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This study analyses the expected utilization of an urban distribution grid under high penetration of photovoltaic and e-mobility with charging infrastructure on a residential level. The grid utilization and the corresponding power flow are evaluated, while varying the control strategies and photovoltaic installed capacity in different scenarios. Four scenarios are used to analyze the impact of e-mobility. The individual mobility demand is modelled based on the largest German studies on mobility “Mobilität in Deutschland”, which is carried out every 5 years. To estimate the ramp-up of photovoltaic generation, a potential analysis of the roof surfaces in the supply area is carried out via an evaluation of an open solar potential study. The photovoltaic feed-in time series is derived individually for each installed system in a resolution of 15 min. The residential consumption is estimated using historical smart meter data, which are collected in London between 2012 and 2014. For a realistic charging demand, each residential household decides daily on the state of charge if their vehicle requires to be charged. The resulting charging time series depends on the underlying behavior scenario. Market prices and mobility demand are therefore used as scenario input parameters for a utility function based on the current state of charge to model individual behavior. The aggregated electricity demand is the starting point of the power flow calculation. The evaluation is carried out for an urban region with approximately 3100 residents. The analysis shows that increased penetration of photovoltaics combined with a flexible and adaptive charging strategy can maximize PV usage and reduce the need for congestion-related intervention by the grid operator by reducing the amount of kWh charged from the grid by 30% which reduces the average price of a charged kWh by 35% to 14 ct/kWh from 21.8 ct/kWh without PV optimization. The resulting grid congestions are managed by implementing an intelligent price or control signal. The analysis took place using data from a real German grid with 10 subgrids. The entire software can be adapted for the analysis of different distribution grids and is publicly available as an open-source software library on GitHub.
Non-nuclear and non-fossil energy resources and their possibilities for future power generation
(1975)
It must be stressed that the assessment of the exploitation possibilities of the energy resources discussed in this paper requires further studies. With this proviso, the situation can be provisionally summarised as follows: The total potential of known geothermal steam sources is only 64 GW. Geothermal energy could therefore only make a significant contribution to covering the worldwide power needs if we succeed in exploiting dry geothermal reservoirs. Exploitation of tidal energy is limited to a few geographically favourable locations. The power generation potential at these locations is only about 64 GW. An important drawback of tidal power is discontinuous power generation. Large scale exploitation of wind, wave and glacier energy, and of ocean heat, requires solution of a number of technological problems. The environmental effects of exploitation of these energy resources are to some extent of a qualitatively different nature from those of operation of fossil-fuel-fired and of nuclear power plants. The scanty knowledge in this area often results in these effects being underestimated. In any case, however, it would be deliberately misleading to postulate that any form of power generation is possible without some detrimental effects on the environment. It may be stated in conclusion that, owing to their small potential or to the as yet insufficiently advanced technological development, none of the energy resources discussed in this paper can make a significant contribution to the solution of middle-term energy supply problems, i.e., to a rapid replacement of mineral oil and natural gas.
In recent years, many onshore wind turbines are erected in seismic active regions and on soils with poor load bearing capacity, where pile grids are inevitable to transfer the loads into the ground. In this contribution, a realistic multi pile grid is designed to analyze the dynamics of a wind turbine tower including frequency dependent soil-structure-interaction. It turns out that different foundations on varying soil configurations heavily influence the vibration response. While the vibration amplitude is mostly attenuated, certain unfavorable combinations of structure and soil parameters lead to amplification in the range of the system's natural frequencies. This testifies the need for overall dynamic analysis in the assessment of the dynamic stability and the holistic frequency tuning of the turbines.
