50 research outputs found
Thermal Stability of Hexamethyldisiloxane (MM) for High-Temperature Organic Rankine Cycle (ORC)
The design of efficient Organic Rankine Cycle (ORC) units for the usage of industrial waste heat at high temperatures requires direct contact evaporators without intermediate thermal oil circuits. Therefore, the thermal stability of high-temperature working fluids gains importance. In this study, the thermal degradation of hexamethyldisiloxane (MM) is investigated in an electrically heated tube. Qualitative results concerning remarks on degradation products as well as quantitative results like the annual degradation rate are presented. It is shown that MM is stable up to a temperature of 300 °C with annual degradation rates of less than 3.5%. Furthermore, the break of a silicon–carbon bond can be a main chemical reaction that influences the thermal degradation. Finally, it is discussed how the results may impact the future design of ORC units
Influence of usage and model inaccuracies on the performance of smart hot water heaters: lessons learned from a demand response field test
Domestic hot water heaters are considered to be easily integrated as flexible loads for demand response. While literature grows on reproducible simulation and lab tests, real-world implementation in field tests considering state estimation and demand prediction-based model predictive control approaches is rare. This work reports the findings of a field test with 16 autonomous smart domestic hot water heaters. The heaters were equipped with a retrofittable sensor/actuator setup and a real-time price-driven model predictive control unit, which covers state estimation, demand prediction, and optimization of switching times. With the introduction of generic performance indicators (specific costs and thermal efficiency), the results achieved in the field are compared by simulations to standard control modes (instantaneous heating, hysteresis, night-only switching). To evaluate how model predictive control performance depends on the user demand prediction and state estimation accuracy, simulations assuming perfect predictions and state estimations are conducted based on the data measured in the field. Results prove the feasible benefit of RTP-based model predictive control in the field compared to a hysteresis-based standard control regarding cost reduction and efficiency increase but show a strong dependency on the degree of utilization
Comparison of Cooling System Designs for an Exhaust Heat Recovery System Using an Organic Rankine Cycle on a Heavy Duty Truck
A complex simulation model of a heavy duty truck, including an Organic Rankine Cycle (ORC) based waste heat recovery system and a vehicle cooling system, was applied to determine the system fuel economy potential in a typical drive cycle. Measures to increase the system performance were investigated and a comparison between two different cooling system designs was derived. The base design, which was realized on a Mercedes-Benz Actros vehicle revealed a fuel efficiency benefit of 2.6%, while a more complicated design would generate 3.1%. Furthermore, fully transient simulation results were performed and are compared to steady state simulation results. It is shown that steady state simulation can produce comparable results if averaged road data are used as boundary conditions
Alleviating the Curse of Dimensionality in Minkowski Sum Approximations of Storage Flexibility
Many real-world applications require the joint optimization of a large number
of flexible devices over time. The flexibility of, e.g., multiple batteries,
thermostatically controlled loads, or electric vehicles can be used to support
grid operation and to reduce operation costs. Using piecewise constant power
values, the flexibility of each device over time periods can be described
as a polytopic subset in power space. The aggregated flexibility is given by
the Minkowski sum of these polytopes. As the computation of Minkowski sums is
in general demanding, several approximations have been proposed in the
literature. Yet, their application potential is often objective-dependent and
limited by the curse of dimensionality. We show that up to vertices of
each polytope can be computed efficiently and that the convex hull of their
sums provides a computationally efficient inner approximation of the Minkowski
sum. Via an extensive simulation study, we illustrate that our approach
outperforms ten state-of-the-art inner approximations in terms of computational
complexity and accuracy for different objectives. Moreover, we propose an
efficient disaggregation method applicable to any vertex-based approximation.
The proposed methods provide an efficient means to aggregate and to
disaggregate energy storages in quarter-hourly periods over an entire day with
reasonable accuracy for aggregated cost and for peak power optimization.Comment: 11 pages, 5 figure
Optimal power tracking for autonomous demand side management of electric vehicles
Increasing electric vehicle penetration leads to undesirable peaks in power if no proper coordination in charging is implemented. We tested the feasibility of electric vehicles acting as flexible demands responding to power signals to minimize the system peaks. The proposed hierarchical autonomous demand side management algorithm is formulated as an optimal power tracking problem. The distribution grid operator determines a power signal for filling the valleys in the non-electric vehicle load profile using the electric vehicle demand flexibility and sends it to all electric vehicle controllers. After receiving the control signal, each electric vehicle controller re-scales it to the expected individual electric vehicle energy demand and determines the optimal charging schedule to track the re-scaled signal. No information concerning the electric vehicles are reported back to the utility, hence the approach can be implemented using unidirectional communication with reduced infrastructural requirements. The achieved results show that the optimal power tracking approach has the potential to eliminate additional peak demands induced by electric vehicle charging and performs comparably to its central implementation. The reduced complexity and computational overhead permits also convenient deployment in practice.publishedVersio
Experimental analysis of the humidification of air in bubble columns for thermal water treatment systems
The humidification-dehumidification process (HDH) for desalination is a promising technology to address water scarcity issues in rural regions. However, a low humidifier efficiency is a weakness of the process. Bubble column humidifiers (BCH) are promising for HDH, as they provide enhanced heat and mass transfer and have low maintenance requirements. Previous studies of HDH-systems with BCHs draw different conclusions regarding the impact of superficial air velocity and liquid height on the humidification. Furthermore, the impact of flow characteristics has never been investigated systematically at all. In this study, an optimized BCH test setup that allows for optical analysis of the humidifier is used and evaluated. Our test setup is validated, since the influence of water temperature on the humidification, which is exponential, is reproduced. Measurements with seawater show that the normalised system productivity is increased by about 56 % with an increase in superficial air velocity from 0.5 to 5 cm/s. Furthermore, the system productivity is increased by around 29 % with an increase in liquid height from 60 to 378 mm. While the impact of superficial air velocity can be traced back to temperature changes at the humidifier and dehumidifier outlets, the impact of liquid height is shown to be caused by a smaller heat loss surface in the humidifier with an increase in liquid height. For the impact of sieve plate orifice diameter, a clear influence on the humidification is not apparent, this parameter needs to be investigated further. Finally, our new test setup allows for analysing the humidification of air (1) in a systematic way, (2) in relevant measurement ranges and (3) in comparison with optical analyses of the flow characteristics