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Forecasting and Optimization Approaches Utilized for Simulating a Hybrid District Heating System
No full textThe historically grown centralized energy system is undergoing massive changes due to the transformation from centralized energy production with large assets (e.g. fossil-thermal power plants) towards a sustainable, clean and decentralized energy system. This transformation is based on the inclusion of renewable energy sources (RESs) (e.g., wind and solar) into the classical systems. However, as the energy production stemming from RESs is extremely volatile and thus challenging to predict, new approaches have to be found in order to guarantee a successful integration of RESs into the existing infrastructure.
In the Austrian state of Burgenland approximately 1,000 MW of wind capacity is available. As already mentioned above, the high volatility of wind energy together with forecast uncertainties hinders the optimal integration of this RES into the existing energy system. Furthermore, the successful deployment of wind turbines was based on an attractive but timely limited subsidy scheme with a fixed feed-in tariff. As these subsidies now come to an end for more and more wind turbines and future support systems will rely on market premiums and tendering models, new approaches and business models have to be devised in order to sustain the rapid transformation of the classical energy systems.
In the research project HDH Demo in close cooperation with the city of Neusiedl am See, Burgenland, Austria, the aim is to integrate wind energy into the existing district heating grid of the city. This is realized by utilizing power-to-heat technologies, e.g., heat pumps. However, an economically feasible and successful integration is based on accurate forecasts for both, wind production and district heating demand as well as the actual energy prices.
Therefore, this work evaluates the applied data-driven forecasting methods. In particular, ensemble approaches that combine autoregressive models with artificial intelligent techniques are used to exploit the strengths of different methods (e.g. stability, flexibility). To compare the model performance, an overview on the accuracy and efficiency of the ensembles by using appropriate score metrics (e.g. RMSE, MAPE, R²) is given. Furthermore, a mixed integer linear optimization model is presented for computing optimized schedules for the different components (e.g., heat pumps, energy storage units, biomass boiler) of the district heating grid. Together, these two approaches, forecasting and optimization, are used to investigate and evaluate different business models, which help to ensure the future market integration of wind production.Forschung Burgenlan
Dual Fuel Reaction Mechanism 2.0 including NOx Formation and Laminar Flame Speed Calculations Using Methane/Propane/n-Heptane Fuel Blends
No full textThis study presents the further development of the TU Wien dual fuel mechanism, which was optimized for simulating ignition and combustion in a rapid compression expansion machine (RCEM) in dual fuel mode using diesel and natural gas at pressures higher than 60 bar at the start of injection. The mechanism is based on the Complete San Diego mechanism with n-heptane extension and was attuned to the RCEM measurements to achieve high agreement between experiments and simulation. This resulted in a specific application area. To obtain a mechanism for a wider parameter range, the Arrhenius parameter changes performed were analyzed and updated. Furthermore, the San Diego nitrogen sub-mechanism was added to consider NOx formation. The ignition delay time-reducing effect of propane addition to methane was closely examined and improved. To investigate the propagation of the flame front, the laminar flame speed of methane–air mixtures was simulated and compared with measured values from literature. Deviations at stoichiometric and fuel-rich conditions were found and by further mechanism optimization reduced significantly. To be able to justify the parameter changes performed, the resulting reaction rate coefficients were compared with data from the National Institute of Standards and Technology chemical kinetics database
(Social) Media and their Role in Public Discourse
No full textThe role of the mass media in political communication and more specifically agenda
setting has changed significantly, not only since Donald Trump’s opposition to traditional mass media and preference for social media. The following article examines the
role of the media in the formation of public opinion in liberal democracies. In particular, the paper explores a shift in the power of interpretation in the agenda setting
process, for example, when journalists are questioned in their gatekeeper role. From
Gatekeeper to Gatewatcher? This perceived threat to journalism is receiving attention
in many places. Social media are the main drivers of this role change. Yet how are they
changing public discourse and the role of mass media? The paper discusses these two
core questions as well as the opportunities and risks for political discourse that the
increasing use of social media entails.Wirtschaf
Die größte Ressource von Unternehmen
No full textGute soziale Beziehungen auf allen Ebenen eines Betriebes sind auch eine gute Basis für dessen Produktivität. Das ist aufgrund der aktuellen Veränderungen noch wichtiger geworden.Gesundhei
An Integrated Framework for Building’s Energy Management based on Deep Learning
No full textScience.Research.Pannonia. 22Forecasting the building energy consumption constitutes a significant factor for a wide variety
of applications including planning, management and optimization. Nowadays, research is focused towards
the development of more efficient and sustainable energy management systems which focus on minimising
energy waste. These systems are based on intelligent models, which provide accurate predictions of future
energy demand/load, both at aggregate and individual site level. In this work, we present a holistic integrated
solution for the buildings’ energy management systems using deep learning methods. The proposed solution
is based on efficient deep-learning forecasting models for short-term local weather parameters and energy load
consumption. The developed forecasting models are integrated into the smart energy management system of
the building for taking the proper decisions to ensure efficient utilization of energy resources.Energie-Umweltmanagemen
Die Dominanz des ökonomischen Systems verhindert Solidarität - Finanzierungsparadigmen als Hürde für Kooperation
No full textSoziale
Österreichische Bewegungsempfehlungen für Frauen während der Schwangerschaft und danach, für Kinder im Kindergartenalter und für Kinder und Jugendliche
No full textLife Cycle Assessment of Biogas Production from Unused Grassland Biomass Pretreated by Steam Explosion Using a System Expansion Method
No full textReforestation is a threat to permanent grasslands in many alpine regions. Using these areas to produce biogas energy may help to preserve these important landscapes and save fossil fuels by adding a renewable local heat and electricity source. This case study compares (a) a status quo (SQ) reference scenario with heating oil, wood-chips, and grid electricity as municipal energy sources, and (b) a hypothetical local biogas (LB) scenario (to also be used as a municipal energy source) based on a 500-kWel biogas plant with steam explosion pretreatment. Here, hay from previously unused grassland is the main biogas substrate, whereas, in the reference SQ scenario, these grasslands remain unused. Life cycle assessment (LCA) results for LB and SQ scenarios are significantly different at p < 0.05 in all six impact categories. In three categories, the LB scenario has lower impacts than the SQ scenario, including climate change (0.367 CO2-eq kWhel-1 versus 0.501 CO2-eq kWhel-1). Dominant contributions to climate change in the SQ scenario are from the extant municipal energy sources that the LB biogas plant would replace; in the LB scenario, important contributions include unburned methane from the biogas plant, as well as CO2 emissions from hay production machines. In summary, important environmental impacts can be reduced and alpine grasslands can be preserved by biogas production from that grass. The advantages of integrating a local biogas plant in municipal energy and waste systems depend strongly on the extant municipal energy system characteristics.Energie-Umweltmanagemen