Recent earthquakes as the 2012 Emilia earthquake sequence showed that recently built unreinforced masonry (URM) buildings behaved much better than expected and sustained, despite the maximum PGA values ranged between 0.20–0.30 g, either minor damage or structural damage that is deemed repairable. Especially low-rise residential and commercial masonry buildings with a code-conforming seismic design and detailing behaved in general very well without substantial damages. The low damage grades of modern masonry buildings that was observed during this earthquake series highlighted again that codified design procedures based on linear analysis can be rather conservative. Although advances in simulation tools make nonlinear calculation methods more readily accessible to designers, linear analyses will still be the standard design method for years to come. The present paper aims to improve the linear seismic design method by providing a proper definition of the q-factor of URM buildings. These q-factors are derived for low-rise URM buildings with rigid diaphragms which represent recent construction practise in low to moderate seismic areas of Italy and Germany. The behaviour factor components for deformation and energy dissipation capacity and for overstrength due to the redistribution of forces are derived by means of pushover analyses. Furthermore, considerations on the behaviour factor component due to other sources of overstrength in masonry buildings are presented. As a result of the investigations, rationally based values of the behaviour factor q to be used in linear analyses in the range of 2.0–3.0 are proposed.
The proposed Den Haag Zuidwest district heating system of the city of The Hague consists of a deep doublet in a Jurassic sandstone layer that is designed for a production temperature of 75 °C and a reinjection temperature of 40 °C at a flow rate of 150 m3 h−1. The prediction of reservoir temperature and production behavior is crucial for success of the proposed geothermal doublet. This work presents the results of a study of the important geothermal and geohydrological issues for the doublet design. In the first phase of the study, the influences of the three-dimensional (3D) structures of anticlines and synclines on the temperature field were examined. A comprehensive petrophysical investigation was performed to build a large scale 3D-model of the reservoir. Several bottomhole temperatures (BHTs), as well as petrophysical logs were used to calibrate the model using thermal conductivity measurements on 50 samples from boreholes in different lithological units in the study area. Profiles and cross sections extracted from the calculated temperature field were used to study the temperature in the surrounding areas of the planned doublet. In the second phase of the project, a detailed 3D numerical reservoir model was set up, with the aim of predicting the evolution of the producer and injector temperatures, and the extent of the cooled area around the injector. The temperature model from the first phase provided the boundary conditions for the reservoir model. Hydraulic parameters for the target horizons, such as porosity and permeability, were taken from data available from the nearby exploration wells. The simulation results are encouraging as no significant thermal breakthrough is predicted. For the originally planned location of the producer, the extracted water temperature is predicted to be around 79 °C, with an almost negligible cooling in the first 50 years of production. When the producer is located shallower parts of the reservoir, the yield water temperatures is lower, starting at ≈76 °C and decreasing to ≈74 °C after 50 years of operation. This comparatively larger decrease in temperature with time is caused by the structural feature of the reservoir, namely a higher dip causes the cooler water to easily move downward. In view of the poor reservoir data, the reservoir simulation model is constructed to allow iterative updates using data assimilation during planned drilling, testing, and production phases. Measurements during an 8 h pumping test carried out in late 2010 suggest that a flow rate of 150 m3 h−1 is achievable. Fluid temperatures of 76.5 °C were measured, which is very close to the predicted value.
A refined substructure technique in the frequency domain is developed, which permits consideration of the interaction effects among adjacent containers through the supporting deformable soil medium. The tank-liquid systems are represented by means of mechanical models, whereas discrete springs and dashpots stand for the soil beneath the foundations. The proposed model is employed to assess the responses of adjacent circular, cylindrical tanks for harmonic and seismic excitations over wide range of tank proportions and soil conditions. The influence of the number, spatial arrangement of the containers and their distance on the overall system's behavior is addressed. The results indicate that the cross-interaction effects can substantially alter the impulsive components of response of each individual element in a tank farm. The degree of this impact is primarily controlled by the tank proportions and the proximity of the predominant natural frequencies of the shell-liquid-soil systems and the input seismic motion. The group effects should be not a priori disregarded, unless the tanks are founded on shallow soil deposit overlying very stiff material or bedrock.
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.
Often, detailed simulations of heat conduction in complicated, porous media have large runtimes. Then homogenization is a powerful tool to speed up the calculations by preserving accurate solutions at the same time. Unfortunately real structures are generally non-periodic, which requires unpractical, complicated homogenization techniques. We demonstrate in this paper, that the application of simple, periodic techniques to realistic media, that are just close to periodic, gives accurate, approximative solutions. In order to obtain effective parameters for the homogenized heat equation, we have to solve a so called “cell problem”. In contrast to periodic structures it is not trivial to determine a suitable unit cell, which represents a non-periodic media. To overcome this problem, we give a rule of thumb on how to choose a good cell. Finally we demonstrate the efficiency of our method for virtually generated foams as well as real foams and compare these results to periodic structures.
