Entity

Time filter

Source Type


Muche T.,Zittau Gorlitz University of Applied Sciences
Applied Energy | Year: 2014

Pump storage plants are an important electricity storage technology at present. Investments in this technology are expected to increase. The necessary investment valuation often includes expected cash flows from future price-based unit commitment policies. A price-based unit commitment policy has to consider market price uncertainty and the information revealing nature of electricity markets. For this environment stochastic programming models are suggested to derive the optimal unit commitment policy. For the considered day-ahead price electricity market stochastic and deterministic unit commitment policies are comparable suggesting an application of easier implementable deterministic models. In order to identify suitable unit commitment and forecasting policies, deterministic unit commitment models are applied to actual day-ahead electricity prices of a whole year. As a result, a robust forecasting model should consider the unit commitment planning period. This robust forecasting models result in expected cash flows similar to realized ones allowing a reliable investment valuation. © 2013 Elsevier Ltd.


Lassig J.,Zittau Gorlitz University of Applied Sciences | Sudholt D.,University of Sheffield
Soft Computing | Year: 2013

Parallelization is becoming a more important issue for solving difficult optimization problems. Island models combine phases of independent evolution with migration where genetic information is spread out to neighbored islands. This can lead to an increased diversity within the population. Despite many successful applications, the reasons behind the success of island models are not well understood. We perform a first rigorous runtime analysis for island models and construct a function where phases of independent evolution as well as communication among the islands are essential. A simple island model with migration finds a global optimum in polynomial time, while panmictic populations as well as island models without migration need exponential time, with very high probability. Our results lead to new insights into the usefulness of migration, how information is propagated in island models, and how to set parameters such as the migration interval. This is a novel contribution to the theoretical foundation of parallel EAs. Further, we provide empirical results that complement the theoretical results, investigate the robustness with respect to the choice of the migration interval and compare various migration topologies using statistical tests. © 2013 Springer-Verlag Berlin Heidelberg.


Lassig J.,Zittau Gorlitz University of Applied Sciences | Sudholt D.,University of Sheffield
Evolutionary Computation | Year: 2014

We present a general method for analyzing the runtime of parallel evolutionary algorithms with spatially structured populations. Based on the fitness-level method, it yields upper bounds on the expected parallel runtime. This allows for a rigorous estimate of the speedup gained by parallelization. Tailored results are given for common migration topologies: ring graphs, torus graphs, hypercubes, and the complete graph. Example applications for pseudo-Boolean optimization show that our method is easy to apply and that it gives powerful results. In our examples the performance guarantees improve with the density of the topology. Surprisingly, even sparse topologies such as ring graphs lead to a significant speedup for many functions while not increasing the total number of function evaluations by more than a constant factor. We also identify which number of processors lead to the best guaranteed speedups, thus giving hints on how to parameterize parallel evolutionary algorithms. © 2014 by the Massachusetts Institute of Technology.


Mathe P.,Weierstrass Institute for Applied Analysis And Stochastics | Tautenhahn U.,Zittau Gorlitz University of Applied Sciences
Inverse Problems | Year: 2011

The authors explain how the major results which were obtained recently in Eggermont et al (2009 Inverse Problems 25 115018) can be derived from a more general perspective of recent regularization theory. By pursuing this further, the authors provide a general viewon regularization under general noise assumptions, including weakly and strongly controlled noise. The prospect is not to generalize previous work in this direction, but rather to envision the intrinsic structure present in regularization under general noise assumptions. In particular, the authors find variants of the discrepancy and the Lepskiǐ principle to choose the regularization parameter, albeit within different context and under different assumptions. © 2011 IOP Publishing Ltd.


Liao Y.,University of Bristol | Weber J.,Zittau Gorlitz University of Applied Sciences | Faul C.F.J.,University of Bristol
Macromolecules | Year: 2015

Carbon dioxide (CO2) capture from point sources like coal-fired power plants is a potential solution for stabilizing atmospheric CO2 content to avoid global warming. Sorbents with high and reversible CO2 uptake, high CO2 selectivity, good chemical and thermal stability, and low cost are desired for the separation of CO2 from N2 in flue or natural gas. We report here, for the first time, on the synthesis of new microporous polyimide (PI) networks from the condensation of perylene-3,4,9,10-tetracarboxylic dianhydride (PTCDA) and 1,3,5-triazine-2,4,6-triamine (melamine) using a Lewis acid catalyst zinc acetate/imidazole complex. These PI network materials, prepared in the absence and presence of dimethyl sulfoxide (DMSO) as weak solvent template, exhibit strong fluorescence. Nitrogen-containing carbons can be accessed from our PI networks via a simple thermal pyrolysis route. The successful construction of new microporous PI networks and derived N-containing carbons is shown here to provide promising CO2 sorbents with high uptake capacities (15 wt %) combined with exceptional selectivities over N2 (240), while their fluorescent properties can be exploited for simple sensing. © 2015 American Chemical Society.

Discover hidden collaborations