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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.
The properties of diamond make it an attractive material for MEMS and sensor devices. We present the feasibility to fabricate membranes and cantilevers made of nano-(micro-) crystalline diamond films grown on Si/SiO2 substrates using microwave chemical vapour deposition (MWCVD). The patterning of micromechanical structures was performed by a combined process of femtosecond laser ablation and wet etching. We designed cantilever structures with varying lengths and widths (25, 50, 100, 200 and 300 μm). The cantilevers were made in a symmetric left- and right-hand configuration. An additional laser treatment was used to modify the mechanical properties of the left-hand cantilever. The deflection of the laser-treated, and non-treated sections was measured. The global mechanical system properties were simulated and corresponded with high accuracy to the measured results of deflection.
The properties of SiC and diamond make them attractive materials for MEMS and sensor devices. We innovated specific laser ablation techniques to fabricate membranes and cantilevers made of SiC or nano-(micro-) crystalline diamond films grown on Si/SiO2 substrates by microwave chemical vapour deposition (MWCVD). We started research to generate surface moulds to grow corrugated diamond films for membranes and cantilevers. A software tool was developed to support the design of micromechanical cantilevers. We can measure deformation and resonant frequency of diamond cantilevers and identify the global mechanical properties. A benchmark against finite element simulations enables an inverse identification of the specific system parameters and simplifies the characterization procedure.
Semiconducting metal oxides are widely used for solar cells, poto-catalysis, bio-active materials and gas sensors. Besides the material properties of the used semiconductor,the specific surface topology of the sensor determines the device performance. We investigate the preparation and transfer suitable metals onto LIPPS structures on glass for gas sensing applications.
Industrial demand side management has shown significant potential to increase the efficiency of industrial energy systems via flexibility management by model-driven optimization methods. We propose a grey-box model of an industrial food processing plant. The model relies on physical and process knowledge and mass and energy balances. The model parameters are estimated using a predictive error method. Optimization methods are applied to separately reduce the total energy consumption, total energy costs and the peak electricity demand of the plant. A viable potential for demand side management in the plant is identified by increasing the energy efficiency, shifting cooling power to low price periods or by peak load reduction.
Sie werden beobachtet
(2022)
Wahrheit braucht Vertrauen
(2022)
Die Arbeitswelt von morgen
(2022)