Stochastic optimisation for secure dynamic AC-load flow in hybrid multi-modal energy systems under uncertainty

不确定性下混合多模态能源系统中安全动态交流潮流的随机优化

• 批准号: 359839719
• 负责人: Professor Dr. Rüdiger Schultz
• 金额: --
• 依托单位: Arbeitsgruppe "Optimierung und Algorithmische Diskrete Mathematik"
• 依托单位国家: 德国
• 项目类别: Priority Programmes
• 财政年份: 2017
• 资助国家: 德国
• 起止时间: 2016-12-31 至 2021-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/359839719?language=en
• 关键词: Stochastic; optimisation; secure; dynamic; AC

Grid-bound resources, in the present project foremostly electricity, but also gas and water, will have a critical role in a world of increased economic activity, and so will the grids themselves. For their design and operation, the growing complexity of decision making under data uncertainty poses challenging optimisation problems for whose solution the advancement of the existing methodology is indispensable. The latter starts with conceptual work on the proper treatment of risk, nonlinearity, and the large-sale nature of resulting models. Optimal power flow (OPF) in alternate-current (AC) networks has a pivotal role, both since it is indispensable for realistic modeling and also mathematically rewarding. Another crucial aspect is the proper inclusion of external uncertainty due to volatile input from renewablesIn the core of the planned investigations there is the development of an appropriate framework of new integrated mathematical models and tailored methods of ``engineering value'' supporting research into those energy systems prone to forecast errors and uncertainty. In particular, the following topics are addressed:stochastic contingency management, network stability, management of congestions in AC networks under renewable infeed uncertainty, and risk aversion in multimodal energy systems are addressed.

受电网约束的资源，在本项目中主要是电力，但也包括天然气和水，将在经济活动增加的世界中发挥关键作用， 网格本身。 对于它们的设计和操作，在数据不确定性下决策的日益复杂性提出了具有挑战性的优化问题，其解决方案的现有方法的进步是必不可少的。后者从正确处理风险、非线性和由此产生的模型的大销售性质的概念性工作开始。交流网络的最优潮流（OPF）具有关键的作用，因为它是不可或缺的现实建模和数学奖励。另一个关键方面是适当纳入外部不确定性，由于可再生能源的不稳定投入，在计划的调查的核心是发展一个适当的框架，新的综合数学模型和量身定制的“工程价值”方法，支持对那些容易出现预测误差和不确定性的能源系统的研究。 特别是，以下主题进行了讨论：随机应急管理，网络稳定性，管理可再生的馈入不确定性下的AC网络中的故障，并在多模式能源系统的风险规避。