TRR 154: Mathematical modelling, simulation and optimization using the example of gas networks
TRR 154: Mathematical modelling, simulation and optimization using the example of gas networks
批准号:
239904186
负责人:
金额:
$0.0万
依托单位国家:
德国
项目类别:
CRC/Transregios
财政年份:
--
资助国家:
德国
项目状态:
未结题
起止时间:
中文摘要
近年来,德国提出了雄心勃勃的气候保护倡议。为了使向可再生能源的过渡成为可能,不仅需要新建基础设施或改变其用途,还需要电网的现代化和高效运行。在向以电力和(绿色)氢气为基础的未来气候中性能源系统的转变中,天然气将在很长一段时间内继续发挥重要作用,原因包括(地缘)政治以及安全和供应方面的原因。特别是,氢气基础设施将建立在现有天然气电网能力的基础上。此外,预计氢气将越来越多地在应用中取代气体作为一种能源载体,因此向气候中性的过渡将顺利进行。CRC 154开始对气体网络进行分析,充分了解在数学建模、模拟和优化背景下的深刻和新的数学见解以及它们之间的联系对于回答核心问题是必要的。在这样做的时候,我们牢记,除了研究基本的数学理论之外,在现实世界中转移和使用这些理论需要相应的准备时间。因此,在过去几年中,特别是在过去一段时间里,取得了突出的新见解,其中考虑了更多动态方面、对不确定性的处理以及与天然气交易的相互关系,特别是与放松管制的能源市场的相互关系。在CRC154中取得的成果是深入合作和研究的结果。自那以后,CRC154建立和建立的结构已经成为大学内外其他更大规模研究合作的典范。其中包括团队合作,科学家们在他们的学科中反映并深化了CRC154的S发现,形成了子领域,不同学科的科学家在领域的耦合上工作,以及演示者的考虑,每个子领域解决与实践相关的问题,这些问题不是一个数学学科单独处理的,因此需要跨学科合作。CRC154正走在实现和完成其初始目标的良好道路上,例如,开发和数学分析基础充分的模型层次结构,包括误差分析或整数和连续模型的耦合,以及在固有的不完整或不确定信息的情况下进行决策的方法。在接下来的几年里,目标是利用现有和发展的数学能力,将这些方法和模型及其耦合提高到一个新的质量水平,以应对当前能源过渡的挑战。在能量背景下的问题与内在的数学挑战的同时,激发了在这个复杂的主题中工作的魅力,并让我们期待着有希望的和新的深刻见解。
英文摘要
In recent years, ambitious climate protection initiatives have been presented in Germany. To make the transition to renewable energy sources possible, not only does infrastructure need to be newly built or repurposed, it also requires modernization and efficient operation of the grids. In the transformation to a climate-neutral energy system of the future based on electricity and (green) hydrogen, natural gas will continue to play a significant role for a long time, for (geo)political as well as security and supply reasons. In particular, hydrogen infrastructure will build on existing gas grid capacity. In addition, it is expected that hydrogen will increasingly replace gas as an energy carrier in applications and thus the transitions to climate neutrality will take place smoothly.CRC 154 set out to do just that with the analysis of gas networks, knowing fully well that deep and new mathematical insights in the context of mathematical modeling, simulation, and optimization as well as the links between them are necessary to answer the questions at the core. In doing so, we kept in mind that, in addition to researching the underlying mathematical theories, transferring to, and using these theories in a real-world context requires a corresponding lead time. Thus, outstanding new insights have been gained in the past years and especially in the last period, in which more dynamic aspects, the handling of uncertainties as well as the interrelation to gas trading and especially deregulated energy markets have been considered.The findings achieved in CRC 154 are the result of intensive, cooperative collaboration and research. The structures that CRC 154 set up and established have since become models for other larger research collaborations within and outside the university. They include cooperation in teams, in which scientists reflect the CRC 154’s findings in their discipline and deepen them there, the formation of subareas, in which scientists of different disciplines work on the coupling of the fields, as well as the consideration of demonstrators, each of which addresses problems relevant to practice, which cannot be treated by one mathematical discipline alone and thus require interdisciplinary cooperation.CRC 154 is on an excellent path to achieve and complete its initial goals, such as the development and mathematical analysis of a well-founded hierarchy of models including error analysis or the coupling of integer and continuous models and methods for decision making with inherent incomplete or uncertain information. In the following years, the goal is to raise these methods and models and their couplings to the current challenges of energy transition to a new level of quality using the existing and developed mathematical competencies. The simultaneity of the questions in the energy context paired with the inner-mathematical challenges inspires the fascination to work in this complex of topics and lets expect promising and new deep insights.
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