600 Technik, Medizin, angewandte Wissenschaften
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Potential analyses identify possible locations for renewable energy installations, such as wind turbines and photovoltaic arrays. The results of previous potential studies for Germany, however, are not consistent due to different assumptions, methods, and datasets being used. For example, different land-use datasets are applied in the literature to identify suitable areas for technologies requiring open land. For the first time, commonly used datasets are compared regarding the area and position of identified features to analyze their impact on potential analyses. It is shown that the use of Corine Land Cover is not recommended as it leads to potential area overestimation in a typical wind potential analyses by a factor of 4.7 and 5.2 in comparison to Basis-DLM and Open Street Map, respectively. Furthermore, we develop scenarios for onshore wind, offshore wind, and open-field photovoltaic potential estimations based on land-eligibility analyses using the land-use datasets that were proven to be best by our pre-analysis. Moreover, we calculate the rooftop photovoltaic potential using 3D building data nationwide for the first time. The potentials have a high sensitivity towards exclusion conditions, which are also currently discussed in public. For example, if restrictive exclusions are chosen for the onshore wind analysis the necessary potential for climate neutrality cannot be met. The potential capacities and possible locations are published for all administrative levels in Germany in the freely accessible database (Tool for Renewable Energy Potentials—Database), for example, to be incorporated into energy system models.
New risk geographies are emerging with war and conflict resurfacing, including nuclear threats. This poses challenges to civil protection for conducting risk-informed preparedness planning. A spatial assessment of Germany and Europe is conducted using a geographic information system. Buffer circles of nuclear explosion effects and fallout buffers show potentially exposed areas around major cities. Different scenarios indicate shrinking areas safe from exposure. However, even in a densely populated country, rural areas and smaller cities can be identified that could provide sites for evacuation shelters. Changing wind directions poses a challenge for civil protection planning because fallout risk covers most German territory even when few cities are attacked. However, wind speeds and topography can help identify suitable shelter areas. More knowledge about the temporal development of a nuclear explosion and its specific forms of harm can also help to improve risk knowledge and planning. While nuclear warfare at first seems to render useless any option for safe areas and survival, the spatial risk assessment shows that exposure does not occur at all places at all times. Being safe from harm will be difficult in such a worst-case scenario, but avoiding large city perimeters and being informed can also help reduce risk.
Remaining-useful-life (RUL) prediction of Li-ion batteries is used to provide an early indication of the expected lifetime of the battery, thereby reducing the risk of failure and increasing safety. In this paper, a detailed method is presented to make long-term predictions for the RUL based on a combination of gated recurrent unit neural network (GRU NN) and soft-sensing method. Firstly, an indirect health indicator (HI) was extracted from the charging processes using a soft-sensing method that can accurately describe power degradation instead of capacity. Then, a GRU NN with a sliding window was applied to learn the long-term performance development. The method also uses a dropout and early stopping method to prevent overfitting. To build the models and validate the effectiveness of the proposed method, a real-world NASA battery data set with various battery measurements was used. The results show that the method can produce a long-term and accurate RUL prediction at each position of the degradation progression based on several historical battery data sets.
Das Ziel der vorliegenden Arbeit besteht darin, die Frage zu beantworten wie Yosys Verilog einliest und daraus RTLIL generiert. Mit der Beantwortung dieser Frage, soll die Datenstruktur RTLIL und die Verknüpfung zu einem Verilog Design besser verstanden werden. Dafür wurde das Frontend von Yosys untersucht und die Datenstruktur RTLIL näher eleuchtet. Als Ergebnis konnte festgehalten werden, dass die AstNode Datenstruktur eine wesentliche Rolle bei der Konvertierung von Verilog zu RTLIL spielt, und mit deren Hilfe beim Einlesen ein abstrakter Syntaxbaum gebildet wird. Allein der Typ des Knotens beeinflusst, wie der RTLIL Generator damit umgeht. Weiter ist die Generierung von RTLIL::Cell Objekten als erster Schritt zur Synthese zu verstehen, da sie durch Technologie Mapping reale Komponenten abbilden können
Effects on the combustion properties of wheat straw after different thermobiological pretreatments
(2022)
Wheat straw could be used for pellet production and therefore as solid fuel. However, it presents challenges due to its inferior combustion properties such as high ash content, low gross calorific value (GCV), and low ash melting temperature.
To evaluate its combustion properties and based on recent work that improved methane production, wheat straw was subjected to thermobiological pretreatments. Nine pretreated samples based on wheat straw and nine pretreated samples based on compost-wheat straw mixture were produced. In addition, due to the ability to remove minerals and decrease the ash content, a washing process with water as a solvent was used. Ash content, net calorific value (NCV) and ash melting temperatures were evaluated.
For the pretreated wheat straw (SW) samples, a 5,8% reduction in ash content was obtained due to the pretreatments when compared to untreated wheat straw. A 55% decrease in ash content was obtained when comparing the same materials before and after the washing process. No statistically significant changes in GCV were found. As for the ash melting temperatures, due to the incubation pretreatment, an average increase in the shrinkage starting temperature (SST) of 4,4% was obtained for anaerobic conditions and a decrease of 2,5% for aerobic conditions, compared to the same material without heat treatment. In addition, an increase in all ash melting temperatures was observed because of the washing process. It was possible to obtain a pellet complying with standard ISO 17225-6 that can be used in medium or large burners and significantly reduces the effort during combustion.
