500 Naturwissenschaften und Mathematik
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Traditional power grids are mainly based on centralized power generation and subsequent distribution. The increasing penetration of distributed renewable energy sources and the growing number of electrical loads is creating difficulties in balancing supply and demand and threatens the secure and efficient operation of power grids. At the same time, households hold an increasing amount of flexibility, which can be exploited by demand-side management to decrease customer cost and support grid operation. Compared to the collection of individual flexibilities, aggregation reduces optimization complexity, protects households’ privacy, and lowers the communication effort. In mathematical terms, each flexibility is modeled by a set of power profiles, and the aggregated flexibility is modeled by the Minkowski sum of individual flexibilities. As the exact Minkowski sum calculation is generally computationally prohibitive, various approximations can be found in the literature. The main contribution of this paper is a comparative evaluation of several approximation algorithms in terms of novel quality criteria, computational complexity, and communication effort using realistic data. Furthermore, we investigate the dependence of selected comparison criteria on the time horizon length and on the number of households. Our results indicate that none of the algorithms perform satisfactorily in all categories. Hence, we provide guidelines on the application-dependent algorithm choice. Moreover, we demonstrate a major drawback of some inner approximations, namely that they may lead to situations in which not using the flexibility is impossible, which may be suboptimal in certain situations.
Gas hydrates are usually synthesized by bringing together a pressurized gas and liquid or solid water. In both cases, the transport of gas or water to the hydrate growth site is hindered once an initial film of hydrate has grown at the water–gas interface. A seemingly forgotten gas-phase technique overcomes this problem by slowly depositing water vapor on a cold surface in the presence of the pressurized guest gas. Despite being used for the synthesis of low-formation-pressure hydrates, it has not yet been tested for hydrates of CO 2 and CH 4 . Moreover, the potential of the technique for the study of hydrate decomposition has not been recognized yet. We employ two advanced implementations of the condensation technique to form hydrates of CO 2 and CH 4 and demonstrate the applicability of the process for the study of hydrate decomposition and the phenomenon of self-preservation. Our results show that CO 2 and CH 4 hydrate samples deposited on graphite at 261–265 K are almost pure hydrates with an ice fraction of less than 8%. Rapid depressurization experiments with thin deposits (approx. 330 mm thickness) of CO 2 hydrate on an aluminum surface at 265 K yield identical dissociation curves when the deposition is done at identical pressure. However, hydrates deposited at 1 MPa almost completely withstand decomposition after rapid depressurization to 0.1 MPa, while samples deposited at 2 MPa decompose 7 times faster. Therefore, this synthesis technique is not only applicable for the study of hydrate decomposition but can also be used for the controlled deposition of a super-preserved hydrate.
Clathrate hydrates, or hydrates for short, are inclusion compounds in which water molecules form a hydrogen-bonded host lattice that accommodates the guest molecules. While vast amounts of hydrates are known to exist in seafloor sediments and in the permafrost on Earth, these occurrences might be dwarfed by the amounts of hydrates occurring in space and on celestial bodies. Since methane is the primary guest molecule in most of the natural occurrences on Earth, hydrates are considered a promising source of energy. Moreover, the ability of one volume of hydrate to store about 170 volumes of gas, make hydrates a promising functional material for various industrial applications. While the static properties of hydrates are reasonably well known, the dynamics of hydrate formation and decomposition are insufficiently understood. For instance, the stochastic period of hydrate nucleation, the memory effect, and the self-preservation phenomenon complicate the development of predictive models of hydrate dynamics. Additionally, the influence of meso- and macroscopic defects as well as the roles of mass and heat transport on different length scales remain to be clarified.
Due to its non-invasive and non-destructive nature and the high spatial resolution of approx. 1µm or even less, micro-computed X-ray attenuation tomography ( µCT ) seems to be the perfect method for the study of the evolving structures of forming or decomposing hydrates on the meso- and macroscopic length scale. However, for the naturally occurring hydrates of low atomic number guests the contrast between hydrate, ice, and liquid water is typically very weak because of similar X-ray attenuation coefficients. So far, good contrast was only restricted to synchrotron beamline experiments which utilize the phase information of monochromatic X-rays.
In this thesis it is shown that with the help of a newly developed sample cell, a contrast between the hydrate and the ice phase sufficiently good for the reliable segmentation of the materials can also be achieved in conventional tube-based µCT. An accurate pressure and temperature management, i.e., the added functionality of the cell, further allows for cross-correlation of structural and thermodynamic data. The capability of this µCT setup is demonstrated in a series of studies on the formation and decomposition of hydrates which yield new insights for the development of a novel route to hydrate synthesis. At last, this thesis points towards possibilities how better models of hydrate formation and decomposition can be developed with the aid of µCT and computer simulations.
The electricity demand due to the increasing number of EVs presents new challenges for the operation of the electricity network, especially for the distribution grids. The existing grid infrastructure may not be sufficient to meet the new demands imposed by the integration of EVs. Thus, EV charging may possibly lead to reliability and stability issues, especially during the peak demand periods. Demand side management (DSM) is a potential and promising approach for mitigation of the resulting impacts. In this work, we developed an autonomous DSM strategy for optimal charging of EVs to minimize the charging cost and we conducted a simulation study to evaluate the impacts to the grid operation. The proposed approach only requires a one way communicated incentive. Real profiles from an Austrian study on mobility behavior are used to simulate the usage of the EVs. Furthermore, real smart meter data are used to simulate the household base load profiles and a real low voltage grid topology is considered in the load flow simulation. Day-ahead electricity stock market prices are used as the incentive to drive the optimization. The results for the optimum charging strategy is determined and compared to uncontrolled EV charging. The results for the optimum charging strategy show a potential cost saving of about 30.8% compared to uncontrolled EV charging. Although autonomous DSM of EVs achieves a shift of load as pursued, distribution grid operation may be substantially affected by it. We show that in the case of real time price driven operation, voltage drops and elevated peak to average powers result from the coincident charging of vehicles during favourable time slots.