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Scientific questions
- How can a non-stationary heat offering in the commercial vehicle be used to reduce fuel consumption?
- Which potentials offer route and environmental information among with predicted speed and load trajectories to increase the efficiency of a ORC-System?
Methods
- Desktop bound holistic simulation model for a heavy duty truck incl. an ORC System
- Prediction of massflows, temperatures and mixture quality (AFR) of exhaust gas
Due to the Renewable Energy Act, in Germany it is planned to increase the amount of renewable energy carriers up to 60%. One of the main problems is the fluctuating supply of wind and solar energy. Here biogas plants provide a solution, because a demand-driven supply is possible. Before running such a plant, it is necessary to simulate and optimize the process. This paper provides a new model of a biogas plant, which is as accurate as the standard ADM1 model. The advantage compared to ADM1 is that it is based on only four parameters compared to 28. Applying this model, an optimization was installed, which allows a demand-driven supply by biogas plants. Finally the results are confirmed by several experiments and measurements with a real test plant.
Heavy-duty trucks are one of the main contributors to greenhouse gas emissions in German traffic. Drivetrain electrification is an option to reduce tailpipe emissions by increasing energy conversion efficiency. To evaluate the vehicle’s environmental impacts, it is necessary to consider the entire life cycle. In addition to the daily use, it is also necessary to include the impact of production and disposal. This study presents the comparative life cycle analysis of a parallel hybrid and a conventional heavy-duty truck in long-haul operation. Assuming a uniform vehicle glider, only the differing parts of both drivetrains are taken into account to calculate the environmental burdens of the production. The use phase is modeled by a backward simulation in MATLAB/Simulink considering a characteristic driving cycle. A break-even analysis is conducted to show at what mileage the larger CO2eq emissions due to the production of the electric drivetrain are compensated. The effect of parameter variation on the break-even mileage is investigated by a sensitivity analysis. The results of this analysis show the difference in CO2eq/t km is negative, indicating that the hybrid vehicle releases 4.34 g CO2eq/t km over a lifetime fewer emissions compared to the diesel truck. The break-even analysis also emphasizes the advantages of the electrified drivetrain, compensating the larger emissions generated during production after already a distance of 15,800 km (approx. 1.5 months of operation time). The intersection coordinates, distance, and CO2eq, strongly depend on fuel, emissions for battery production and the driving profile, which lead to nearly all parameter variations showing an increase in break-even distance.
Die Energiewirtschaft befindet sich in einem starken Wandel, der v. a. durch die Energiewende und Digitalisierung Druck auf sämtliche Marktteilnehmer ausübt. Das klassische Geschäftsmodell des Energieversorgungsunternehmens verändert sich dabei grundlegend. Der kontinuierlich ansteigende Einsatz dezentraler und volatiler Erzeugungsanlagen macht die Identifikation von Flexibilitätspotenzialen notwendig, um weiterhin eine hohe Versorgungssicherheit zu gewährleisten. Dieser Schritt ist nur mit einem hohen Digitalisierungsgrad möglich. Eine funktionale Plattform mit Microservices, die zu Geschäftsprozessen verbunden werden können, wird als Möglichkeit zur Aktivierung der Flexibilität und Digitalisierung der Energieversorgungsunternehmen im Folgenden vorgestellt.
Characterizing volcanic ash elements from the 2015 eruptions of bromo and raung volcanoes, Indonesia
(2020)
The volcanic eruptions of Mt. Bromo and Mt. Raung in East Java, Indonesia, in 2015 perturbed volcanic materials and affected surface-layer air quality at surrounding locations. During the episodes, the volcanic ash from the eruptions influenced visibility, traffic accidents, flight schedules, and human health. In this research, the volcanic ash particles were collected and characterized by relying on the detail of physical observation. We performed an assessment of the volcanic ash elements to characterize the volcanic ash using two different methods which are aqua regia extracts followed by MP-AES and XRF laboratory test of bulk samples. The analysis results showed that the volcanic ash was mixed of many materials, such as Al, Si, P, K, Ca, Ti, V, Cr, Mn, Fe, Ni, and others. Fe, Si, Ca, and Al were found as the major elements, while the others were the trace elements Ba, Cr, Cu, Mn, P, Mn, Ni, Zn, Sb, Sr, and V with the minor concentrations. XRF analyses showed that Fe dominated the elements of the volcanic ash. The XRF analysis showed that Fe was at 35.40% in Bromo and 43.00% in Raung of the detected elements in bulk material. The results of aqua regia extracts analyzed by MP-AES were 1.80% and 1.70% of Fe element for Bromo and Raung volcanoes, respectively.
The fundamental modeling of energy systems through individual unit commitment decisions is crucial for energy system planning. However, current large-scale models are not capable of including uncertainties or even risk-averse behavior arising from forecasting errors of variable renewable energies. However, risks associated with uncertain forecasting errors have become increasingly relevant within the process of decarbonization. The intraday market serves to compensate for these forecasting errors. Thus, the uncertainty of forecasting errors results in uncertain intraday prices and quantities. Therefore, this paper proposes a two-stage risk-constrained stochastic optimization approach to fundamentally model unit commitment decisions facing an uncertain intraday market. By the nesting of Lagrangian relaxation and an extended Benders decomposition, this model can be applied to large-scale, e.g., pan-European, power systems. The approach is applied to scenarios for 2023—considering a full nuclear phase-out in Germany—and 2035—considering a full coal phase-out in Germany. First, the influence of the risk factors is evaluated. Furthermore, an evaluation of the market prices shows an increase in price levels as well as an increasing day-ahead-intraday spread in 2023 and in 2035. Finally, it is shown that intraday cross-border trading has a significant influence on trading volumes and prices and ensures a more efficient allocation of resources.