Numerical solution of the heat equation with non-linear, time derivative-dependent source term
(2010)
The mathematical modeling of heat conduction with adsorption effects in coated metal structures yields the heat equation with piecewise smooth coefficients and a new kind of source term. This term is special, because it is non-linear and furthermore depends on a time derivative. In our approach we reformulated this as a new problem for the usual heat equation, without source term but with a new non-linear coefficient. We gave an existence and uniqueness proof for the weak solution of the reformulated problem. To obtain a numerical solution, we developed a semi-implicit and a fully implicit finite volume method. We compared these two methods theoretically as well as numerically. Finally, as practical application, we simulated the heat conduction in coated aluminum fibers with adsorption in the zeolite coating. Copyright © 2010 John Wiley & Sons, Ltd.
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.
The article presents the investigation of the seismic behaviour of a modern URM building located in the municipality of Finale Emilia in province of Modena, Northern Italy. The building is situated in the centre of the series of the 2012 Northern Italy earthquakes and has not suffered any damage during the earthquake series in 2012. The observed earthquake resistance of the building is compared with predicted resistances based on linear and nonlinear design approaches according to Eurocode. Furthermore, probabilistic analyses based on nonlinear calculation models taking into account scattering of the most relevant input parameters are carried out to identify their influence to the results and to derive fragility curves.
The 2012 Emilia-Romagna earthquake, that mainly struck the homonymous Italian region provoking 28 casualties and damage to thousands of structures and infrastructures, is an exceptional source of information to question, investigate, and challenge the validity of seismic fragility functions and loss curves from an empirical standpoint. Among the most recent seismic events taking place in Europe, that of Emilia-Romagna is quite likely one of the best documented, not only in terms of experienced damages, but also for what concerns occurred losses and necessary reconstruction costs. In fact, in order to manage the compensations in a fair way both to citizens and business owners, soon after the seismic sequence, the regional administrative authority started (1) collecting damage and consequence-related data, (2) evaluating information sources and (3) taking care of the cross-checking of various reports. A specific database—so-called Sistema Informativo Gestione Europa (SFINGE)—was devoted to damaged business activities. As a result, 7 years after the seismic events, scientists can rely on a one-of-a-kind, vast and consistent database, containing information about (among other things): (1) buildings’ location and dimensions, (2) occurred structural damages, (3) experienced direct economic losses and (4) related reconstruction costs. The present work is focused on a specific data subset of SFINGE, whose elements are Long-Span-Beam buildings (mostly precast) deployed for business activities in industry, trade or agriculture. With the available set of data, empirical fragility functions, cost and loss ratio curves are elaborated, that may be included within existing Performance Based Earthquake Engineering assessment toolkits.
Monte Carlo Tree Search (MCTS) is a search technique that in the last decade emerged as a major breakthrough for Artificial Intelligence applications regarding board- and video-games. In 2016, AlphaGo, an MCTS-based software agent, outperformed the human world champion of the board game Go. This game was for long considered almost infeasible for machines, due to its immense search space and the need for a long-term strategy. Since this historical success, MCTS is considered as an effective new approach for many other scientific and technical problems. Interestingly, civil structural engineering, as a discipline, offers many tasks whose solution may benefit from intelligent search and in particular from adopting MCTS as a search tool. In this work, we show how MCTS can be adapted to search for suitable solutions of a structural engineering design problem. The problem consists of choosing the load-bearing elements in a reference reinforced concrete structure, so to achieve a set of specific dynamic characteristics. In the paper, we report the results obtained by applying both a plain and a hybrid version of single-agent MCTS. The hybrid approach consists of an integration of both MCTS and classic Genetic Algorithm (GA), the latter also serving as a term of comparison for the results. The study’s outcomes may open new perspectives for the adoption of MCTS as a design tool for civil engineers.