For samples pretreated with a homogeneous compost-wheat straw (SKW) mixture, an average ash content decrease of 27% was obtained after using autoclave pretreatment at 140°C, compared to the same material without thermal pretreatment. The biggest decrease was due to the washing process, reducing the ash content on average by 43% when comparing the same materials before and after washing. GCV were 13% lower than samples pretreated with wheat straw, due to the low calorific value and high ash content of the compost. During ash melting temperature tests, an average 60% increase in SST was observed compared to pretreated SW ashes due to the high melting temperature of compost. Results are considered satisfactory since pellets based on this mixture would not cause ash sintering or slagging. However, counter effects were observed as the addition of compost increased the ash content and decreased the GCV, not complying with ISO 17225-6 for non-woody pellets. To achieve a pellet based on a compost-wheat straw mixture that complies with the standards, it is recommended for future research to control the percentage of compost added to the mixture.
In this study the link between renewable energies and employment in Senegal is analyzed.
The Sustainable Livelihood Approach is used to understand the investigated situation in a holistic view. To successfully implement renewable energies in Senegal and to have a significant impact on the employment market, the governmental framework and the technical education has to improve, to match the needs of the labor market.
Rural communities do not have all the assets to lift themselves out of poverty and disadvantages by the usage of renewable energy. Solar irrigation, off-grid systems and solar devices impact the level of education and the labor force in rural areas in Senegal.
Moreover, access to a reliable energy source improves people’s livelihood in terms
of health, education, income and employment.
The resulting employment effect of adding 20 MW with the solar power plant Senergy 2 can be estimated with 28.686 created jobs (0,54 % of total employment).
Upcoming power projects offer employment opportunities for graduates of the master study renewable energies. Furthermore, the demand of specialized engineers and
technicians in the distribution and project planning sector will rise.
AbstractThe Ganges-Brahmaputra (GB) delta is one of the most disaster-prone areas in the world due to a combination of high population density and exposure to tropical cyclones, floods, salinity intrusion and other hazards. Due to the complexity of natural deltaic processes and human influence on these processes, structural solutions like embankments are inadequate on their own for effective hazard mitigation. This article examines nature-based solutions (NbSs) as a complementary or alternative approach to managing hazards in the GB delta. We investigate the potential of NbS as a complementary and sustainable method for mitigating the impacts of coastal disaster risks, mainly cyclones and flooding. Using the emerging framework of NbS principles, we evaluate three existing approaches: tidal river management, mangrove afforestation, and oyster reef cultivation, all of which are actively being used to help reduce the impacts of coastal hazards. We also identify major challenges (socioeconomic, biophysical, governance and policy) that need to be overcome to allow broader application of the existing approaches by incorporating the NbS principles. In addition to addressing GB delta-specific challenges, our findings provide more widely applicable insights into the challenges of implementing NbS in deltaic environments globally.
Im Rahmen des Technologiescreenings sind zunächst relevante Technologien, die Einfluss auf das Energienachfrageverhalten für Haushalte besitzen, identifiziert worden. Dabei ist ausschließlich eine technologische Betrachtung erfolgt, das individuelle Nutzerverhalten von Haushaltsbewohnern wurde dabei nicht betrachtet. Die Einordnung der Technologien sind in Standard Energietechnologien: Erzeuger, Umwandler, Verbraucher und Speicher kategorisiert. Zudem zeigt die in die Kategorien Messsysteme, Gebäudeautomation und Energiemanagementsysteme. Dabei handelt es sich um, digitale Technologien mit Aspekten und Anwendungen von Energietransparenz und -management. Zeitraum des kontinuierlichen Technologie-Screenings war von 2017-2020.
Das interdisziplinäre Forschungsprojekt “Smarte Technologien für Unternehmen” untersuchte im Zeitraum von Juli 2017 bis Dezember 2020 Anwendungs- und Akzeptanzprobleme zum Einsatz smarter Technologien in KMU und entwickelte darauf aufbauend Lösungsansätze zur Steigerung der Energieeffizienz sowie zum Energie- und Lastmanagement. Dazu wurden smarte Technologien zunächst im Zuge eines Screenings identifiziert, kategorisiert und bewertet. In den qualitativen und quantitativen Nutzeranalysen wurden Unternehmer*innen in den Fokus der Analyse gestellt, um den Wissensstand sowie Chancen und Barrieren zum Einsatz smarter Technologien in KMU darzulegen. Mit der Durchführung transdisziplinärer Anwendungstests wurde ein zentraler Lösungsansatz entwickelt: Die Effizienzanalyse von KMU mittels mobiler Messtechnik und Visualisierungstools als potenzielle Strategie zur Reduktion von Energieverbräuchen.
Die Ergebnisse dieses anwendungsorientierten Forschungsprojektes zeigen die Anwendungs- und Akzeptanzprobleme zum Einsatz smarter Technologien in KMU auf und geben Handlungsoptionen zur Steigerung der Energieeffizienz mit Hilfe ausgewählter smarter Produkte und Tools.