in a robust manner. As a case study, an office building at the “Innovation District Inffeld” is considered. The proposed predictive control strategy, together with the user feedback, is implemented. A central information and communication technology (ICT) handles all communication with the building automation system. We developed a simple web-based feedback system with a five-point Likert scale for user feedback integration. The presented ideas are evaluated based on both a preliminary simulation study and potential evaluation using the building modelling software IDA ICE, and a real-world implementation. A key requirement was to limit the number of new sensors and actuators, thus focusing on how much can be achieved with a retrofit measure with minimal hardware, but intelligent software. The presentation will give, an overview of the developed methods and first results of the real implementation will be given.

A better understanding of end users’ motives for choosing their energy supply system (heating and domestic hot water, cooling and electricity) can support the establishment of favorable conditions for the energy transition. In this research project, a survey was conducted in the Austrian residential sector to identify end users’ interests and decisions for certain energy supply systems as well as motives for the choice. Based on 169 responses to the questionnaire, a statistical analysis was performed to evaluate the influence of gender aspects on interests and decisions. More than 90% of respondents required robust and efficient energy supply systems, which should have the highest technical standards. The environmental performance was also highly valued, whereas financial aspects, including investment costs were considered less important. 79% of men were mainly involved in the decision-making process, whereas only 59% of women were involved and, in most cases, made the decision together with their partner (52%). Identifying these motives and analyzing investment decisions enables the future integration of social and gender aspects into optimization models for individual households or energy communities.

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

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

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



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



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

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

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

One of the main tasks for operators of medium- and large-scale biomass boilers is the continuous operational monitoring of these plants in order to assess their performance, detect errors and identify possibilities for operational optimization. However, due to the high complexity of this task, errors are frequently detected too late or not at all, which can lead to even more costly secondary errors. In addition, possibilities for optimization remain unused in many existing plants, resulting in unnecessary pollutant emissions and low efficiencies.
To assist operators in performing this task and to achieve a high level of automation, methods for the automated, model-based monitoring of such plants have been focus of recent research activities. In this contribution, we will discuss the numerous possibilities provided by the application of such methods in a practical context. For this purpose, we present selected results from previous activities, demonstrating how methods for model-based monitoring were applied at combustion plants and used to enable automated error detection and support operational optimization.

Exemplary result 1: We developed a soft-sensor which accurately estimates the non-measurable internal state of heat exchangers and implemented it at a large-scale combustion plant with a nominal capacity of 38.2 MW. This soft-sensor uses a dynamic mathematical model of the heat exchanger in combination with measured data to determine a new estimate for the heat exchanger’s internal state every second. Based on this estimate, the soft-sensor accurately detects fouling and determines the non-measurable flue gas mass flow in real time. The estimated flue gas mass flow was used in a model-based control strategy which resulted in significant improvements of the combustion plant’s operational behaviour and load modulation capabilities. These results are discussed in this contribution.

Exemplary result 2: We developed a method for the real-time estimation of non-measurable fuel properties, i.e. chemical composition, bulk density, lower heating value, in biomass boilers. These estimates were subsequently used in a model-based control strategy and enabled the improvement of the biomass boiler’s fuel flexibility. Results of this estimator achieved for different biomass fuels, e.g. poplar wood chips, corncob grits and standard wood pellets, are discussed in this contribution.
On the basis of these selected results, it will be examined which possibilities arise from the use of methods for model-based monitoring in biomass boilers and also how these results can be extended to other technologies such as biomass gasifiers.

Microgrids can integrate variable renewable energy sources into the energy system by controlling flexible assets locally. However, as the energy system is dynamic, an effective microgrid controller must be able to receive feedback from the system in real-time, plan ahead and take into account the active electricity tariff, to maximize the benefits to the operator. These requirements motivate the use of optimization-based control methods, such as Model Predictive Control to optimally dispatch flexible assets in microgrids. However, the major bottleneck to achieve maximum benefits with these methods is their predictive accuracy. This paper addresses this bottleneck by developing a novel multi-step forecasting method for a Model Predictive Control framework. The presented methods are applied to a real test-bed of a renewable energy community in Austria, where its operational costs and CO2 emissions are benchmarked with those of a rule-based control strategy for Flat, Time-of-Use, Demand Charge and variable energy price tariffs. In addition, the impact of forecast errors and electric battery capacity on energy community operational savings are examined. The key results indicate that the proposed controller can outperform a rule-based dispatch strategy by 24.7% in operational costs and by 8.4% in CO2 emissions through optimal operation of flexibilities if it has perfect foresight. However, if the controller is deployed in a realistic environment, where forecasts for electrical load and PV generation are required, the same savings are reduced to 3.3% for cost and 7.3% for CO2, respectively. In such environments, the proposed controller performs best in highly dynamic tariffs such as Time-of-Use and Real-time pricing rates, achieving real cost savings of up to 6.3%. These results show that the profitability of optimization-based control of microgrids is threatened by forecast errors. This motivates future research on control strategies that compensate for forecast errors in real-world operation and more accurate forecasting methods.

Microgrids generate and store energy for self consumption (electricity, heating, cooling, etc.). Decentralized and renewable generation and storage technologies, as well as energy strategies increase efficiency, resilience, grid stability, independency of imports, sustainability, and climate neutrality.

One promising technology in the field of residue valorization is the pyrolytic conversion of biomass to biochar. There are a lot of proven technologies for this task, with many of them being quite distinctive. Biochar has a lot of valuable properties and it shows potential to be applicated in many different fields of industry as a green carbon resource. Thus, as the demand for its production rises, more and more people from different fields share interest in the same technologies and the demand for guidance in form of readily available information increases. Two prominent technologies rather similar in appearance are rotary kilns and screw reactors. Both technologies consist of a long, hollow cylinder and both technologies use some form of longitudinal rotation as a means to transport feedstock. In this review, both technologies are described and their biggest differences and similarities are discussed, all under the aspect of biochar production. In total, 21 unique rotary kilns and 58 unique auger reactors were identified. The paper addresses process specific aspects, like heat supply or residence time, but it also gives an overview on current research and general aspects like scale-up considerations. Differences between both technologies were found in all of these aspects, with some of the most pronounced being the bigger maximum capacities and the greater residence time distributions in rotary kiln pyrolysis. Both technologies are viable candidates for producing biochar on a commercial level, however, literature comparing the influence of the reactor type on biochar properties was very scarce. As a future outlook it is recommended to produce data that can be compared on a quantitative level, so a more accurate assessment of each technologies up- and downsides can be made.

Steam gasification in a dual fluidized bed (DFB) reactor has already been developed in the power sector from lab- to commercial-scale for woody biomass as feedstock. A trend towards utilizing feedstock of lower quality, such as low-grade biomass, biogenic residues or waste drives the development of the technology in terms of reactor design, gas cleaning and optimizing operation parameters. Additionally, the need for production of sustainable end products more valuable than electricity and heat leads to the embedding of DFB gasification into complete process chains.

District heating (DH) networks have the potential for intelligent integration and combination of renewable energy sources, waste heat, thermal energy storage, heat consumers, and coupling with
other sectors. For growing networks in close geographical proximity, often the possibility arises to couple them using bidirectional heat exchangers, possibly unlocking synergies and reducing costs for the consumers. Each DH network may consist of producers, consumers and thermal energy storage (TES) devices. Often, each of the coupled DH networks will be already controlled via low-level controllers. Hence, a high-level control approach is needed, that coordinates the heat exchange between the
networks and takes renewable energy sources and the TES capacities in each network into account. These supervisory controllers are generally referred to as energy management systems (EMS).