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

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

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

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

The reduction of greenhouse gas emission is an important issue for steel industry. One possibility is to use biomass-based reducing agents, also called bioreducers, to replace a least partly the fossil reducer agents. To produce bioreducer we treated woody biomass in a lab-scale muffle furnace, we performed grinding experiments with a ball mill, we analyzed the particle size distribution with laser diffraction and we used a rotating device, the revolution powder analyzer, for flow behavior investigations. Our preliminary results show that treatment temperatures >250 oC bring adequate increased calorific value and improved grindability. For a certain treatment temperature the particle size distribution and as well the flow behavior shows similarities to lignite.

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

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

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

The microalga Acutodesmus obliquus was investigated as a feedstock in semi-continuously fed anaerobic digestion trials, where A. obliquus was co-digested with pig slurry and maize silage. Maize silage was substituted by both 10% and 20% untreated, and 20% ultrasonicated microalgae biomass on a VS (volatile solids) basis. The substitution of maize silage with 20% of either ultrasonicated and untreated microalgae led to significantly lower biogas yields, i.e., 560 dm³ kg⁻¹ VS_corr in the reference compared to 516 and 509 dm³ kg^-1VS_corr for untreated and ultrasonicated microalgae substitution. Further, the viscosities in the different reactors were measured at an OLR of 3.5 g VS dm^-3 d^-1. However, all treatments with microalgae resulted in significantly lower viscosities. While the mean viscosity reached 0.503 Pa s in the reference reactor, mean viscosities were 53% lower in reactors where maize was substituted by 20% microalgae, i.e. 0.239 Pa s, at a constant rotation speed of 30 rpm. Reactors where maize was substituted by 20% ultrasonicated microalgae had a 32% lower viscosity, for 10% microalgae substitution a decrease of 8% was measured. Decreased viscosities have beneficial effect on the bioprocess and the economy in biogas plants. Nonetheless, with regard to other parameters, no positive effect on biogas yields by partial substitution with microalgae biomass was found. The application of microalgae may be an interesting option in anaerobic digestion when fibrous or lignocellulosic substances lead to high viscosities of the digested slurries. High production costs remain the bottleneck for making microalgae an interesting feedstock.

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

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

The efficient and flexible conversion of solid biomass into energetic products will be an essential part of a future renewable, independent and reliable energy providing system. The main objective of the project Bio-CCHP is the development of a novel tri-generation system, including biomass gasification, gas cleaning, a Solid Oxide Fuel Cell (SOFC) and a cooling machine with the aim to produce electricity, heat and cold (CCHP), maximizing the efficiency and flexibility of the system. However, the employment of biomass derived product gas as fuel gas for SOFC is facing new challenges for gas quality assurance. For the evaluation of required dry high temperature gas cleaning processes the applied methods of gas characterization have to be accurate and reliable. Therefore, a comprehensive evaluation of analytical methods for the detection of SOFC harmful compounds is conducted within the ongoing project. First results of online and offline sampling and analysis methods employed at air- and steam-operated gasifiers are shown in this paper.

Although the number of studies investigating the contribution of anaerobic digestion facilities to greenhouse gas (GHG) emissions has increased during the last decade, reliable data with respect to gaseous process losses from these management practices, particularly at commercial scale, is scarce (Liebetrau et al., 2013, Reinelt et al., 2017, Hrad et al., 2015). The dynamic and fugitive nature of methane emissions, changing operating conditions, and different as well as not standardised measurement approaches compromise the precise quantification of the overall emissions from full-scale biogas plants. However, reliable and verifiable emission data from biogas or biomethane facilities are required in order to optimise and improve the plant-specific process efficiency as well as future technology developments. In addition, precise and comprehensive measurement data from full-scale waste treatment facilities are needed for more accurate emission factors (EFs) estimates, which are required for annual reporting according to the Intergovernmental Panel on Climate Change (IPCC) guidelines (IPCC, 2006).
Within the European project “EvEmBi - Evaluation and reduction of different biogas plant concepts” (2018-2021, funded within the 11th ERA-NET bioenergy call) 15 partners from 5 European countries evaluate the existing technologies at biogas plants regarding their methane EFs and develop emission reduction strategies, respectively. The focus of the Austrian research group within this project is the evaluation of Austrian bio-waste plants.
In a first step, emissions from single sources as well as overall plant emissions are quantified. For the latter, the Austrian team uses an open-path technology (Open-Path Tunable-Diode-Laser-Spectroscopy) together with meteorological data (ultra-sonic anemometer) and inverse dispersion modelling (Backward Lagrangian Model). In order to determine comparable EFs, the applied methodologies are based on a measurement guideline developed in the previous project “MetHarmo – European harmonization of method to quantify methane emissions from biogas plants” (funded within the 9th ERA-NET bioenergy call). In addition, the determined EFs of the individual plant concepts are transferred to EFs of the entire plant inventory of the particular countries. For that, a model for EF quantification is used which is based on statistical information on the emissions from different plant components as well as on the distribution of certain technologies present in the participating countries. Furthermore, for the particular biogas plants emission reduction strategies are developed, implemented and verified.
In this presentation, the harmonised approach, first emission results from the Austrian measurement campaigns as well as emission reduction strategies are presented.