In many cities, diesel buses are being replaced by electric buses with the aim of reducing local emissions and thus improving air quality. The protection of the environment and the health of the population is the highest priority of our society. For the transport companies that operate these buses, not only ecological issues but also economic issues are of great importance. Due to the high purchase costs of electric buses compared to conventional buses, operators are forced to use electric vehicles in a targeted manner in order to ensure amortization over the service life of the vehicles. A compromise between ecology and economy must be found in order to both protect the environment and ensure economical operation of the buses.
In this study, we present a new methodology for optimizing the vehicles’ charging time as a function of the parameters CO₂eq emissions and electricity costs. Based on recorded driving profiles in daily bus operation, the energy demands of conventional and electric buses are calculated for the passenger transportation in the city of Aachen in 2017. Different charging scenarios are defined to analyze the influence of the temporal variability of CO₂eq intensity and electricity price on the environmental impact and economy of the bus. For every individual day of a year, charging periods with the lowest and highest costs and emissions are identified and recommendations for daily bus operation are made. To enable both the ecological and economical operation of the bus, the parameters of electricity price and CO₂ are weighted differently, and several charging periods are proposed, taking into account the priorities previously set. A sensitivity analysis is carried out to evaluate the influence of selected parameters and to derive recommendations for improving the ecological and economic balance of the battery-powered electric vehicle.
In all scenarios, the optimization of the charging period results in energy cost savings of a maximum of 13.6% compared to charging at a fixed electricity price. The savings potential of CO₂eq emissions is similar, at 14.9%. From an economic point of view, charging between 2 a.m. and 4 a.m. results in the lowest energy costs on average. The CO₂eq intensity is also low in this period, but midday charging leads to the largest savings in CO₂eq emissions. From a life cycle perspective, the electric bus is not economically competitive with the conventional bus. However, from an ecological point of view, the electric bus saves on average 37.5% CO₂eq emissions over its service life compared to the diesel bus. The reduction potential is maximized if the electric vehicle exclusively consumes electricity from solar and wind power.
Large scale central receiver systems typically deploy between thousands to more than a hundred thousand heliostats. During solar operation, each heliostat is aligned individually in such a way that the overall surface normal bisects the angle between the sun’s position and the aim point coordinate on the receiver. Due to various tracking error sources, achieving accurate alignment ≤1 mrad for all the heliostats with respect to the aim points on the receiver without a calibration system can be regarded as unrealistic. Therefore, a calibration system is necessary not only to improve the aiming accuracy for achieving desired flux distributions but also to reduce or eliminate spillage. An overview of current larger-scale central receiver systems (CRS), tracking error sources and the basic requirements of an ideal calibration system is presented. Leading up to the main topic, a description of general and specific terms on the topics heliostat calibration and tracking control clarifies the terminology used in this work. Various figures illustrate the signal flows along various typical components as well as the corresponding monitoring or measuring devices that indicate or measure along the signal (or effect) chain. The numerous calibration systems are described in detail and classified in groups. Two tables allow the juxtaposition of the calibration methods for a better comparison. In an assessment, the advantages and disadvantages of individual calibration methods are presented.
Plans for investigations of subthreshold K+ production in p+A collisions / O. W. B. Schult [u.a.]
(1995)
In order to realistically predict and optimize the actual performance of a concentrating solar power (CSP) plant sophisticated simulation models and methods are required. This paper presents a detailed dynamic simulation model for a Molten Salt Solar Tower (MST) system, which is capable of simulating transient operation including detailed startup and shutdown procedures including drainage and refill. For appropriate representation of the transient behavior of the receiver as well as replication of local bulk and surface temperatures a discretized receiver model based on a novel homogeneous two-phase (2P) flow modelling approach is implemented in Modelica Dymola®. This allows for reasonable representation of the very different hydraulic and thermal properties of molten salt versus air as well as the transition between both. This dynamic 2P receiver model is embedded in a comprehensive one-dimensional model of a commercial scale MST system and coupled with a transient receiver flux density distribution from raytracing based heliostat field simulation. This enables for detailed process prediction with reasonable computational effort, while providing data such as local salt film and wall temperatures, realistic control behavior as well as net performance of the overall system. Besides a model description, this paper presents some results of a validation as well as the simulation of a complete startup procedure. Finally, a study on numerical simulation performance and grid dependencies is presented and discussed.